The Biological and Social Dimensions of Human Knowledge 3031391365, 9783031391361

Table of contents :
Preface
Contents
1: Naturalistic Epistemology
Naturalism and Its Adversaries
Externalist Theories of Knowledge
Knowledge as a Disposition for Acting and Thinking
Cognition, Knowledge, and Understanding
2: Knowledge as a Natural Phenomenon
Knowledge in Non-human Animals
Cognitive Schemas and Animal Knowledge
Beliefs, Desires, and Recognition
Acquaintance as Image-based Knowledge
The Evolution of the Mind
Doxastic Knowledge as Concept-based Knowledge
3: Experiential Knowledge Without Beliefs
Ideas, Beliefs, and Thoughts
Experiential Knowledge as Behavioral or Actional Knowledge
Why Instincts Are Not Knowledge
Embodied Cognition and the Extended Mind
Blending of Knowing-how and Knowing-that
4: Human Sensory Knowledge
Knowledge as Justified True Beliefs
Sensory Knowledge and Belief-acquisition
The Logical Space of Reason
Knowledge Before Language
Empirical Evidence in Support
The Sensorimotor Space
5: Linking Experiences to the Social World
The Evolution of Language
Becoming Sapiens
Ostension, Induction, and Correlations
Narrow Content and Broad Content
Shared Intentions
6: Self-awareness, Language, and Empirical Knowledge
Speaking as Embodied Knowledge
Speaker Meaning Determines Word Meaning
The Rise of Linguistic Conventions
Empirical Knowledge and the Evolution of Language
From Concrete to Abstract Thinking
7: Social Knowledge, Agreements, and Testimonies
From Language to Social Epistemology
Perlocutionary Effects and Social Knowledge
Objection: Agreement is Not the Same as Truth
Nothing But the Truth
Social Knowledge and Testimony
Knowledge Beyond Empirical Beliefs
8: Science and its Epistemic Limits
What Are We Adapted to Know, and What Are We Adapted to Understand?
The Introduction of Invisible But Observable Objects
Why Scientific Theories Do Not Express de re Knowledge
Mathematics and Empirical Knowledge
9: Epistemic Values from a Naturalistic Perspective
The Evolution of Understanding
A Naturalist Approach
The Cognitive Standards
Reflection-based Understanding
Epistemic Values and the Naturalist Stance
Literature
Index

Citation preview

The Biological and Social Dimensions of Human Knowledge Jan Faye

The Biological and Social Dimensions of Human Knowledge

Jan Faye

The Biological and Social Dimensions of Human Knowledge

Jan Faye Department of Communication University of Copenhagen Copenhagen, Denmark

ISBN 978-3-031-39136-1    ISBN 978-3-031-39137-8 (eBook) https://doi.org/10.1007/978-3-031-39137-8 © The Editor(s) (if applicable) and The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023 This work is subject to copyright. All rights are solely and exclusively licensed by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors, and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, expressed or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Cover illustration: Alexei Novikov / Alamy Stock Photo This Palgrave Macmillan imprint is published by the registered company Springer Nature Switzerland AG. The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland Paper in this product is recyclable.

Preface

What you are about to read is a naturalistic account of human knowledge in a biological and social setting. In contrast to traditional epistemology, my book attempts to develop an epistemological framework by appeal to human evolution and societal conditions. As a philosopher, I am often amazed to learn how many of my peers still think they can do epistemology without considering what is going on in science. Not because I think science can solve philosophical problems, but because epistemological suggestions become hollow unless we consider what biology and cognitive science actually know about human as well as non-human thinking. Paraphrasing Imre Lakatos’ famous words, we may proclaim, “Science without philosophy is blind, philosophy without science is empty.” Indeed, epistemological traditionalists’ response usually is that epistemology is a normative discipline whereas science is mere descriptive. In spite of this common response, I argue that although our epistemic norms and values are social conventions, they have their roots in our observation of our own natural ways of thinking that have evolved through natural selection. Also I am amazed to discover how much is included as scientific knowledge. Today many scholars within the humanities and the social sciences believe that all human behavior can be accounted for in terms of social construction, ignoring everything we know about biology. I recognize that much theorizing in these fields is meant to provide abstract v

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interpretations of cultural and social phenomena, which may be phrased as understanding our Lebenswelt to use a German expression. However, if these interpretations are not merely phantoms of our imagination, but express fruitful conceptions of our life world, they must meet some elementary empirical demands of applicability and refutability. It is by these conditions that human knowledge has developed. The philosophical disrespect for considering the biological contribution to the achievement of human knowledge is traceable back to the tradition instigated by Descartes’ division between mind and matter. Humans could use the mind’s first principles to represent matter whose nature was foreign to the mind. The outcomes were the natural sciences. The mind’s principles were the objects of the mind’s own reflection and were left for philosophy to study. Still, the natural sciences were, when all was said and done, a representation of the mind’s a priori principles and, if one believed that human beings, as God’s creations, were far superior to other beasts, one is not far from accepting that our understanding of human knowledge is to be found in our mind’s own a priori principles. Although much of this development belongs to history, it gave rise to a tradition that silently determines the analytic perspective under which many still study human knowledge, even today. As Ruth Millikan remarked in her Language: A Biological Model about conceptual analysis—the philosophical method that both she and I were brought up with—“this tradition of philosophy managed to continue to understand itself as an a priori discipline after the demise of rationalism. Otherwise it was thought unclear why philosophers wouldn’t need to turn to data or to experimental work in order to carry out their tasks” (p. 122). Therefore, philosophers often reduce the epistemological challenge to questions about the necessary and sufficient conditions for attributing knowledge to a person. Thus, on the one hand, within traditional analytic philosophy we encounter two general propositions, which stand in opposition to naturalistic philosophy. First: the attribution of knowledge to an individual is normative and relies on personal justification. A corollary of this principle is that animals cannot have knowledge. Second: the use of concepts is essentially linked to language. Ergo animals do not have concepts. I accept

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neither of these two fundamental claims nor the methodology behind them. On the other hand, a naturalistic epistemology is based on the results of science. But if a naturalistic epistemology is to make an independent and constructive contribution to our understanding of the diverse results of the sciences, it must produce a philosophical interpretation of how these observations can be connected into a whole. Methodologically, the naturalistic approach to interpretations is similar to any other construction of scientific theories. It stipulates the use of a number of different terms based on various considerations and then seeks to justify this interpretation by looking at which of the probable interpretations gives us the best and most coherent explanation of as many phenomena as possible. For this reason the present book breaks methodologically with the Cartesian tradition and, like the works of other naturalists, treats human knowledge as a natural phenomenon being studied by a variety of disciplines. Its purpose is to lay down a conceptual framework by which experiential knowledge—evolutionarily the first version of knowledge—is explainable in terms of its biological function, whereas the much later evolved versions of knowledge, such as empirical and theoretical knowledge, require certain social standards. Especially I focus on why much of our sensory and behavioral knowledge is reliable but neither justified nor known to be true, as those terms are traditionally defined. As epistemic prescriptions, ‘truth’ and ‘justification’ enter epistemology with the expansion of our domain of beliefs to include things that we cannot directly experience with our naked eye. This expansion took place, I posit, as humans and other primates began to master language to express their thoughts. At that point in evolutionary history human knowledge moved from merely resting on cognitively reliable processes to the involvement of communicative commitments to truth and justification. Here I want to thank a number of people who, during my work with the manuscript, have spent time reading and commenting on parts of it. I am grateful to Nina Bonderup Dohn, Finn Collin, Peter Harder, Rasmus Jaksland, Lars-Göran Johansson, Ib Ulbæk, and an anonymous reviewer for their insightful comments and suggestions to the immense benefit of the final result. Also I want to express my special gratitude to Henry Folse who again prevented me from making too many idiomatic

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errors. His challenging comments are sometimes overwhelming, and even though we substantially agree, they always make me think twice. Finally, I would like to thank Steen Søgaard for his valuable comments and assistance with the proofreading. Needless to say, none of these people are responsible for any inconsistency or for my inaptitude to meet the readers’ expectations. København, Denmark

Jan Faye

Contents

1 N  aturalistic Epistemology  1 2 Knowledge as a Natural Phenomenon 31 3 E  xperiential Knowledge Without Beliefs 61 4 H  uman Sensory Knowledge 99 5 Linking Experiences to the Social World133 6 Self-awareness, Language, and Empirical Knowledge169 7 Social Knowledge, Agreements, and Testimonies201 8 Science and its Epistemic Limits231 9 Epistemic Values from a Naturalistic Perspective271 L  iterature299 I ndex311 ix

1 Naturalistic Epistemology

It is evident that human beings possess knowledge. We often remember truthfully what happened in the past. We also know what is going on in our everyday life through direct sensory experiences or from testimonies and other social sources. In an attempt to understand human knowledge, philosophers have for centuries focused on what elevates true beliefs above mere opinions. Traditionally their responses have been that humans are individually responsible for their beliefs being justified. And beliefs are justified as true just in case they meet certain epistemic norms such as being derivable from incontestable, self-authoritative beliefs or being part of a coherent body of beliefs. Although different epistemologies disagreed on what those norms were, it was widely assumed that the goal of a theory of knowledge was to formulate them. Now those days are changing. The scope of knowledge has broadened such that some philosophers are now prepared to ascribe knowledge to individuals if their beliefs are true and acquired by a reliable process. A reliable process may be one that follows certain epistemic norms; but also one, if you are a naturalist, we automatically follow due to our biological heritage. This raises all sorts of questions: in which situations do we need to appeal to epistemic norms and in which can we just rely on innate © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. Faye, The Biological and Social Dimensions of Human Knowledge, https://doi.org/10.1007/978-3-031-39137-8_1

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mechanism of knowledge acquisition? Do animals, small children, and adults suffering from dementia possess knowledge in case cognitive deficits exclude them from being personally responsible for believing what they believe? To mention just a few. One such question is whether we obtain all of our knowledge because of experiences after birth or is some knowledge innate, in the sense of given to us by genetically transferred information. The actual content of sensory knowledge is something we have learned by experience. What is innate is the capacity to learn through experience. Yet, the real issue is whether at least some inherited aptitudes, which we call “instincts,” reasonably count as knowledge. The proper answer might depend on the respective functions of instincts and knowledge. That would mean they would have different goals. But both instincts and knowledge seem to exist for the same purpose. Apart from the most elevated forms, most knowledge is cognitive states whose function is to guide our behavior for the purpose of survival and reproduction if we are to believe the theory of biological evolution. We acquire knowledge for the sake of our own safety. Concerning instincts, they seem not much different except for the possible genetic transmission.

Naturalism and Its Adversaries Around the time of Descartes, it was perhaps not obvious that non-­ human animals might have knowledge. But his view that animals were pure automata survived more or less intact up to recent days, in spite of the fact that the great natural philosopher, David Hume, famously announced that “no truth appears to me more evident, than that beasts are endow’d with thought and reason as well as men.”1 He laid out his justification by saying that given animals’ behavior this is the simplest hypothesis. Hume’s argument deserves quotation in its entirety, remembering that he stated his opinion more than a century before Charles Darwin published his Origin.  Hume, D. (1739–1740/2007). A Treatise of Human Nature. Oxford University Press, Sec. 16, p. 118. 1

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’Tis from the resemblance of the external actions of animals to those we ourselves perform, that we judge their internal likewise to resemble ours; and the same principle of reasoning, carry’d one step farther, will make us conclude that since our internal actions resemble each other, the causes, from which they are deriv’d, must also be resembling. When any hypothesis, therefore, is advanc’d to explain a mental operation, which is common to men and beasts, we must apply the same hypothesis to both; and as every true hypothesis will abide this trial, so I may venture to affirm, that no false one will ever be able to endure it. The common defect of those systems, which philosophers have employ’d to account for the actions of the mind, is, that they suppose such a subtility and refinement of thought, as not only exceeds the capacity of mere animals, but even of children and the common people in our own species; who are notwithstanding susceptible of the same emotions and affections as persons of the most accomplish’d genius and understanding. Such a subtility is a clear proof of the falsehood, as the contrary simplicity of the truth, of any system.2

Yet, Hume’s seemingly true conclusion was almost universally disregarded. Even after Darwin, it took science another century or more before it really began to accommodate to the possibility that animal studies might help us to understand their mental powers, just as Hume had proposed. One impediment in reaching Hume’s insight was a continuing deep ignorance of animals’ mental capacities. The behaviorists refused to acknowledge cognitive abilities in animals since they thought appealing to such to explain animal behavior was not open to empirical investigation and so bad science. A similar attitude toward animal cognition was present among the instinctivists who were only willing to explain animal behavior as something guided by inborn dispositions. No reasoning, no thinking was involved. Today, however, scientists’ understanding of non-­ human animals is more advanced than in earlier periods of human history, and they are no longer so worried about being accused of being anthropocentric in their descriptions of animals. Many scientific studies demonstrate that animals have a complex knowledge about their environment based on sensory experience, just as we have. The abilities to see, hear, smell, and taste, and the ability to learn about their surroundings  Hume, D. (1739–1740/2007), Sec. 16, pp. 118–119.

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from information delivered by the senses, seem to make other animals comparable to human beings by enabling them to act in keeping with the acquired information. Any alternative view would also be surprising, considering that both are the products of Darwinian evolution according to which human beings like other animals are the results of the same processes of natural selection. Modern genetics has established that Homo sapiens shares between 98 and 99 percent of our genes with the chimpanzees. The capacity of acquisition and retention of information about one’s environment is primarily a feature related to our biological adaptation and survival as it is for other animals. Therefore, we must assume that the preconditions for acquiring sensory knowledge in humans are also found in chimpanzees. Another obstacle has been that much philosophy still follows in the footsteps of Descartes rather than in those of Hume. Solutions to scepticism and commitments to epistemic responsibility are still very much in vogue in epistemology, though a few philosophers nowadays seek to break with this very tradition. The tradition received a new momentum from the Wittgensteinian and the Sellarian idea that possessing a concept is the same as mastering the use of words. Sense impressions have to be grasped in terms of a conceptual framework before they get their status of knowledge or conscious experience. Both Wittgenstein and Wilfrid Sellars believed that all knowledge is part of a social practice of justifying our claims to ourselves and other human beings. As Sellars says: “all awareness of sorts, resemblances, facts, etc., in short all awareness of abstract entities—indeed all awareness even of particulars—is a linguistic affair.”3 Such a transition from sense impressions to knowledge takes us from what he calls an empirical description of mental states to placing them within the space of reasons, which enables us to make such justifications. We shall discuss Sellars’s ideas more closely in Chap. 4. The present work is inspired by the changing attitude in epistemology, which refuses to exclude animals, children, and illiterate or demented people from having genuine knowledge, regardless of the fact that these individuals are not able to give reasons for their true beliefs. Usually  Sellars, W. (1956). Empiricism and the Philosophy of Mind. Harvard University Press, Sec. 29.

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naturalized epistemology is associated with W.V.O. Quine after he published his famous paper “Epistemology Naturalized”.4 Although Quine’s voice has had a greater impact on the discussion than any other naturalist’s before him, one should not forget that he has several forerunners whose views were familiar to him. For instance, John Dewey, George Santayana, and Roy Wood Sellars, the father of Wilfrid. Quine held that Epistemology, or something like it, simply falls into place as a chapter of psychology and hence of natural science. It studies a natural phenomenon, viz., a physical human subject. This human subject is accorded a certain experimentally controlled input—certain patterns of irradiation in assorted frequencies, for instance—and in the fullness of time the subject delivers as output a description of the three-dimensional external world and its history. The relation between the meager input and the torrential output is a relation that we are prompted to study for somewhat the same reasons that always prompted epistemology: namely, in order to see how evidence relates to theory, and in what ways one’s theory of nature transcends any available evidence… But a conspicuous difference between old epistemology and the epistemological enterprise in this new psychological setting is that we can now make free use of empirical psychology.”5

In my opinion, if we really want to understand human knowledge as a natural phenomenon we cannot settle for psychology alone, but our investigation has to include animal cognition as well as human evolution. Knowing something, I shall argue, is at a minimum something we should attribute to an organism when it gets information about its environment right, and this information allows it to interact beneficially with its surroundings. Granting animals the capacity of having knowledge jeopardizes almost any internalist theory of knowledge, which would demand that every being with knowledge knows that he or she possesses knowledge. It does not make much sense to claim that animals must know that they know or that they have epistemic responsibilities. Nor with respect to children. Nevertheless, upholding the internalist criteria  Quine, W.V.O. (1969). Epistemology Naturalized,  Reprinted  in his Ontological Relativity and Other Essays, Columbia University Press, 69–90. 5  Quine, W.V.O. (1969), pp. 82–83. 4

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of knowledge, arguing that non-human animals therefore do not possess knowledge, even if their senses do not malfunction and their brain does work properly, would be wrong, simply because this would presumably exclude early members of Homo family from having knowledge. Only their descendants developed a comprehensive language. The exclusion of creatures from having knowledge, though they behave according to the information they receive by their senses, would be an act of definitional fiat. It stipulates the preposterous definition that knowledge would require that successfully behaving animals, children, and illiterate people be in a particular sophisticated linguistic state of mind, which is not attainable to them; and that therefore these individuals do not possess any knowledge. Indeed, one might object that these individuals possess only sensory information, and this is not the same as knowledge. According to this outlook, knowledge demands mental states, like beliefs, whose propositional content purports to express facts. People gain some beliefs from the sensory information they gather, but beliefs are not information but mental results caused by such information. Only if sensory information produces a belief state are there grounds for talking about knowledge. Single celled animals attracted to light receive information about their surroundings; however, they do not hold any belief. The same is the case for multicellular animals whose automatic behavior is congenital with respect to specific stimuli. So it seems outright wrong to ascribe a specific belief to a bird that is migrating south in the autumn. A belief is a mental state an organism can achieve from sensory information, but which has a propositional content. Another objection to the claim that non-human animals have knowledge is the rejection that they are epistemic agents. Animals have sensory experiences and may remember these experiences; thus, we may classify them as cognitive agents but not as epistemic agents. The latter requires not only that the agent has beliefs—and non-human animals may have sensory experiences without beliefs—but also that the agent can justify these beliefs in relation to certain set of norms. The requirement of justification is in and by itself an epistemic norm, which a belief has to meet in order for it to be a candidate for knowledge.

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Thus, information is arguably not the same as beliefs, but it may bring about beliefs. Many epistemologists would certainly argue that in order for a belief to count as knowledge its content has to be justifiable, and it is only justifiable in case it meets certain norms of justification. This conception of human knowledge may very well characterize highly deliberating beings, like humans, but I shall argue that even with respect to them it applies only to socially formed knowledge such as scientific knowledge. I shall defend three claims: (1) Sensory and behavioral knowledge need not give rise to beliefs; (2) beliefs come with the capacity of conceptualizing particulars; and (3) the capacity of conceptualization is independent of language and therefore evolutionarily predates the development of language. However, the commitment to justificatory norms is very illustrative of the traditional approach to epistemology, namely that we have to characterize all aspects of (propositional) knowledge in terms of intellectual and prescriptive principles. Nevertheless, there is an important difference between regarding knowledge as a natural phenomenon and regarding it a social one. This is also how I read Hilary Kornblith as he maintains, “The goal of a naturalistic theory of knowledge, as I see it, is not to provide an account of our concept of knowledge, but instead to provide an account of a certain natural phenomenon, namely, knowledge itself.”6 As a natural phenomenon, knowledge consists in an organism’s ability to handle sensory impressions in accordance to its memory of similar sense impressions in the past, sensory impressions that it received from the environment to which it is adapted. It has little connection to social norms that first become parts of hominin evolution when our ancestors evolved into becoming linguistic beings. As linguistic beings working with abstractions and idealizations, humans need to add normative constraints to those beliefs that are not directly concerned with our perceptual experiences. The traditional theories of knowledge have always assumed that beliefs should meet the same epistemic norms and standards regardless of their content. But is it obvious that all forms of knowledge have to be treated  Kornblith, H. (1999). In Defense of a Naturalized Theory of Knowledge. In J. Greco and E. Sosa (Eds.), The Blackwell Guide to Epistemology. Blackwell, 158–169, p. 161. 6

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on equal terms? If it makes sense to ascribe experiential knowledge to animals, as I think it does, it is absurd to require that their beliefs must be rationally and personally justified in order for them to be knowledge. On the one hand, animals are not epistemically responsible agents, and therefore it is absurd to require them to be able to justify their beliefs; on the other hand, highly sophisticated scientists are epistemically accountable for their claims to knowledge and therefore they must be able to justify these claims. Rational justification makes sense only in relation to abstract and theoretical knowledge, none of which is merely based on perception. Theoretical knowledge has to keep up to certain epistemic standards for it to be characterized as such. As we shall see, embodied knowledge as well as sensory knowledge are cognitive states which we share with the other animals, but which are not intellectually justified by reason. In addition, higher animals also develop empirical knowledge generalized from experience and observation. On the top of that, humans advance theoretical knowledge, which we expect them to defend if challenged by another person or by the community of which they are a part. My thesis is that empirical knowledge, considered as a social phenomenon, is still a natural phenomenon whose content, because it transcends our sensory experience, we have subjected to certain methodological prescriptions. Naturalistic epistemology, the trunk of naturalized and social epistemology, assumes that these methodological descriptions are abstractions from our practice of communication. We construct epistemic norms and prescriptions for social purposes. We set up such values and standards in order to make each other epistemically accountable. Yet these norms and prescriptions build on the inherited aptitudes of speaking nature has given us. No other possibility makes sense. For instance, we would not have an ethical norm that said it is wrong to lie if we did not have the ability to lie and the ability to speak truthfully. The ability of deception is congenital; it also exists in octopuses, some birds, and higher mammals. It has given those who possess this ability certain adaptive benefits. However, one must be able to know what the actual situation is and to imagine what happens if one cheats and does not cheat respectively. Only an individual who knows the situation can be said to cheat. You must be able to present the surroundings and find out what the consequences are if you do one thing instead of

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another. Thus, this ability is necessary for you to be morally accountable. The same holds true for reflective thinking with respect to epistemic accountability. Since your cognitive mechanisms may deceive you, especially in situations where your beliefs reach beyond your sensory experience, you need an ability to keep your thoughts from going astray and to correct them if it nevertheless happens. Here sensory information alone is not sufficient for correcting false beliefs. Nature has selected such anticipatory and intentional abilities for the benefit of achieving different purposes. In higher animals, knowledge, imagination, desires and intention are functionally interconnected. The adaptation of anticipatory and intentional abilities enhances an individual’s ability to get to a particular goal based on knowledge of its actual and previously experienced situations. In this way, evolution has laid the foundation for a more reflective and social approach to knowledge, where one can deliberately obey epistemic and moral norms, but always in tandem with already adapted rules of cognition. The crucial point in this epistemic evolution occurred when the disposition to imagine a goal arose, because then the adaptive processes no longer fully determine the goals an organism actually seeks. Eventually goals turned out to be natural, constructed, or highly imaginary. It is one thing to think and reason according to predetermined rules; it is quite something else to act in compliance with epistemic norms and prescriptions. However, the function of both adaptive and norm-driven thinking is measured by their cognitive success, which differs with respect to adaptive thinking and norm-­ driven thinking. In the first case, the survival of the creature depends on it, whereas in the second case the fulfilment of the thinker’s contextual purposes determines the social success. As I move on, I continue to maintain that knowledge does not necessarily involve true beliefs. Moreover, even in those cases where knowledge implicates such beliefs, I shall argue that higher animals acquire true beliefs but that these beliefs need not be internally justified by the believer to be knowledge. It is sufficient that we can potentially make such a justification. I conclude that ascribing knowledge to an organism depends on the function that environmental information has for the individual to whom we are willing to ascribe knowledge. This indicates that the general concept “knowledge” at least covers every form of information about the

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environment gathered by learning. I take sensory knowledge to be that part of animal cognition where neuronal mechanisms transform sensorily acquired information into sensations, and thereby behavioral dispositions, while other parts of cognition such as remembrance are the flexible use of this knowledge for concurrent or subsequent behavioral purposes.

Externalist Theories of Knowledge In contrast to the internalist accounts, I have considered so far, externalist theories of knowledge usually point to causal interaction, information, or reliable methods as what may replace the internalist commitment of personal justification and responsibility in the characterization of knowledge. Externalism has no problem with ascribing knowledge to non-human animals, children and intellectually deficient people, but it may not be the best approach to understand how norms might play a role in establishing knowledge that goes far beyond what the naked eye can see. Here I shall side with Alvin Goldman that human knowledge is reliably produced true belief, but also grant Kornblith his claim that reliability should be explained as the adaptation of an animal’s cognitive capacity of being attuned to the environment such that it is informed to have behavioral success.7 Most of the time the brain and the sensory system present the environment to animals in a reliable fashion. What counts as reliable is functionally determined with respect to survival and reproduction of the organism in question. Thus, reproductive success depends on both the environment in which the organism is actually living and the actual fitness of the adapted organism (since it might, in principle, have been adapted to a different environment in which it is actually living.) Because animals may have sensory beliefs, because they have the ability of conceptualizing what is important in their environment, I argue that sensory knowledge is a natural kind. Some animals are not only adapted to acquiring sensory beliefs, they are also adapted to making a fitting  See Goldman, A. (1967). A Causal Theory of Knowing. Journal of Philosophy, 64, 357–372; and Kornblith, H. (2002). Knowledge and its Place in Nature. Clarendon Press, pp. 58–59. 7

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response to the content of these beliefs such that their behavior might become successful. Both the process by which animals acquire their beliefs and the behavioral success caused by the informational content guarantee that these beliefs are in general true. Human and non-human animals alike do not need to be able to justify their beliefs for them to be non-accidentally true. All that is required is that they have sensory dispositions adapted by natural selection to produce beliefs that accurately reflect their environment. It seems reasonable to ask, though, if you are an epistemic naturalist, do you really need a philosophical theory of knowledge in order to understand knowledge. Yes and no. If knowledge is a natural phenomenon, one is able to study knowledge empirically like all other natural phenomena. To this extent, philosophical epistemology does not matter. But a philosophical theory is required to justify a naturalistic understanding of human knowledge. The appropriateness of this answer depends on what we mean by a philosophical theory, which is not self-evident. In my terminology, a theory is not a representation of reality but a semantic vehicle, a vocabulary and a set of linguistic (or mathematically formulated) rules by which you are able to describe a certain domain of reality.8 In addition to the vocabulary and linguistic rules, we need a model reflecting how we believe the vocabulary applies to ideal objects or phenomena representing the real world. This holds regardless of the topic. As long as we treat knowledge as true beliefs that must be justified in all circumstances, it seems evident that we need a model of the knowledge acquisition process and a vocabulary to describe the conditions under which an organism possesses knowledge. However, we do not need a philosophical theory to tell us that we possess knowledge. This is something we already know. We want a philosophical theory, not because it can guard us against global epistemic scepticism, but because it explicates under which circumstances knowledge involves beliefs, justification, and epistemic responsibility, and under which it does not. For a naturalist global scepticism is not a viable option. I am very persistent on this issue. We cannot understand anything, including global  Faye, J. (2014), The Nature of Scientific Thinking. Palgrave Macmillan, pp. 85–113 provides an elaborated rejection of representationalism. 8

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scepticism, unless we grant ourselves and other humans some level of knowledge and understanding. Other animals also have knowledge, but neither theoretical nor practical scepticism is within their horizon. A philosopher of scepticism among them would have passed away long time ago. Scepticism presupposes prior normative commitments that naturalists are not forced to accept such as knowledge as justified true beliefs. This may really sound like a verbal dispute over how to define knowledge, but my point is that whichever we choose has practical consequences. But it also means we must accept fallibilism and be willing, at least in principle, to revise any belief in the light of new recalcitrant evidence. Moreover, we could not understand the alleged challenge of scepticism, if we did not already have knowledge of an external world and knowledge of how our sensory apparatus sometimes fails to present it correctly. In the wake of Agrippa’s challenges in regards to epistemic certainty and Descartes’ methodological scepticism, modern philosophers have struggled with global scepticism and almost forgotten to discuss knowledge in the light of Darwin’s theory of natural selection, the evolution of human language, and the social institutions emerging from this evolution. The theory of Charles Darwin implies that all the features of our cognitive apparatus have been selected because they are beneficial to our survival. (Of course, as a sceptic one may doubt that any scientific theory helps us to say something about the world, but you cannot at the same time  doubt that such theories exist and pretend via their help to say something about the world.) Here I use the word “selected” as an indication that evolution would not build on any trait that is not already adapted to the surroundings, i.e. without this further development of the trait being an additional favour of the individual: for the organism it would be energetic too costly to build on an unfavourable trait.9 If we have had no knowledge of the external world, it would not have helped us to have a belief that we actually know something. If such a belief was mistaken seen from an evolutionary perspective, we would not have become so epistemically successful in comparison to all other animals.  Actually, some biologists argue that contemporary evolutionary theory grants that some traits may be selected simply because they come with other traits that are beneficial, but are not themselves advantageous. It may well be if their retention does not add to the overall consumption of energy. 9

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Similarly, global scepticism cannot get us off the ground as a possible challenge to such Darwinian ideas without accepting the existence of other people who can make themselves understandable by using language to express their knowledge. The more we think about global scepticism, the more it seems irrelevant, self-defeating, and belonging to a stage of human thinking where the doxastic view of knowledge was in vogue and true belief had to be introspectively justified to count as knowledge. This is not where we are today. Hence, we may leave scepticism to the flames. Indeed, both local and narrow scepticism are possible, and even required by naturalism. These forms of scepticism concern particular beliefs or a particular set of beliefs. We may be wrong about what to believe. The evidence we possess may not suffice to establish the truth of a certain belief. In addition, the alleged evidence may be faulty due to an inaccurate method of collection of data or to a collection of irrelevant data. Most philosophers would admit that empirical knowledge is fallible in the sense that new information can overturn a current belief. Knowledge is not the same as certainty. It cannot be, since induction is somehow the inferential basis on which humans and non-human animals generate empirical knowledge. Deduction plays only a minor role in empirical knowledge building. However, naturalists can also be sceptical with regard to a particular kind of belief that some hold may count as knowledge. Human beings assume many things whose existence is not confirmable by experience and observation. Naturalists, especially the evolutionary sort, may exclude knowledge of abstract objects or other metaphysical entities that do not exist in space and time to which we are sensorily adapted by natural selection. Instead, abstract objects are nothing but conceptual constructions, and we have no knowledge of them apart from the understanding they supposedly provide. Global scepticism denies all knowledge, while local scepticism challenges speculative thinking. I take Hume’s scepticism to be a narrow form of scepticism in the sense that he puts certain limitations on human knowledge. His scepticism derives from a naturalistic approach to knowledge. One can claim to have knowledge only of things that exist in nature, and what exists in nature are only those things that we can experience or observe. Some ideas do not correspond to any sense impressions, whereas others have their roots in sense impressions, but parts of them are

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constructions by our imagination. For instance, according to Hume, our ideas of space, time, substance, and causation are in part a result of sense impressions and in part of our imagination. His naturalism excludes that we can have knowledge of something that does not generate sensations and feelings. Thus, as expected of a naturalist, he is sceptic about every belief that “is not founded on fact and observation.” The result of a naturalistic approach is that an investigation into human knowledge as a natural phenomenon involves two steps. The first one is to examine the psychological and cognitive mechanisms that enable human as well as non-human animals to obtain knowledge, i.e. find cases of experiential information and check out how this information functions as knowledge. The second step is to isolate the social (and linguistic) mechanisms that determine the social factors that are important for the production and retention of empirical and theoretical knowledge in humans. Since the culturally determined features of human knowledge such as epistemic values also belong to our nature, together both steps uncover important aspects of a naturalistic epistemology. Naturalism has become increasingly important in philosophy as the view that the world consists of those objects that are studied by science. The issue of a naturalistic epistemology hits on a larger discussion of the issue of the relationship between epistemology and science in general. We find three different attitudes toward this discussion. One position regards science and epistemology as very different disciplines that at best we should keep entirely separated. Another position considers one of those two disciplines as either redundant or reducible to the other. Today, a typical view of this sort is that science has made epistemology irrelevant or that epistemology should be subordinated science. The third position views science and epistemology as different disciplines, but also holds that they can benefit from interacting with each other. Few philosophers would indeed argue that science makes epistemology superfluous, but there seems to be a move toward an increasing openness to involving the results of the sciences in philosophical discussions. The present work embraces the third position: science informs philosophy about the world, including knowledge as a natural phenomenon, but science itself cannot answer all those self-imposed questions about human knowledge,

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including the epistemic status of science itself, which epistemology usually raises, because science lacks the appropriate theoretical resources. Answering such questions is a philosopher’s job.

 nowledge as a Disposition for Acting K and Thinking An evolutionary naturalist faces two preliminary questions concerning knowledge that have to be answered before we assign knowledge to non-­ human animals. (i) What is the biological purpose of sensory knowledge? (ii) How can we characterize knowledge such that it makes sense to ascribe knowledge to non-human animals? Replying to the first question, we should be looking at what benefit human beings gain from having sensory knowledge, a benefit they may share with non-human animals. A plausible answer is that sensory knowledge consists of mental states, which have a causal role to play as parts of an input-output mechanism adapted to secure cognitive and behavioral success. Sensory knowledge helps human beings to think successfully about possible actions in their environment, such that the intended responses are successful, given these sensory and bodily stimuli. Indeed, non-human animals will benefit from having mental states with similar functions. In response to the second question, let us first consider propositional knowledge. I shall compare it to non-propositional knowledge later. Almost no knowledge is occurrent but exists as dispositional states. Exceptions are knowledge we get by sensation, reflection and remembrance. Most of our beliefs about a proposition are dispositional in the sense that they allow an agent having these beliefs to become aware of them whenever the agent is exposed to appropriate external or internal stimulations. We have obtained propositional knowledge through various forms of sensations, most of which is “hidden” in the sense that, at any given moment, we are not aware that we have this knowledge. It constitutes the most of our memory and forms much of our background knowledge. It functions to assist an agent in the recognition of what it senses, and in this agent’s response to its perceptions.

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Apart from assisting in the recognition of the content of our sensations, propositional knowledge is relevant for the fulfilment of a person’s intentions and for a successful satisfaction of the intention in this subject’s behavior. Of course, naturalists have no problem in explaining why almost none of our knowledge is occurrent. If all our knowledge were manifestly present at a given time, then overwhelmed by conflicting instructions to act we would be unable to function at all. Knowledge is relevant to a person only in certain perceptual and behavioral contexts, such that we do not have to be aware of it outside these contexts. So human knowledge, including propositional knowledge, mostly function as dispositions for sensing, acting, and thinking given the appropriate stimuli. There exist dispositional theories of knowledge, but for the most part, they have been developed within the traditional a priori approach to justification, truth, and belief.10 However, the sensations we acquire when we experience something are manifested to us as a mental presentation and often provide us with episodic beliefs concerning sensorily accessible facts. Also remembering and reflecting supply us with episodic beliefs. But, at the same time, we are not aware of all sensorily acquired beliefs that are not manifested to us, because no external or internal stimuli cause these beliefs to appear. All of it disposes us to react and reason in a certain way, although only little of it disposes us to form mental representations. Hence, whether or not knowledge is occurrent depends on which portion of our background knowledge is retrieved as relevant for recognizing what we sense. What automatically determines the selection is how the actual stimuli we acquire through our senses fit the relevant parts of our memory. Together our sensations, active beliefs, and background knowledge organize our cognitive apparatus such that we reason and react successfully with respect to our well-being and survival. Some propositional knowledge concerns beliefs that are relevant for our actual sensory-motoric orientation. Apart from perceptual knowledge, propositional knowledge also consists of empirical and theoretical knowledge; both versions, as we shall see, are forms of knowledge that  See, for instance, Gundersen, L.B. (2003). Dispositional Theories of Knowledge. Ashgate.

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human beings have abstracted from their experiential knowledge. However, sensory knowledge may be separated into propositional and non-propositional knowledge although often existing side by side as two kinds of disposition to present the same object, as when I see a girl as my daughter. So even if one would wish to deny animals propositional knowledge, i.e. having the capacity of forming conceptual representations, non-propositional knowledge certainly disposes animals to form other versions of mental representations in the form of sensory or bodily recognition, and anticipations of the behavior of others. For instance, Layson albatrosses live in huge colonies with millions of individuals, but each one is still able to recognize its mate and its fledgling. Likewise, I know Bob, i.e. I know what he looks like. When I see Bob, I directly recognize his image, but I also immediately see that he has a black eye. Similarly, I know that a hammer can be used to drive a nail into two pieces of wood to join them, but I also recognize a hammer when I see one and know how to use it properly. Propositional knowledge can appear as both episodic and non-episodic beliefs. The same also holds true for non-propositional knowledge that is occurrent, say, whenever I actually see Bob or use a hammer; otherwise, it is non-occurrent. Indeed, non-propositional knowledge consists of dispositions for sensory or bodily presentations of objects or behavior. These different versions of presentations, I shall argue, may cause actions without any beliefs are involved. Thus, the content of our non-propositional knowledge is not mental representations in the form of sentences in the language of thoughts, as Jerry Fodor has suggested with respect to propositional knowledge. Therefore, they do not have the features of propositional attitudes.11 The fact is that propositional knowledge seems to presuppose some form of non-propositional knowledge. The latter is knowledge that provides us with identifying, conceptual, linguistic, and behavioral competences and enables us to form beliefs of the appropriate sort. Therefore, such knowledge cannot be explained in terms of beliefs. Non-propositional knowledge ensures that we will recognize what we experience and will  See Fodor, J.A. (1975). The Language of Thought. New York: Thomas Y. Crowell. See also Fodor, J.A. (1981). Representations. MIT Press. 11

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behave as we do. Much of our experiential knowledge is non-­propositional and little of it can be retrieved from our memory. In contrast, propositional knowledge can be retrieved as beliefs in our conscious thinking. Originally such knowledge is a result of a belief formation process in which sensations are sorted into different categories with the help of the conceptual resources we have earned as a disposition to classify our sensations. Nothing of this characterization of the difference between propositional and non-propositional knowledge prohibits us from ascribing experiential knowledge to animals. Does this mean that we have cleared the road for an evolutionary account of knowledge? I think we have. But before I defend this conclusion, I want to point to a psychological attitude in human beliefs, which does not seem to characterize the beliefs of non-human creatures. That human beliefs come in degrees is commonplace. Most people are more confident of some of their beliefs than of others. Nothing like this differing degrees of confidence seems to characterize animals’ attitude to their own beliefs; assuming, of course, that they are able to form beliefs. Indeed, this does not exclude them for having degree of beliefs. I shall assume that the precondition for having a psychological attitude of confidence is awareness with respect to one’s beliefs. Only to the extent that an individual is consciously able to assess and evaluate its own beliefs, does it seem capable of developing a psychological attitude of confidence toward its own beliefs. And such an individual can make judgement about its own belief, only if it is able to represent consciously its own belief to itself. Whether chimpanzees and bonobos come close to being conscious of their own beliefs is a matter of current debate, but some experiments seem to indicate a gradual modification in the evolution of self-consciousness. Chimpanzees are known for their ability to deceive intentionally or tactically.12 The best explanation, although not the only one, is indeed that they have the capacity of learning to understand the mind of another through observing its behavior. In addition, they also have to be aware of  See de Waal, F. (1992). Intentional Deception in Primates. Evolutionary Anthropology, 1(3), 86–92; and Hare, B., Call, J., & Tomasello, M. (2006). Chimpanzees Deceive a Human Competitor by Hiding. Cognition, 101(3), 495–514. 12

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their own beliefs to perform intentional acts to deceive others by presenting an inaccurate or false impression of knowledge or intention. Later I shall discuss a case in which some monkeys trust the alarm call coming from other members of the troop, except for one individual because this member of the troop often cheats the others. Apparently, they are led to believe that a leopard is present if most members make a particular call, but not to believe that a leopard is present if one particular member makes the call. This seems to indicate that confidence in believing something is a psychological attitude we find among our closest relatives, but in this case that such an attitude of confidence seems to consist of all or nothing rather than allowing degrees. Yet, human beings seem to be the only animals for which there is any evidence that they are capable of having more or less confidence in their own beliefs because they are reflectively aware of their own mental states. The varying degrees of confidence, which human beings may have, not only deals with empirical and theoretical beliefs, but also may concern sensory beliefs. In some cases, our confidence in believing something seems to be determined by the amount of empirical evidence we have for this particular belief. Whenever I hear a woodpecker pecking on a tree in the nearby woods, I may be highly confident in believing that it is great spotted woodpecker because I am well aware that this is the only kind of woodpecker living in my area. Similarly, waiting to meet my wife at a prearranged location and watching the crowd passing by, I may experience a woman in the crowd as my wife until I realize when she comes closer that this was not her. Apparently, I am in a psychological state in which I am prepared to see my wife, and therefore more confident in believing that a distinguishing appearance is my wife, than I would be in case I knew she was still in the shop behind me. In the latter case, I would only see the woman as someone looking very similar to my wife. As background knowledge, both empirical and theoretical beliefs may assist me in increasing the confidence I have in believing or disbelieving in what I see. This brings us to a distinction made by Robert Audi who differentiates between dispositional beliefs and dispositions to believe. He explains it as follows: “The suggested difference between a dispositional belief and a disposition to believe is in part that between accessibility of a proposition

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by a retrieval process that draws on memory and its accessibility only through a belief formation process.”13 For instance, on the one hand, I believe that our present universe started out in a Big Bang. This is one of my dispositional beliefs, since it is not something about which I am normally thinking. I can retrieve this belief if prompted by certain questions. On the other hand, I have a disposition to believe that I hear a woodpecker when I hear in the distance a faint sound like pecking on a tree. This evidence puts me in a state of having a degree of confidence in believing that it was a woodpecker, which I did not have beforehand. It seems reasonable to assume that we originally obtained many of our dispositional beliefs through a belief formation process. Therefore, one might think that during this process we start by forming tentative beliefs in which we are less than fully confident. And could there not also be a similar process going on in the minds of some of our closest relatives? The answer, I think, consists in three steps. First, apes and monkeys probably acquire their beliefs gradually as, say, learning to recognize leopards, and therefore initially believe their experience of leopards with only a low degree but eventually realizing them with a high degree whenever they see or hear one. Second, undoubtedly higher animals automatically measure the degree in which they believe their percepts, beliefs, memories, and decisions all the time as the outcome of the processing of sensory and behavioral information.14 If the degree of belief is high, indeed we may say that the animal feels confident. But, third, feeling confidence seem to be found only in human beings who are conscious about their own belief, because this psychological attitude seems to require a reflective attention toward one’s own mental states. The latter would not exit, I guess, before  Audi, R. (1994). Dispositional beliefs and dispositions to believe. Noûs, 28, 419–434. Reprinted in his Rational Belief: Sructures, Grounds, and Intellectual Virtues. Oxford University Press, 11–24, p. 13. 14  See Smith, J.D., Shields,  W.E., & Washburn, D.A. (2003). The Comparative Psychology of Uncertainty Monitoring and Metacognition. Behavioral and Brain Sciences, 26, 317–339, discussion 340–373; and Smith, J.D., Couchman, J.J., & Beren, M.J. (2012). The Highs and Lows of Theoretical Interpretation in Animal Metacognition Research. Philosophical Transaction of Royal Society, B 367, 1297–1309. A review of various methods and suggestions to come to grips with uncertainty and confidence among animals can be found in Kepecs, A., & Z.F. Main (2012). A Computational Framework for the Study of Confidence in Humans and Animals. Philosophical Transaction of Royal Society, B 367, 1322–1337. 13

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confidence was identifiable by our predecessors as a possible attitude in connection with judgement about empirical and theoretical beliefs. The experiential beliefs we have acquired were obtained for the most part unconsciously, and they form the reliable basis upon which we later can formulate doubts about or confidence in all of our empirical and theoretical beliefs. These experiential beliefs are, as Wittgenstein pointed out, the “hinges” of our cognitive practices. They constitute the foundation for our cognitive practices of reasoning about and justification of all our other beliefs that concern judgements beyond our immediate experience. However, until hominins developed the capacity of being consciously aware of their higher cognitive states, they would not have felt confidence, but would automatically rely on these beliefs in virtue of the evolutionary adaptation of their experiential knowledge. Probably, the capability of being aware of one’s own empirical and theoretical beliefs evolved in interaction with the development of a psychological vocabulary by which our ancestors could identify these mental states. I suggest that it makes little sense to talk about feelings of confidence before human beings were able to develop an attitude toward manifesting beliefs that are more complex. Such feelings first emerged, I hold, as recognizable mental states in humans caused by a successful process of evidential justification. Some cognitive scientists nevertheless ascribe feelings of confidence to higher animals. For analytic purposes, however, there is an evolutionary difference between having different degrees of beliefs and being aware of having these different degrees of beliefs. We may still explain why both human beings and other animals have different degrees of beliefs, which they do not represent or are unable to represent consciously. Finally let me pick up a suggestion made by Darrell Rowbottom. As he says, “to have an active belief or degree of belief in p requires having a mental representation of p. But to have a disposition to believe or to degree of believe in p does not require having a mental representation of p.” 15 He points out that we need not care about the existence of numerous mental representations (as Fodor characterizes them) in our memory if we think  Rowbottom, D.P. (2021). How can Representationalism accommodate Degrees of Belief? A Dispositional Representationalist Proposal. Synthese, 199. 8943–8963, p. 8958. 15

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of non-occurrent beliefs as dispositions to form mental representations in response to appropriate stimuli. Moreover, he states that having a disposition to a degree of belief, given some sensory stimuli, does not require having dispositions to represent more or less supporting evidence. What is at stake here, I think, is not whether beliefs should be characterized ontologically as mental representations or not. This is a question about whether a belief can be a mental representation unless we are consciously aware of it. What is at stake is that, given our cognitive resources, we can only be disposed to form beliefs or degrees of beliefs concerning things of which we become aware because they are happening or we are thinking of them. However, many of our non-occurrent beliefs are of course not disposition to believe; we still attribute people beliefs, even though they are not actually aware of having them. What we can say is that sensory beliefs are always occurrent, whenever we have them, in the sense that they concern sensory stimuli we have learned to grasp conceptually, whenever they occur. Likewise, we may be disposed to believe p to a certain degree when we receive less than an optimal amount of specific sensory and bodily stimuli. In my view, such a disposition to believing p to a certain degree may be obtained unconsciously as the outcome of an automatic weighting mechanism in both human beings and other animals. This function is determined by our background knowledge and takes part in the process of forming what we believe and the degree to which we believe it.16 Such a weighting function, however, may work for images as well as beliefs. So both human and non-human animals seem to have a disposition to believe something to a certain degree or to be aware of an image with a certain degree of vividness. For instance, depending on the degree of a disposition to believe something or imagine something, an animal may, or may not, respond adequately to the appropriate stimuli. A chital deer may get a faint sense of a tiger approaching the herd; it then becomes alert because it has acquired a certain degree of a tiger belief. Subsequently, given this enhancement of its senses, if it receives further stimuli associated with a tiger, it will react with an alarm signal and start running. So  I believe this observation is somehow similar to what Weisberg, J. (2020). Belief in Psyontology. Philosophers’ Imprint, 20(11), 1–27, has in mind when he notices, “So other animals appear to have a way of using and reconciling retrieved information without relying on confidence levels formed based on fluency and quantity. Humans presumably possess the same means …” (p. 20). 16

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the dear become aware of the tiger as soon as it gives a signal and begins to run, but the degree to which it is disposed to obtain this belief depends on its conceptual resources, the mechanisms by which its sensory stimuli is processed, and the strength of the stimulation. Summarizing the discussion thus far, I have attempted to take an initial step in clearing the way for an evolutionary account of human knowledge. Many of the cognitive mechanisms supporting human knowledge are apparently parallel to many of those found in non-human primates, but we will do well to remember that there are also important differences between us and other creatures. Humans (and perhaps some other higher animals) do not depend entirely on their senses to acquire knowledge. As we shall argue, the evolution of human language opened up for hominins new versions of knowledge such as empirical and theoretical knowledge that exceeded the degree of comprehension we can get from having only experiential knowledge; justified, true beliefs we do not share with our fellow creatures. Nevertheless, if we want to understand how these kinds of social knowledge still feed on and are grounded in our experiential knowledge, we need to understand human knowledge as a product of human evolution.

Cognition, Knowledge, and Understanding The conceptual framework and some of the most important distinctions on which my naturalistic discussion of knowledge relies may be summarized as follows: first, I distinguish presentations from representations. Seeing, hearing, tasting, smelling, touching, and feeling provide information about the environment to an organism in the form of a mental presentation of objects and qualities in its surroundings. The brain of an organism is adapted to present the external and internal state of affairs to this creature such that it is immediately aware of what is presented and not of its presentation. Therefore, we cannot compare this presentation with what it is supposed to present. In contrast, intellectual representations are artificial cognitive constructions or mappings of the organism’s environment that cover thoughts, statements, physical pictures, models, and theories. The function of these representations is to serve a specific intention and can

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be compared to what they allegedly represent. However, most philosophers and scientists speak about “mental representations” where I use the term “mental presentation,” which I take to indicate that they have ignored an important distinction. The function of mentality is to present the world to an organism on the basis of the physical inputs it receives from its own body and its environment. The different modalities of mental states are nothing but distinct forms of adapted presentational states. However, physical causes can affect an organism without these inputs giving rise to any presentational state. All our reflexes, and other involuntary responses, are triggered by external or internal causes. For instance, stimulating of the cornea elicits involuntary blinking with both eyes. Heat regulation is another example of an involuntary response. No mental presentation takes place in the brain in such cases. However, the way our nervous system presents the world to us is also not within our control. Experiencing colors is just an innate physical reaction to electromagnetic radiation. Elsewhere, I have argued that any system, biological or otherwise, that interacts with its environment acquires extrinsic properties, which the system would not have had, had it not been for this interaction.17 Visual sensations are exactly examples of the brain acquiring such extrinsic properties during its physical interaction with the organism’s surrounding or with its internal bodily states. Emotional sensations are other examples of the manifestation of extrinsic properties associated with the nervous system. In general, physical signals must move along sensory channels to the brain before their effects transform into a mental presentation. Sensations are not the same as perceptions. A sensation is an adapted qualitative reaction of an organism to the physical simulations of one of its various sense organs, but a perception is the recognition of some sensations in the light of previously acquired knowledge. One could argue that blind sight is a sort of perception without the experience of sensations. In that case, perception would still refer to the processing of some external information in accord with the organism’s earlier learning.

 Faye, J. (2019). How Matter Becomes Conscious. A Naturalistic Theory of the Mind. Palgrave Macmillan. 17

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Another distinction I make is between cognition and knowledge. Like the words “presentation” and “representation”, or other words ending with “tion”, the term “cognition” can denote both a mental activity and the product of that activity. However, usually we think of knowledge as a cognitive product and not a cognitive activity, whereas thinking is a cognitive activity and not a product. For an organism, knowing that something is the case is to be in a presentational state that is reliable because the physiological and psychological activity leading to this presentational state is a reliable process. Knowledge is something an organism can retrieve for the purpose of maximizing its behavior, and the sources of knowledge may be sensation, memory, intuition, inference, or testimony, which I shall describe more fully later in this book. For the present, we can characterize cognition as an activity that differs from knowledge by having a broader scope than both knowledge and thinking together. Cognition covers both those mechanisms that bring about knowledge, like perception and thinking, as well as those that help us to retrieve previously acquired states of knowledge for the benefit of behavior. The study of cognition focuses on more than just knowledge and thinking. A cognitive system also contains desires, imagination, and perhaps volition. A cognitive system is defined as one that produces behavior by encoding information from the surroundings in the form of mental presentations, which that system is able to retrieve and process in order to perform appropriate behavior to achieve the goal that the system desires. However, a cognitive system is not yet an intentional system. Any cognitive system is conative, but its behavior may be programmed entirely by adaptation.18 A cognitive system acts intentionally, if it is able to select between various possible actions the one that seems to be the most efficient, given the system’s ability to imagine a certain goal to behave in a way to reach this particular goal. An intentional system is active and not just reactive. It knows from past experiences the consequences of different actions; therefore, it is able to choose between them.  See, for instance, Callistel, C.R. (1985). Motivation, Intention and Emotion: Goal-directed Behavior from a Cognitive-neuro-ethological Perspective. In M.  Frese & J.  Sabini (Eds.), Goal Directed Behavior: The Concept of Action in Psychology, 48–66, L. Erlbaum Associates, in which he discusses experiments concerning the feeding behavior of digger wasps, showing how programmed their behavior is. 18

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The purpose of bringing cognitive mechanisms into the explanation of human knowledge is because these mechanisms, as a direct product of our genes, determine behavioral abilities, sensations, and conceptualizations. Even if one considers these mechanisms and the variation in behavior and knowledge as expressing the scope of their enactment, one can still understand their function as regulative cognitive schemas whose existence can be explained by natural selection and adaptation. Assuming that cognitive mechanisms operate as cognitive schemas indicates that they not only form behavioral and sensory knowledge but also structure our beliefs in ways such that we can obtain understanding. Cognitive mechanisms work together through multiple interactions between various sorts of neurons that make possible perception, emotion, thinking and behavior. The genes determine the possible activities of the neurons, and thereby the possible variations in knowledge and behavior, whereas the actual information received, depending on its origin, controls how the mechanisms perform in the circumstances. Cognition also includes mechanisms that bring about feelings and emotional states triggered by thoughts or physical events. Feelings and emotions are mental states that present the physiological reactions in our body to these events and thoughts, and they give rise to beliefs in those cases where an organism is able to identify a particular emotion and distinguish it from other emotions—beliefs that are absorbed into our thinking. A third distinction is one between information and knowledge. If an organism responds to a physical signal, we usually say that it carries information about a certain state of affairs by producing a content that mentally presents what the signal conveys. However, a signal is not informative in and by itself. A particular kind of radiation may carry information for one organism but not for another. Information conveyed by, say, an electromagnetic signal, first exists for a particular individual as an informational content the very moment the physical properties of this signal cause an adapted mental reaction in the organism and the reaction results in, say, a sensation. The content of a sensation informs the organism about something in its environment. The specific signals that convey information to particular organisms depend on the fitness of an organism’s sensory and cognitive capacities.

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In contrast, knowledge is a mental property we attribute to an organism. Knowledge is learned in contrast to instinct. Animals acquire knowledge to control the causal process between their sensation and behavior such that this knowledge increases the probability of survival and reproduction. The acquisition of knowledge may happen in case an animal processes the information it received into a mental state, and this processing is carried out by mechanisms that are working, as they were adapted to work. However, an organism first has knowledge when it relies on the informational content of its mental states and therefore reacts when the situation demands it to do so. The function of knowledge is to enable an organism to respond to the mental states obtained through its senses. Indeed, the mechanisms behind this response involve many cognitive feedback processes which neuroscience may eventually discover. However, as we shall argue later, the informational content need not be believed in order to provide an organism with knowledge. The final distinction we need to make is between knowledge and understanding. I regard these terms as referring to distinct cognitive phenomena. Knowledge is traditionally associated with true beliefs, whereas I hold that understanding consists in the organization of beliefs, images and actions. Some philosophers, however, hold that understanding is identical with skills. But this is not how I use this term. Elsewhere I have argued that this view  gets everything upside down.19 Skills are behavioral evidence of practical understanding, which is rooted in two more elementary forms of embodied understanding we may call behavioral and actional. Maturing animals improve their understanding of their surroundings owing to the fact that they constantly acquire both sensory and bodily sensations, which they then organize into a network of images, beliefs and actions. However, it is a bit strange to argue that human understanding of mathematics, religion, philosophy, science, morals and art, just to mention a few obvious fields, consists in the ability to provide justified true arguments or in the ability to speak or write ardently about these topics. In principle, one may understand some of these topics quite well and never engage oneself in expressing this insight. Thus, I hold understanding is a structured body of beliefs, images and actions. What people usually call skills and competences is just an  See Faye, J. (2014), Ch. 2.

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expression of practical understanding. In addition to practical understanding, we may attain empirical or theoretical understanding. Just as we talk about propositional and non-propositional knowledge, the same sort of distinction is available with respect to understanding. Sometimes we exhibit propositional understanding because we are able to describe many aspects of a case or explain to others how things are related. For instance, explaining causal connections in nature is one way to demonstrate to others that we have propositional understanding of the matter. At other times, however, we have causal understanding that does not involve beliefs. This kind of understanding, which we may not be able to express linguistically, is exhibited in those cases when we display a practical skill such as driving a car or playing an instrument. We are so used to thinking of knowledge in terms of beliefs that few philosophers have bothered to address whether this need to be the case.20 As David Lewis expresses his objection: “I allow justified true belief without knowledge, as in the case of your belief that you will lose the lottery. I allow knowledge without justification, in the case of face recognition and chicken sexing. I even allow knowledge without belief, as in the case of the timid student who knows the answer but has no confidence that he has it right, and so does not believe what he knows.”21 Apparently, according to Lewis, a belief is a mental state that a person is aware of having. One may not be conscious of what one knows, but not of what one believes. Hence, in case we follow Lewis, animals, just like the timid student, may have knowledge but no beliefs. This suggestion raises various issues such as whether there can be non-conscious beliefs. I hope to address some of them in due course. However, as we shall see, there are many forms of knowledge: some of which do not involve belief, some are not justified, and finally some are not true. To end this introductory chapter, I should lay out a kind of typological chart of the species of knowledge, which I will cover and explain how these distinctions are the product of evolutionary selection, and thus say  Among those deviationists are Woozley, A.D. (1953). Knowing and Not Knowing. Proceedings of the Aristotelian Society, 53, 151–172; Radford, C. (1966). Knowledge—By Examples. Analysis, 27, 1–11; and Lewis, D. (1996). Elusive Knowledge. Australasian Journal of Philosophy, 74, 549–67. Reprinted in S. Bernecker & F. Dretske (Eds.), Knowledge. Readings in Contemporary Epistemology. Oxford University Press, 2000, 366–384. 21  Lewis, D. (1996), p. 373. 20

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how a naturalistic epistemologist may account for them. Epistemology bristles with distinctions and, of course, it is well to remember that different philosophers will use the same terms very differently, so even though they may talk the same, they may mean very different things. Thus, the first distinction I want to make is between biological forms of knowledge and social forms of knowledge. The biological forms are the ones we share with other animals. They exist because we are adapted to acquire information about our environment to make our behavior relevant and successful. The social forms are those we almost certainly do not share with other animals, because these forms concern beliefs about phenomena we have linguistically defined. Let us first look at the biological forms of knowledge. I distinguish between knowledge acquired by the external senses and knowledge acquired by the internal senses. The former, attained from seeing, hearing, smelling, I call sensory knowledge, and the latter, achieved by the movement of a body, I refer to as embodied knowledge. Sensory knowledge I further divide between image-based knowledge (knowledge of acquaintance) and concept-based knowledge. Here the former is an example of non-­ propositional knowledge attained by even the most primitive animals to a certain extent, whereas the latter is an example of propositional knowledge that appears much later in organic evolution, whenever some animals begin to form beliefs because they are able to conceptualize parts of their environment. However, I claim that an overwhelming proportion of animal knowledge is image-based just as is a great part of human knowledge. Embodied knowledge I divide into behavioral knowledge and actional knowledge. Both are examples of non-propositional knowledge, although actional knowledge requires some level of conceptualization. Sensory and embodied knowledge are two aspects of what I call experiential knowledge, whereas both behavioral and actional knowledge, together with image-based and concept-based knowledge, constitute the four different modes of experiential knowledge. Empirical knowledge, as I use the term, is different from experiential knowledge. While the various modes of experiential knowledge are widespread among animals, empirical knowledge is restricted to a few highly developed birds and mammals, often living in social groups. In fact, I propose that empirical knowledge really

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evolved in its most sophisticated form with our predecessors’ ability to become aware of and to reflect upon their own experiential knowledge. This special cognitive capacity improved enormously with the evolution of verbal language. Since most of our empirical knowledge is linguistically defined, I consider empirical knowledge as a social form of knowledge. Another form is theoretical knowledge. So the final distinction I want to make is between empirical knowledge and theoretical knowledge. Here I assume that experiential knowledge in combination with reflective thinking, and in keeping with the conceptualization provided by the language community, produce what I call empirical knowledge. Empirical knowledge is by any reckoning the largest part of human knowledge, grounded in our sensory and bodily experiences but extended from this cognitive basis by reflective and linguistic considerations. In contrast, theoretical knowledge consists of educated guesses about invisible entities or structures, expressed in an abstract, systematic, and perhaps mathematical form and partly justified by empirical knowledge and partly by the background of the rest of one’s theoretical knowledge. Indeed, the various versions of human knowledge just mentioned do not work in isolation as separate cognitive units. During the course of human evolution, the capacity for achieving advanced versions of knowledge developed based on the capacity for attaining lesser-advanced versions of knowledge. Thus, the function of more advanced versions depends both phylogenetically and ontogenetically on the function of more primitive ones. New versions of knowledge evolved by incorporating already existing versions. As we shall see, evolution therefore explains why epistemic commitments have a social origin, and why the need for them is first required whenever people begin to articulate either empirical or theoretical beliefs. Experiential knowledge, in contrast, has a biological origin and has little or no need for such epistemic commitments because adaptation has shaped the fitness of the sensorial and belief-forming mechanisms.

2 Knowledge as a Natural Phenomenon

When we take the naturalist turn in epistemology, we realize at once that human beings are not the only animals that possess knowledge. Non-­ human animals seem to acquire something we may call knowledge ranging from accumulating sensory information to highly complex beliefs. Numerous scientific publications on animal cognition describe how all sorts of animals behave selectively and intentionally by using information gathered by their senses. Through their sense organs both birds and mammals gain information about their territory, their hiding or nesting place, objects of food, mating partner, conspecifics, and possible predators that might hunt them down. These animals not only learn to recognize in detail particular sites that are important to them, but many are able to sort out various kinds of animals and know how these would behave and react under various circumstances. Nevertheless, much academic epistemology still ignores these facts as if Darwin had not existed and comparative, behavioral science, and cognitive ethology were not parts of established science.

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. Faye, The Biological and Social Dimensions of Human Knowledge, https://doi.org/10.1007/978-3-031-39137-8_2

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In the current chapter, I argue that humans and other animals are alike in having experiential knowledge of our environment. I do not mean to suggest that animals are consciously aware of their own sensory states. There is little evidence to show that non-human animals in general are able to reflect on their own mental states. Awareness of one’s own mental states is a capacity that presumably progressed rather recently in the history of biological evolution, whereas sensory awareness of the environment is a capacity that has existed for a very long time. Amphibians, fish and insects have minds, but they are not conscious that they have one.1 Their senses help them to present the world around them such that they are aware of their environments. In contrast to secondary consciousness, primary consciousness corresponds to this form of awareness.2 It can be associated with the brain’s ability to present the surroundings to the organism, i.e. having primary consciousness puts animals in a state where, in the secondary sense of consciousness, they are not consciously aware of having these experiences. Mentality is the brain’s sensory and bodily construction of the environment based on sensory stimulations, and such a construction even functions as the cause of dispositional reactions like instinctive behavior. Sensory and bodily impressions present the world to an animal and thereby convey information. Each particular organism is adapted to be sensitive to the sort of content that this sensory information contains. Although sense impressions in non-human animals may not imply the existence of true beliefs, there may still be a convincing argument, as we shall see, to regard this kind of mental presentation as a form of knowledge. Moreover, I hold that our knowledge about external affairs comes in two modes we may call acquaintance knowledge and doxastic knowledge. I suggest that the acquaintance knowledge is the most primitive form of sensory knowledge since it does not operate in virtue of concepts but in virtue of images. Correspondingly, we and other animals comply with  Refusing to consider animals as mere stimuli-response machines, Donald Griffin provides in his The Question of Animal Awareness. Evolutionary Continuity of Mental Experience. The Rockefeller University Press (1976) an early defense of the gradual evolution of the mind. He also argues that evolution is just as important for understanding the capacity of human cognition as our use of language. See also his Griffin, D.R. (1998). From Cognition to Consciousness. Animal cognition, 1, 3–16. 2  The distinction between primary and secondary consciousness is equivalent to one between creature and state consciousness. 1

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two modes of thinking. One that consists of mental manipulation with images and the other with concepts. In my opinion, both sensory images and sensory concepts are exemplars of thoughts that represent some state of affairs in virtue of carrying a content. What distinguishes them is that sensory images are mental presentations of particulars, whereas sensory concepts are a classificatory comprehension of ones’ sense impressions of these particulars. Indeed, human beings may form beliefs about their images and have doxastic knowledge of their content.

Knowledge in Non-human Animals As new generations of biologists, ethologists, and cognitive scientists learn more about non-human animals their reluctance to ascribe mentality, intentionality, knowledge, and thinking to these living beings has dwindled. For all scientific purposes, the use of such allegedly anthropocentric concepts in describing our fellow creatures makes sense given the huge amount of controlled experiments and field observations in recent years. Using only behavioristic or instinctive terms seems both artificial and simplistic and does not describe the way scientists nowadays understand the complexity of animal behavior. Here is what one eminent scientist, John Marzluff, says about crows: “Its brain allows the bird to learn quickly, to accurately associate rewards and dangers with environmental cues, and to then combine what it knows with what it senses and to draw conclusions leading to a more informed response.”3 Life-long observation of corvids puts Marzluff in a position to say what he does. Another distinguished biologist, Frans de Waal, who has worked with primates for decades, emphasizes, “… each organism is driven to learn those things that it needs to know in order to survive.”4 Further, in the same work de Waal points out that “Clark’s nutcrackers remember where they stored thousands of nuts, beewolves make an orientation flight before leaving their burrow, and chimpanzees nonchalantly learn the affordances of play  Marzluff, J., & Angell, T. (2012). The Gifts of the Crows. How Perception, Emotion, and Thought Allow Smart Birds to Behave like Humans. Free Press, p. 4. 4  de Waal, F. (2016). Are We Smart enough to Know How Smart Animals are? Granta Books, p. 58. 3

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objects. Without reward or punishment animals accumulate knowledge that will come in handy in the future, from finding nuts in the spring, to returning to one’s burrow, to reaching a banana.”5 Each one of these species is adapted to collect a particular kind of information that increases its chances of overcoming future environmental challenges. Examples are legion—so it seems. A rat running a maze learns to navigate, knowing where to avoid dead ends; a pigeon can be trained to know the difference between photos of human beings and of non-human beings, and an octopus can learn to unscrew the lid of a jaw from within. In the wild, birds and mammals know the specific features of their territory, which allows them to move around safely; they know where their nest is situated and where the hiding places are. They also learn, which kind of food they can eat, and which not—in particular, by watching what their parents eat—and they know the kind of animals that may prey on them and which to ignore. Through observations and accumulated experiences, they learn to know the behavior of their foes and friends. The ability of mature animals to identify other kinds of animals and to behave the most optimal way in what are for them recognizable circumstances is not an innate capacity. These aptitudes are something they eventually picked up, as they grew older, in the same way that humans learn to separate different kinds and behave accordingly based upon their own observations and instructions of their parents. The simplest model of learning is to consider animals’ behavior to obey a stimulus-response mechanism. In such a model, there is room for some form of knowledge. Indeed, some stimulus-response mechanisms are innate, but others are learned, at least in higher animals as when a dog learns to obey a command. In addition to environmental stimulations, the model operates with a simple reinforcement process in virtue of rewards and punishments, where these two components together causally determine the animals’ reaction. But, as Hilary Kornblith already pointed out years ago, “evidence for the existence of beliefs in the animal world is extremely widespread, and such attribution is common in the animal  de Waal, F. (2016), p. 69.

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behavior literature. More than this, what one sees in the animal behavior literature, and with a great deal of frequency, is talk about animal knowledge.”6 As soon as we introduce beliefs as a cognitive element that transforms environmental stimuli into behavior, the learning model becomes more complex, but it also opens up for a larger behavioral ­flexibility depending on many more internal and external factors. The model becomes more complex because it postulates more various mental steps between the physical input and the physical output. However, these mental steps may permit one to ascribe desire, memory, intention, and planning to an animal. The choice of which one of these models gives us the best explanation is always partially a question of parsimony and adequacy, but also partially a question of which model is able to explain evolutionary continuity and transition from the simplest to the most complex animals like humans. In the end, it is a scientific challenge to understand where the data take us. An experimental and observational approach to animal cognition does not imply that there is consensus among evolutionary psychologists and biologists about the extent to which the cognitive capacity of the most intelligent non-human animals is similar to humans. Some researchers work constructively and build up their interpretation on common functional and neuronal features. They argue that creatures like chimpanzees share most of their cognitive abilities with humans because the basic mechanisms of cognition are common across a wide range of species.7 Others reason from a more principled stance, holding that no animals other than humans are able to share intentions and therefore have social knowledge. Humans are unique in their capacity of collaboration and in acquiring new knowledge. As humans eventually appeared, the evolution of language moved them from having only individual knowledge to

 Kornblit, H. (2002). Knowledge and its Place in Nature. Clarendon Press, p. 53.  See de Waal, F., & Ferrari, P. (2010). Toward a Bottom-up Perspective on Animal and Human Cognition. Trends in Cognitive Science, 14, 201–207. 6 7

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having social knowledge.8 A difference between the bottom-up perspective and the top-down perspective is their respective focus on behavioral and neuronal communality across various species and emphasis on each individual species and its uniqueness. Nonetheless, there is more to the disagreement between the top-down and bottom-up perspectives than mere methodology. It is also a dispute over semantics. How should we understand central descriptive terms like mind, consciousness, intelligence, and behavior? Consider a term like “imitation”. The classical and operational definition of imitation is something like “doing an act from seeing [or hearing] it be done”.9 This sense allowed the field workers to attribute social learning to wild primates as they actually observe a performance of copying played out among apes and monkeys in their natural habitats. For instance, young macaques on the Japanese islet Koshima learn to wash sweet potatoes in water after a female monkey more than half a century ago was the first to begin to do  Tomasello, M. (2014). A Natural History of Human Thinking. Harvard University Press. Regardless of the fact that bonobos and chimpanzees do not manage to speak a language, they seem to have advanced social skills that require some form of communication. In contrast to monkeys, apes do not depend much on calls and cries; nevertheless, they are able to communicate their intentions by subtle gestures. Hobaiter, C., & Byrne, R.W. (2014). The Meanings of Chimpanzee Gestures. Current Biology, 24(14), 1596–1600, report their findings of the use of gestures among chimpanzees. They discovered the use of 66 different none-playful gestures to communicate 19 different meanings. The meanings of the various gestures were the same across individual signalers. Moreover, the flexible use of several gestures for the same goal was higher during social negotiation. Other recent studies also show that apes and monkeys can learn to express their intentions such that other individuals understand these intensions. In a later paper, Bonobo and Chimpanzee Gestures Overlap Extensively in Meaning. PLoS Biology, 2018, https://doi.org/10.1371/journal. pbio.2004825, Graham, K. et  al conclude their investigation that “Bonobos and chimpanzees share not only the physical form of the gestures but also many gesture meanings.” The method used to find the meaning of the physical gestures is a signaler-response analysis. As they point out, “Bonobos and chimpanzees are closely related members of the great ape family, and both species use gestures to communicate. We are able to deduce the meaning of great ape gestures by looking at the ‘Apparently Satisfactory Outcome’ (ASO), which reflects how the recipient of the gesture reacts and whether their reaction satisfies the signaller; satisfaction is shown by the signaller ceasing to produce more gestures. Here, we use ASOs to define the meaning of bonobo gestures, most of which are used to start or stop social interactions such as grooming, travelling, or sex. We then compare the meanings of bonobo gestures with those of chimpanzees and find that many of the gestures share the same meanings.” That bonobos and chimpanzees share most of their sign vocabulary shows that at least forms and their communicative functions are inborn and generically evolved before their lineage splits into two. However, this heritage does not exclude that each individual ape has to learn the meaning of each particular gesture. 9  See de Waal & Ferrari, P. (2010). 8

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so. Subsequently its offspring learned the same technique, and in the years that followed, the entire troop came to adopt it. From such observations, it seems reasonable to conclude that non-human primates and humans share the same ability of replaying others’ behavior and learn from such an action. That young songbirds apparently learn to sing by imitating the song of older males is also well documented. However, some cognitive ethologists see it in a different light, perhaps influenced by traditional epistemology, maintaining the uniqueness of humans is due to our rationality and intentional use of language. Their demand is that talking about imitation makes sense if, and only if, an individual understands the intentional structure of another’s action; i.e., recognizes the envisioned goal and the reasoning and the implementation leading up to the goal.10 In this way, attributing imitation to an individual is not solely an assertion about overt behavior, but one alleged to show insight into the thinking of another individual. These scientists simply move the goal posts. Hence, with respect to the definition in terms of overt behavior, songbirds and non-human primates exhibit imitation, but with respect to a definition in terms of a concealed insight into the goal of another’s mind, they may fail to imitate. Certainly, we have direct access only into our own mind. In addition, we also believe that other humans are like ourselves, not because, I think, we analogously infer that they are conscious just like ourselves, but because we are adapted to learn as children about our own mind from recognizing theirs. I tend to say that we learn how to identify our thoughts and feelings based on our interactions with others, but the content of those thoughts and feelings is only directly presented to me. In a nutshell, we learn about our own mind from the experience of our intercourse with our parents, siblings, and other human beings. The discovery of mirror neurons may help us to understand why this can happen. If this is true, there are good reasons to expect that animals other than humans may have a sense of other subjects’ intentions prior to any capacity of learning about their own intentions. Being introspectively aware of one’s own intentions requires that the brain is able to make conscious one’s own mental state to oneself, which involves the cognitive mechanisms of 10

 Tomasello, M. (2014).

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secondary consciousness, but being aware of other’s intention requires only that one has the ability to form a concept of intentionality. The latter includes merely the cognitive mechanisms of primary consciousness. Analogously, an animal does not need to know that it knows, before it knows what it does not know that it knows. It may have perceptual knowledge without knowing it, and it may even have social knowledge without knowing it. Only humans may be able to know that they have beliefs, and it may therefore make sense under certain circumstances to require that the truth of such beliefs must be rationally justified before those humans can maintain to know whether these beliefs are true or not. Moreover, people often find that they may actually know something they are not able to recall or to justify at a given moment; they first remember it when they are being told (Yes, I knew it!), or they may first recall it through hypnosis. Or you can give the right answer in Trivial Pursuit, because that’s what first comes to the mind, but you didn’t know if you actually knew it, or it was just an impulse or a false memory. Therefore, the inability of a subject to recollect what it knows is not a reason to deny knowledge to this subject. Of course, animals are in principle unable to justify the content of their mental states, partly because they do not know that they possess such mental states, but more importantly, because they are cognitively unable to engage themselves in justificatory reasoning that relies heavily on evidence and truth. Thus, if animals have knowledge, it must be because of the process by which sensory information becomes acquired, stored, and treated that legitimizes attributing knowledge to them. And, of course, if such a process, given the animals’ cognitive circumstances, is good enough for them to behave appropriately with respect to the environment, it will be good enough for humans in similar cognitive circumstances.

Cognitive Schemas and Animal Knowledge A foundational premise of empiricism is its denial of the existence of innate beliefs. Everything we know comes from the senses, and before we are born, our mind is a tabula rasa. Are naturalists bound to follow suit? In many ways, epistemic naturalists are a sort of empiricists because they maintain that knowledge, like any other natural phenomenon, should be the object of empirical investigations and not a priori studies. However,

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in contrast to empiricists, epistemic naturalists will accept that we are born with cognitive schemas, which are adapted to the physical environment, and which determine how our brain organizes and presents environmental stimuli. Far from being a blank slate at birth, the mind is a slate highly shaped by natural selection. I view cognitive schemas as cognitive-neurological patterns that organize behavior, thinking, and understanding. Cognitive schemas are of many sorts but, in general, they are adaptations of the nervous system that enable it to respond uniformly to environmental stimulations for the benefit of survival.11 They bring different experiences into a coherent whole, function as a blueprint for concept formation, form a system of knowledge, serve as vehicles of inference, and coordinate sensory information, thinking, and behavior. The processing of sensory information into thoughts takes place according to these schemas depending of their purpose of use. In order for physical input to be beneficial to an organism, the received information has to be processed in a systematic and regular manner. The schemas are nature’s way of guaranteeing that the processing is carried out such that similar stimulations cause similar experiences, and that similar behavior is performed based on these experiences. Although many cognitive schemas are innate, learning may also provide an animal with some cognitive schemas in the form of manifested customs and social habits. For example, when an animal learns to coordinate its hunting strategy with conspecifics, it acquires a functional schema for how it should behave in similar circumstances.  See Faye, J. (2014). The Nature of Scientific Thinking. Palgrave Macmillan, pp. 56 ff. Well known is Kant’s use of schemata in his philosophy to overcome the problems of applying a priori categories on a posteriori sensations. Jean Piaget seems to be the first to use the term schemas or schemata in cognitive psychology. Later Frederic Bartlett developed his schema theory in his book Remembering. A Study in Experimental and Social Psychology, Cambridge University Press, 1932. He defined a schema as “an active organization of past reactions, or of past experience, which must always be supposed to be operating in any well-adapted organic response” (p. 201). This book has been the inspiration of much later works on schemas. However, where Bartlett mainly associated schemas with the capacity of remembering, I am more in line with recent authors, such as Michael A. Arbib, who see schemas as cognitive mechanisms of the brain that establish its capacity of organizing all kinds of sensory presentations, behavioral activities, and cognitive responses. See Arbib, M.A. (2005). Modules, Brains, and Schemas. In H.-J.  Kreowski et  al. (Eds.), Formal Methods and System Modeling. Springer, 153–166, for both a brief historical survey of the development of schemas and an exposition of various levels of schemas in relation to the brain. 11

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Before knowledge can be empirically studied, we must know what to look for. It is not enough to say that naturalists think that knowledge is a fundamental explanatory category that also successfully applies to the account of animal behavior. Indeed, naturalists will claim that explanations in terms of knowledge in many cases yield the best explanation, namely in those situations in which animals seem to purposely act in accordance with earlier experiences. Likewise, according to the naturalist, we must be able to recognize cases where knowledge functions as the most viable explanatory category from cases where other categories are more likely to hold grounds. We need a workable notion of knowledge on which the empirical sciences can rely in their investigations. According to traditional philosophy, knowledge is equivalent to true justified beliefs. But turning our attention toward beliefs does not solve the explanatory problem. What are beliefs, and how do we distinguish them from mere information? Here is how Kornblith, an ardent advocate of epistemic naturalism, characterizes the landscape: Informational content by itself, however, falls short of true mental representation. Thermostats have internal states that register information about their environment; they do not, however, have mental states. And even allowing for the existence of mental states with informational content does not, by itself, give us belief. … So even though we must allow that animals have internal states that are bearer of information, still more needs to be said in order to make out the case for animal belief.12

In other words, Kornblith holds that the existence of informational content is necessary but insufficient for belief-attribution. What is also required is that the informational content exists in the form of a mental presentation. However, even those two conditions may not be sufficient. Kornblith rightly points out that the environment places certain informational demands on animals if these should fulfill their needs and desires. They must be able to collect information about food, mating partners, competing conspecifics and predators together with information about the features of the landscape they inhabit. This requires, he  Kornblith, H. (2002), pp. 36–37.

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says, that the animal can process this information into a mental presentation, although it is always an open empirical question which of the many features of the environment that must be included in such a presentation.13 Kornblith also acknowledges that plants have needs, but he argues that we can give a lower-level explanation of such needs that does not refer to a mental representation. Sunlight is necessary for the photosynthesis, which explains most of the behavior of plants. The plants need not process information into a mental representation about sunlight in order for them to respond to it. It is a completely different matter as we target animal cognition. Apart from certain terminological issues, I agree with Kornblith’s overall analysis except for his requirement that the mental presentation necessarily involves beliefs or has to be true. I prefer to call what have traditionally been called “mental representations” instead “mental presentations” to distinguish them from artificial representations where we intentionally stipulate the representational elements and relations, and therefore can compare the representans with the representandum. However, Kornblith does not tell us how we should understand a mental state or a mental presentation. First, for my part, I take mental presentations to be extrinsic properties of the brain, which it acquires through causal interactions between its neurons and their environment.14 Hence, a mental state is an extrinsic state of the brain characterized in terms of those properties it acquires through interaction with the rest of the body or the entire environment. Second, I say that a sensory presentation, or representation if you prefer, is the causal outcome of the brain’s processing of incoming signals from the world. The information processing in the brain results in a qualitative mental state, which we call a sensory image, and this state is an extrinsic property of the brain adapted to inform the animal about its environment and to function as a source of fitting responses to the environment. These are the steps in the process: incoming signals carry input information, which the nervous  Kornblith, H. (2002), p. 37.  Faye, J. (2019), How Matter Becomes Conscious. Palgrave Macmillan, Ch. 8. The environment of a single neuron includes all other nerve cells, the environment of a network of neurons includes the entire nervous system, and the environment of the nervous system includes the body and the external world. 13 14

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system processes in various ways resulting in a sensory image, and the content that comes out of the processing mechanisms provides an animal with a sensory presentation of the source of the signals. Indeed, the “source” that the organism identifies is only relative to its survival interests. In traditional epistemology, a sensory presentation would be equivalent to one or a number of sensations or sense impressions. Moreover, depending on the kind of organism it is adapted to serve, the brain may, I suggest, support cognitive mechanisms that transform a sensory presentation into a conceptual comprehension of this very presentation. Therefore, we shall define a perceptual experience as a sensory image, or a composition of sensations or sense impressions, whose informational content provides the animal with a sensory belief in case it has a conceptual comprehension of the informational content of this sensory image. However, it is well known that non-sensory categories, like social or theoretical ideas, often participate in our perceptual experience as well, which means that sensations do not merely provide us with sensory beliefs but often with non-sensory beliefs. Finally, at least in humans, our nervous system can present our thoughts and thinking so that we become aware of these mental processes. Thus, animals have a perceptual experience whenever they acquire a sensory belief about a conceptual comprehension of the content of their external and internal sense impressions. The sense organs and some mechanisms of brain help an animal to form sensory presentations by collecting, transducing, and processing input information from either its body or its environment; and additional mechanisms help it to learn to comprehend conceptually the content of these presentations. The mind itself does not present anything; the mind is the presentation. The brain and the incoming information do all the work in the sense that the sensory or conceptual content resulting from this interaction constitutes the mental states such that mental states occur from this interaction as extrinsic properties of the brain states. 15 Both sensory images and the conceptual comprehension of  In Faye, J. (2019), Ch. 8, I develop this externalist view. The view is that mental states are extrinsic properties of brain states caused by some neurons interacting with other neurons. Thus, I consider the mind to be sum of all these mental states. If you do not have this ontological view in mind, it may sound as if I argue for epiphenomenalism. Part of the view is also that extrinsic properties of a smaller, more confined system (a group of interacting neurons) function as intrinsic properties in our description of a larger system (the entire brain) that includes the smaller system, say a particular group of neurons, and its environment (other neurons). 15

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their content are mental states, and this allows at least humans to learn that their sensory presentations and conceptual comprehension are distinct from what these mental states reveal. A thermostat works without having to transform the input information into a sensory presentation. Therefore, it functions based on a different set of extrinsic features caused by the incoming signal. Similarly, animals also have the opportunity to just act directly on physical information—without ­transformation into a sensory presentation—when they respond “instinctively, without reaching the senses.” In addition, animals are also capable of processing input information in order for their nervous system to turn the incoming signals into a sensory presentation and/or a conceptual comprehension. But, apparently, it is humans who have the ability to realize that their sensory presentation may be an illusion or their conceptual grasp inadequate. However, a separate question is whether a belief is identical to a sensory presentation. The answer seems to be in the negative, because this would demand that you could have a belief about something of which you have no previous information. If you for the first time sense something, and if you have never been informed about it (or something similar to it), it is difficult to see how you can form a belief about what it is you sense. You must be familiar with similarities of what you sense, before you can form any belief with respect to what you sense. Acquiring a particular belief concerning the subject of your sensory presentation requires that a learning process has installed in your brain a conceptual schema that enables you, unconsciously, to recognize that your actual experience is of the same sort as earlier corresponding experiences. Such a conceptual schema also allows you to understand that the actual experience is different from any earlier experiences.

Beliefs, Desires, and Recognition A naturalist like Kornblith holds that the belief-attribution comes with the need of a belief-desire psychology.16 The attribution of beliefs and desires prove their pragmatic value in their role in successfully explaining 16

 Kornblith, H. (2002), p. 38 ff.

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and predicting human as well as non-human animal behavior. Such a psychology enables us to come up with a single explanation for a heterogeneous collection of different behaviors just as various desires can explain the same homogenous behavior on repeated occasions. The demand for a belief-desire psychology is methodologically motivated. Mental states, according to Kornblith, supervene on brain states. So a reference to the underlying brain states of particular beliefs and desires may be to very distinct states, whereas a reference to the supervening mental states points to the common cause behind an animal’s distinct kinds of behavior. Hence, an explanation that involves a theory of beliefs and desires helps us to understand how different animals behaving in a wide range of ways may be driven by the same beliefs and desires. Beliefs are identified by their content. Today cognitive ethologists have no problem in ascribing beliefs with a specific content to higher animals like ravens or chimpanzees. Their motivation is very likely the same as the one that Kornblith states: “The elaborated behavior of ravens to distracting a hawk so as to steal her egg is not a simple response triggered by some environmental condition. While the behavior is straightforwardly explained by appealing to beliefs and desires, no one has ever offered an explanation of such complex behaviors in terms that obviate the need for representational states.”17 But what if we refer to the behavior of rotifers or nematodes? Likewise, they do not respond automatically to environmental conditions. As Evan Ardiel and Catharine Rankin emphasize in their review of all the research on the cognitive capacities of Caenorhabditis elegans: “Even this relatively small organism shows a large number of degrees of freedom in adapting its behavior to reflect its experience.”18 This is exactly what Kornblith maintains with respect to more intelligent animals. They learn to adapt their behavior to the situation they are sensing. Therefore, in order to be consistent, we should also attribute beliefs and desires to more primitive organisms. They have sensations and are able to compare the mental content of these sensations with that of earlier ones in which they remember such relevant environmental stimuli as  Kornblith, H. (2002), p. 42.  Ardiel, E.L., & Rankin, C.H. (2010). An Elegant Mind: Learning and Memory in Caenorhabditis Elegans. Learning and Memory, 17, 191–201, p. 191. 17 18

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smells, tastes, temperatures, and oxygen levels. And they have learned to adjust their behavior according to favorable and unfavorable stimuli. Perhaps it is possible to come up with a better explanation. If the observations of rotifers and nematodes lead anybody to hypothesize that their behavior is motivated by specific epistemic states such as holding beliefs, I suggest an alternative hypothesis that these primitive organisms are able to learn about their environment in ways that avoid the introduction of beliefs as the best way to explain their behavior. Indeed, sense impressions may give rise to a sensory belief, but if an organism is not adapted to take different attitudes toward the informational content of its sense impression, my suggestion is that it is not able to form beliefs either. Thus, I shall say that holding a belief, or for that matter a desire, is to have a certain psychological attitude toward one’s thoughts. Before organisms evolved the adaptation of being in such mental states they may have knowledge but no beliefs. However, Kornblith’s account is not completely satisfactory even with respect to higher animals. There must be more evidential support for a naturalistic narrative than explanatory coherency and simplicity. He argues that knowledge is a natural kind; thus, beliefs also must be a natural kind. He embraces Richard Boyd’s characterization of natural kinds as “homeostatically clustered properties, properties that are mutually supporting and reinforcing in the face of external changes.”19 Thus, it cannot be for pragmatic reasons alone that we may attribute beliefs to higher animals. I maintain that we ascribe beliefs to them because we think they are in some mental states with a certain kind of intentional content, which they have acquired by learning from recurring sensory experiences. Thus, I hold that we use ‘belief ’ to refer to some specific mental state individuated by its type of intentional content. However, we have to supplement this causal theory of reference with some empirically accessible criteria, since we are not directly aware of the intentional content of beliefs other than our own. And sometimes we may not even be able to recognize our own beliefs in cases of being socialized into believing something we have not made conscious to ourselves (unconscious bias.)

19

 Kornblith, H. (2002), p. 61.

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Elsewhere, I have argued that the causal relation between the use of a name for a natural kind and the bearer of that name is determined by some criteria by which we identify the bearer. These epistemically accessible criteria constitute the bearer’s sortal properties. Hence, a natural kind can be characterized in such a way that it is part of the meaning of a natural kind that its sortal properties, which are causally connected to their referent, are good evidence for making certain that the selected name applies correctly.20 A sortal property assists us in establishing the original causal correlation between the name and its bearer. So if beliefs are considered as a natural kind, the term ‘belief ’ refers to some mental state with a particular kind of informational content, and in order to secure this reference we must be able to point to some criteria for applying the term ‘belief ’ in the form of recognizable sortal properties. I would say that these criteria are the various behaviors that scientists observe when they argue that animals are able to identify their sensations as of a certain sort.21 Let us assume that a belief, say, “x is F”, has something to do with information from stimuli processed previously stored in the memory. In addition, let us distinguish sensory beliefs from non-sensory beliefs. Sensory beliefs are episodic mental states, caused by sensory impressions, whereas non-sensory beliefs are quasi-permanent mental states, not directly caused by sensations. Remembering a sensory belief makes it a non-­ sensory belief. Walking down the street, I see cars, bicycles, houses, people, shops, windows, trees, etc. Indeed, I would not be able to identify all these things if I did not already have information about the criteria for being a car, a bicycle, a house, etc. A sensory belief that this object is a house or a person cannot arise without the presence of background information that makes me conceptually identify the object as a house or a person. Sensory beliefs disappear as quickly as they arise. However, some of them we may recall later as non-sensory beliefs in case we have paid these sensory beliefs a special attention and stored them as beliefs about what we sensed in our short-term or long-term memory. Along with our  Faye, J. (2002). Rethinking Science. A Philosophical Introduction to the Unity of Science. Ashgate/ Routledge, pp. 72 ff. 21  Likewise, sensation is a natural kind and subject to a similar semantics. 20

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classificatory capability, such non-sensory beliefs may causally influence the way we apprehend our current sensations. In case non-sensory beliefs have such an influence and add something to the way we grasp our actual sensations, we may call the beliefs we obtain from these sensations experiential rather than sensory. So having sensory beliefs presupposes an ability of the organism to form concepts, not necessarily an ability to reason based on non-sensory beliefs. However, if sensory beliefs do not automatically couple to instinctive behavior, the explanation must be that non-sensory beliefs together with sensory beliefs may guide the organism’s behavior. The propositional content of some mental states seems to be part and parcel of the usual notion of belief. Normally, we think of a belief as a mental state whose conceptual content is expressible in terms of the sentence “x is F”. In virtue of our introspective experiences, we can often be aware of this content. But for a naturalist, it makes sense to ascribe the ability to form concepts and beliefs to an animal without also needing to ascribe to it the ability to speak a language. Earlier, I have set apart first-­ order propositional attitudes and second-order propositional attitudes while associating them with first-order presentations and second-order presentations.22 A first-order presentation is one that gives rise to a first-order belief of what is presented, and therefore an animal who has such a belief harbors an attitude toward the content of that belief. However, a second-­ order presentation is one concerned with our awareness of our inner life and is possible due to an animals’ capacity of self-awareness or self-­ reflection. In Chap. 6, I shall argue that this capacity of self-awareness is the cognitive precondition for the evolution of language.

Acquaintance as Image-based Knowledge Knowledge need not necessarily involve beliefs or even true beliefs. When viewed naturalistically, knowledge in its evolutionarily most basic form is no more than sensory information in which a cognitive system learns about some aspect of its environment. An animal acquires this mode of 22

 Faye, J. (2019), Ch. 8.

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knowledge as a reaction to the continuous reinforcement of similar stimuli and responses. This reinforcement makes an organism acquainted with the content of its sensations. For instance, whenever we experience a particular object as an individual thing, the information of it is stored in us as a mental image. In other word, whenever we become acquainted with something, we develop an ability to remember it, because the specific sensations we have of it are stored (over time) as information of a sensory image in our memory. Then this information can be retrieved in situations where we have the same sensations again. Thus, I shall define acquaintance knowledge as an acquired disposition by which an organism has learned to respond successfully to a sensory induced mental image that presents some particular feature of its environment. Before going into details, I would like to consider how my view on acquaintance relates to Bertrand Russell’s well-known distinction between knowledge by acquaintance and knowledge by description. Although he was not the first to distinguish knowledge by acquaintance from knowledge by description, his characterization has become standard in the vocabulary of contemporary epistemology. The basic intuition behind Russell’s notion seems to be that we have propositional knowledge alongside directly given non-propositional knowledge that requires neither naming nor conceptualization. Russell says, “We have acquaintance with anything of which we are directly aware, without the intermediary of any process of inference or any knowledge of truths.”23 However, Russell also held that sense-data are the objects of which we are immediately conscious. Here our usages of the terms diverge. Russell believed that we have acquaintance with sense-data, of which our conceptions of objects are constructed, whereas I think that sensory images as mental presentations acquaint us with what is presented by the images, which are the physical objects themselves. Furthermore, I hold that just because we are aware of something, this does not imply that we recognize it as a familiar object. The first time we experience something, we are not acquainted with it, but we may subsequently become acquainted with it through our remembrance of its uniqueness. We must learn to identify a particular sensory awareness as a presentation of a distinctive thing before we are  Russell, B. (1912). The Problems of Philosophy, p. 28.

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familiar with that thing. Thus, according to my usage, an organism possesses acquaintance knowledge if, and only if, it is able to recognize an individual, a thing or a place as unique, when it actually experiences it, because it remembers the appearance of this individual, this thing or this place. Having acquaintance knowledge therefore also implies that an organism may be able to recall an image, where the image may consist of different forms of sensory qualities, without the recalled image being produced by the particular entity that originally caused it. Often we remember particular things or episodes by just recalling the image we received when we perceived that very thing or episode we remember. The content of the sensory information we have stored in memory when we sensed this particular object exists in our memory not as a belief but as an image. By recalling this content, we entertain our memory in the particular form of what we have remembered, which is in the form of a mental image. Thus, the remembering of a particular experienced thing is not the remembering of an individual thing but of the sensations that once presented the thing to us and now stored in us as mental images. This process of acquiring knowledge does not require beliefs and therefore involves no concepts.24 Thus, keeping information of a thing’s individuality for later use is possible because the information of this thing is stored such that it carries the sensory image by which the thing was experienced. Much of our experiential orientation in the world is an orientation toward individuals. This holds even more with respect to other animals. A squirrel, for instance, has to recognize and defend its particular territory as consisting of individual trees, houses, etc. Probably this is possible only if visual images make up its mental map of the landscape. Equally, the squirrel has to be able to distinguish between its individual mate and other squirrels. It knows its territory and its mate by acquaintance. It  It seems that animals would have to have the concept, or more Kantianly, the category of being “a thing” in order to be able to recognize this particular set of sensory impressions as indeed the presentation of an object. That is the first one on Kant’s table of concepts. Likewise it would seem that in order to identify a unique individual object would also involve the (conceptual) distinction between essential properties necessary to the object’s being that object, and merely accidental properties which, of course, may change from moment to moment without affecting the individuality of the object. Suppose you recall perceiving an apple fall from a tree. The apple has to stay the same apple against a moving background through the duration of the fall. 24

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seems reasonable to assume that the squirrel originally formed a mental image corresponding to it sensory experience of the territory and of its mate, and then the acquaintance happens when a stored image matches the image made by the actual sensation. If this account is even in general correct, then recognizing individuals not only does not demand beliefs, but knowledge of individuals would be practically impossible if all knowledge must exist in a conceptual form. Also the account is true for humans. We consciously identify people we have seen before by recalling mental pictures of what these people look like. Whenever we attempt to describe a person whom we know well by experience, we mentally call up a visual image of this person before we can begin our description. Our knowledge of our family, friends, and acquaintances consists of mental pictures and not of beliefs. And these pictures become more and more vivid the more we have seen the person in question. So when we think about them, our thoughts are not made up of conceptualized ideas but of images. Like other animals who recognize their territory, human beings think of particular places, they know of, by the help of visual images. All my knowledge of how to get around in my home town is installed in me as information in the form of sensory images, and when I think about a specific way to get from one place to another my thoughts are but a mental reliving of these particular experiences. This characterization of acquaintance knowledge may easily promote the misunderstanding that imaged-based thoughts cannot be the objects of beliefs. But this is far from the case. I know x; say, I know my wife, but I believe that x is F, that my wife is a professor. To believe something is to have a psychological attitude toward a specific thought regardless of whether it is image-based or not. I may form beliefs of something I know by acquaintance. What I want to emphasize, however, is that acquaintance knowledge—as the recognition of an individual—does not require that an organism is able to form such a psychological attitude toward its own thoughts. Beliefs arise only very late in organic evolution, only when animals are capable of conceptualizing the similarities and differences between individual images. Human visual images normally consist of a combination of multiple sensory features such as colors, shapes, and a spatial configuration. The sensory features connecting to other sensory modalities combine features

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in a similar ways; for example, auditory images of a tune combine volumes, pitches, and their temporal order. However, even if we assume that the environmental stimulation of the most primitive organisms causes only a single sensory feature that may still contain enough information to enable such an organism to recognize and react to this feature when it senses this stimulation again. Many primitive organisms like worms, snails or insects are able to learn from their sensations. We do not have to assume that these sensations cause them to have beliefs. In such cases, it suffices to think that the information these organisms receive from a particular sensation automatically triggers a comparison between this image and earlier received images. Eventually these organisms have learned how to manage their behavior according to whenever their sensations give rise to pleasure or its opposite. Apparently, this cognitive process happens independently of any formation of beliefs. Therefore, I think, it is justifiable to assume that evolutionarily the most basic feature of thinking is that it is imagebased and not one that it is belief-based. Most animals, I propose, think only or mainly in sensory images by remembering particular sense impressions. However, more advanced and abstract thinking as we find in humans and other higher animals may be the object of beliefs. That image-based knowledge still dominates much of human thinking is evident from the way we recall the past. The author Marcel Proust is famous for having vividly described in his In Search of Lost Time how he as an adult revisited the past by reproducing images of things he once saw, heard, smelled or touched. Recalling former images seems to be a universal way used by all people to remember individual experiences of the past. Apparently, our memory has different access to images and beliefs and the English language seems to reflect this difference. ‘Recall’ means to bring back or to recollect images. We do not recall beliefs but images. Later archived information about these sensations may help us internally to reestablish past images or externally to identify people or things we have met before. Another argument for why image-based thinking is the original form of thinking and concept-based thinking is evolutionarily speaking relatively new may rely on the way humans and non-humans dream. In general, humans dream by reproducing and recombining successive visual images but other forms of sensory images also enter into such a

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reproduction. Human dreaming occurs mostly, but not wholly, in the state known as REM sleep. During this phase, the electrical activity in the brain is more like a waking state than a sleeping state. Scientists have discovered that mammals, birds, reptiles, and most recently, fish likewise experience REM sleep.25 The electrical activity in these creatures’ brains during REM sleep is quite similar to that of humans while they dream. Of course, this does not prove that other animals are dreaming like us while they are in these sleeping states, but such a suggestion seems to be the best explanation. Since mammals, birds, reptiles and fish do not share a common ancestor within the last 200–300 million years and since these animals in their dreams most likely reproduce those images that characterize their main ways of presenting the world, the conclusion seems to be that image-based thinking is evolutionarily very old.

The Evolution of the Mind A theory of knowledge cannot exist in isolation from a theory of the mind. A naturalist in epistemology must be a naturalist in philosophy of mind. A naturalist believes that the mind evolved gradually from a simple to a complex entity as brains became more and more elaborate in virtue of adaptation by natural selection. Since acquiring knowledge depends on the brain’s cognitive capacity, the naturalist must conclude that the ability of animals to achieve beliefs and knowledge comes in degrees. As a natural phenomenon, beliefs must have empirically accessible properties, and these control the amounts of propositional knowledge we may encounter in other animals as well as in ourselves. For instance, among animals and humans, a young infant knows less than a normal grown up, and a Diana monkey knows less than a human being. An animal is a cognitive subject, but it is also a cognitive agent. The function of sensory knowledge of its environment is to facilitate a possible behavioral reaction of the animal. We may define a cognitive organism, at least in its higher forms, as one in which beliefs, desires,  See, for instance, Yamazaki, R. et al. (2020). Evolutionary Origin of Distinct NREM and REM Sleep. Frontier Psychology, 14 December, https://doi.org/10.3389/fpsyg.2020.567618 25

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expectations, and uncertainties drive its behavior in relation to a sensory presentation of the world. Accumulated knowledge determines an animal’s expectations, and together with its beliefs, desires, and actual sensory experiences, this anticipation may initiate a specific action, whereas sensory experience without accumulated knowledge normally propagates uncertainty that may result in bewilderment and perhaps no action at all. When we talk about sensory knowledge of the external world, we should always think of it as knowledge about the environment to which the organism is cognitively adapted. An organism cannot have knowledge of anything unless its senses and schemas have evolved in a way so as to present that object appropriately, where an appropriate presentation is measured in relation to survival success of this individual. Human beings are no exceptions. Also for humans sensory knowledge is a series of mental states that present the world in accordance to our cognitive capability of processing information and together with our background assumptions dispose us to act in a particular goal-oriented way. Elsewhere I distinguish between sentient beings, thinking beings, and self-reflective beings.26 The characteristics of sentient beings is that they have a mind in virtue of their ability to construct a sensory presentation of the environment to which they are adapted. Thinking beings, however, have primary consciousness in virtue of their capacity of making a conceptual comprehension of their sensory impressions, which at least requires the adaptation of some forms of abstract reasoning. And self-­ reflective beings possess secondary consciousness in virtue of having the ability to reason about their own thinking. This distinction between primary and secondary consciousness raises several questions. Are sentient beings not aware of their surroundings, and if not, what does it take to be aware of the content of one’s sensory presentation? Moreover, is it possible for a sentient being to know something about the content of its sensations without being aware of it? Sentient beings, like rotifers or nematodes, are some of the most primitive organisms that exist today. Wheel animals contain only a couple of hundred neurons. Their eyes—which may be more than two—may  Faye, J. (2019), Ch. 2. As with other analytic categorizations that encompass a continuum of diachronic phenomena, some species may fall down the cracks between one of the categories as they belong to a transitional phase. 26

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consist of a single photoreceptor cell. In addition, other neurons are sensitive to touch in connection with bristles and cilia. Other neurons form a primitive brain that processes and coordinates information from the various receptors, and thereby these neurons possibly create various embryotic presentations, which in connection with motor neurons determine the organism’s behavior. My suggestion is that a mental presentation, apart from being an extrinsic property of the brain, is an adaptive effect of the processing power of the nervous system that reduces and compresses the amount of input information. All sentient beings, whether a wheel animal or a human being, receive more input information than their nervous system can handle and coordinate into a unified response.27 Therefore, as a mental state any sensory presentation has a causal role to play in the description of this biological input-output function. If we assume my suggestion above, I think it is reasonable to say that primitive animals, like rotifers and nematodes, all have mental states in the form of sense impressions, because they all have a rudimentary brain and a nervous system with receptor cells connecting them to the external world. These sense impressions are the causal effects of processed input information and therefore function as ways in which the environment is presented to the organism. I also think that it makes sense to argue that the informational content of these sense impressions appears to the organism in the form of qualitative sensations. But, as Kornblith states, mental states with informational content don’t necessarily add up to beliefs. What is missing? Probably, few philosophers and scientists will attribute beliefs, let alone a mind, to rotifers or nematodes in spite of the fact that these animals may have mental states such as sensations. However, the debate about belief-attribution to animals becomes even more intricate, as we saw above, when we realize that it has been empirically demonstrated that the nematode Caenorhabditis elegans is equipped with memory and several functions of learning.28 Apparently, these small animals are able to accrue information from their sensations and reuse it in their later encounters with their environment. Normally, learning and knowledge are considered closely associated in human beings. We have to learn about something before we can know it.  Faye, J. (2019). Ch. 8.  Ardiel, E.L., & Rankin, C.H. (2010).

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Sometimes we may infer something from what we have already learned; but unless one accepts a priori knowledge (something we shall return to in a following chapter,) what we know is always something we have learned directly or indirectly through out senses. That is why we don’t count lucky guesses as examples of knowledge. It seems self-contradicting to say that I learned something, but I didn’t know the something I learned (although I might have forgotten it again.) Similarly, the same holds if I claim that I know something a posteriori, but I never experienced it myself or was told it by others. Learning is the process of cognition that leads to knowledge. So, and this is my point, if rotifers and nematodes are able to learn from their earlier encounters with their surroundings, because the information about their previous sensations is stored in their memory, they seem to possess knowledge in the form of reliably acquired sensory information about their environment. The critical reply would be that primitive animals, like rotifers and nematodes, might learn about their environment without being sentient beings. However, in my opinion such an objection misses the important distinction between organisms with neurons and those without neurons. The capacity of neurons to convey the amount of input information, which an animal receives from its environment, is highly reduced during their work of information processing even though the organism needs as much information as possible for its own survival. The evolutionary solution is the sensory presentation of the environment. Therefore, the function of neurons is to transform the information of the environmental input into a mental presentation of the informational content, a process that is naturally selected because it has empowered an organism to move around more safely. Thus, critics who refuse to ascribe knowledge to rotifers and nematodes must explain why recognition of the informational content of a sentient being’s sensory presentation is not sufficient for attributing such a mental state to an organism, in spite of the fact that biologists find empirical evidence in support of several learning processes in these organisms. Indeed, a possible objection might be that learning cannot happen without belief-formations, but such a claim seems not true given imaged-­ based acquaintance. As this problem is part of a more general discussion of whether or not every form of knowledge requires the presence of beliefs, I shall discuss it partly in the subsequent section and postpone what remains of this discussion to the following chapter.

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Doxastic Knowledge as Concept-based Knowledge In their introduction to epistemology, Alvin Goldman and Matthew McGrath write that a belief “is a psychological attitude toward a proposition, where a proposition (roughly) is a content that purports to express facts.”29 How far is this statement consistent with the naturalist exposition given until now? It seems obvious to think of beliefs as psychological attitudes toward propositions. The challenge is how we should understand this claim in detail. Philosophers divide with respect to their conception of propositions, but most of them associate this notion with a content that can be expressed in language. For the sake of my argument, however, I shall define a proposition as the content of a thought, which at least humans may express in language. A proposition is in my use of the term the content of a thought that may be the subject of, say, a belief, a hope or a desire. Thus, a belief consists in a positive attitude to some thought, whereas an idea, as we shall discuss in the next chapter, is the intentional object of a particular thought. Of course, we cannot think of animal cognition without expressing our thoughts in a human language, but it would be wrong to think of it in terms whose meaning presupposes the existence of a language. When we talk about non-linguistic organism as having beliefs, we are referring to non-linguistic thinking. Therefore, I shall define a sensory belief as a mental state of an animal in which the animal somehow relies on its thoughts about something in its environment presented to it by some conceptualized sensations. If an animal has the capacity to identify a phenomenon as being of a certain type—i.e. the ability to sort things into classes—because it has experienced similar phenomena before, then the animal has what I shall call a notion of this particular type of phenomenon. To the extent an animal has such a notion, it forms a belief in those cases when it relies on its thoughts about something in the environment, and it is adapted to rely on these thoughts because its behavioral success depends on the content of its thought.  Goldman, A., & McGrath, M. (2015). Epistemology. A Contemporary Introduction. Oxford University Press, p. 4. 29

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So whenever an animal receives sensory information about a state of affairs, which it is able to recognize as of a particular sort, this information usually produces a sensory belief with a specific conceptual content. This happens in cases only where there is a match between the content of the animal’s actual sensory presentation and the content of earlier sensory presentations. However, such a match exists only if the animal has the ability to abstract, compare, and recall the common features that characterize a set consisting of certain previously experienced sensations and the actually experienced sensation while disregarding all non-common features. Such capacities help non-human as well as human animals to navigate in the environment to which they are adapted. A great deal of observational and experimental evidence supports the conclusion that higher animals are able to recognize both individual phenomena and types of phenomena by learning from their sensory experiences. 30 Certainly, one can always hold that animal knowledge is different from human knowledge and decline to ascribe beliefs to non-human animals based on behavioral evidence alone. Making such a move on rational grounds commits one to ascribe a capacity to human, which explains why humans can distinguish types and tokens in their world, but which does not apply equally well to non-humans. One reason that has been given for such an explanation is that humans form concepts only as they learn how to speak a language. And, since non-human animals are unable to speak a language, so the argument goes, they cannot have concepts. Therefore, they cannot have beliefs. Concepts appear only with the advent of language. This attitude is very common among analytic philosophers who associate the possession of concepts with the use of language. As Donald Davidson expressed it: “I think it is possible for an animal to have considerable learned mastery of an environment, to employ implements, solve problems, and generally perform many tasks that require memory, learning, and calculation,  All pet owners know well how dogs and cats are able to identify their owners even after a long separation. Like other animals, they can identify individual objects as well as sorts of objects. Experiments with animals’ object recognition have been carried out for years. Antunes, M. and G. Biala (2012). The Novel Object Recognition Memory: Neurobiology, Test Procedure, and its Modification. Cognitive Processing, 13, 93–110, present a survey study of the methodology behind novel object recognition especially in rodents with many references. The general result is that rodents spend more time with unfamiliar objects. 30

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without ever entertaining a propositional content. I would say such an animal does not have beliefs. …”31 In another place, he gave the following explanation, “a creature cannot have thoughts unless it is an interpreter of the speech of another.”32 Moreover, Davidson is not alone. Daniel Dennett is following suit, although his arguments are not like Davidson’s a priori and normative.33 Also Jonathan Bennett insists that language is necessary for conceptual thoughts.34 And both Jonathan Lowe and Peter Carruthers reject that animals have conscious experience because animals have no concepts drawn from experience, and therefore they do not have what it takes to have higher order thoughts that they have such experiences.35 In my opinion, it is quite the opposite. The evolution of human language was possible only because our ancestors already possessed a large variety of concepts reflecting the content of their sensory beliefs and perhaps non-sensory beliefs. As we shall see later, language emerged to the benefit of social organization because it is a more effective means of communicating one’s internal life into the communal sphere of living than merely making sounds, grunts, gestures, and other bodily behavior. Having sensory beliefs demands, among other things, that an organism recognizes a token as a certain type. Consequently, I suggest that having a concept is nothing but the ability of an organism to identify different  Davidson, D. (1999). Reply to Simon J. Evnine. In Lewis Hahn (Ed.), The Philosophy of Donald Davidson, Open Court, p. 309. 32  Davidson, D. (1984). Thought and Talk. Reprinted in his Inquires into Truth and Interpretation, Oxford University Press, p. 157. However, there is little evidence for such a view, which we shall return to in Chap. 3. 33  It may be ambiguous what Daniel Dennett really thinks. We may describe creatures in accord with the intentional stance by predicting their behavior based on ascribing them beliefs and desires, but he denies that nothing more than an instrumental interpretation of such mentalist terms is empirically justified. See his (1987). The Intentional Stance, MIT Press. See also Dennett, D. (1999). Animal Consciousness: What Matters and Why. In A. Mack (ed.), Humans and Other Animals, 281–300. Ohio State University Press, pp. 292–293. 34  Bennett, J. (1988). Thoughtful Brutes. Proceeding of the American Philosophical Association, 62, 197–210, p. 204. 35  See Lowe, J. (2000). An Introduction to the Philosophy of Mind. Cambridge University Press, pp. 178 ff., and Carruthers, P. (1989). Brute Experience. Journal of Philosophy, 86(5), 258–269. Indeed, Carruthers does not exclude that animals have belief of what they experience, he merely excludes them from having concepts of their beliefs. So he seems to argue that even though no animal may be conscious of having experiences, many may be conscious of what their sensory experiences are about. 31

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sensory tokens as belonging to the same type. This ability is the result of a cognitive process of abstraction by which an organism learns to be familiar with a number of recurring sensory similarities. Evidence tells us at least that many birds and mammals are capable of sorting important things in their environment for their survival, but evidence also seems to indicate that on a proto-level very primitive organisms are adapted to form simple sensations and learn to respond to them as being of a certain type. This leads me to propose the following definition: A concept is a cognitive schema of an animal that enables it to grasp a separable property or an separable object as to be of a specific sort whenever it receives sensory information about this individual property or this individual object. This naturalistic definition of concepts immediately prompts me to explain what the evolutionary function of having concepts is. Why did evolution add an ability to recognize sorts besides individuals? The answer of which I can think is that experiencing things as individuals might involve much too much information to produce successful responses. From an evolutionary perspective, an animal’s ability to categorize its environment into groups of individuals must have been advantageous in many ways because it enabled this animal to think and behave uniformly even though there may be a certain amount of variation in its sensory stimuli. Often it is relevant for animals to react in the same way facing different individuals of the same sort. Many different individuals of the same kind may look differently; smell differently; etc., such that an animal receives a large variation of sensory stimuli even though it is confronted with conspecifics, the same type of predators, the same type of food, etc. So being able to sort these individual stimuli into different categories enables the cognition system of an animal to coordinate a variation among its sensory stimuli with a uniform pattern of responses. How large such a variation can be for the difference in stimuli to no longer be classified under the same concept probably varies from species to species. This analysis now provides us with a means for defining doxastic knowledge in two versions. Doxastic sensory knowledge is a mental state that enables the senses of an organism to present its environment according to its conceptual resources, and this presentation enables the organism to respond successfully to the environment. We shall then say doxastic non-­ sensory knowledge consists of beliefs not caused by a sensory presentation

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but which still helps an organism to manage its survival and reproduction. The latter form of knowledge becomes manifest, for instance, whenever a monkey remembers that leopards are dangerous. It seems to be parts of biological adaptation according to which environmental stimuli are processed into sensations that there exists some cognitive mechanism that compares the informational content of the actual sensations against the informational content of earlier sensations. Such a cognitive mechanism may employ something like a color palette template and a shape morphological template, where information of the later but similar sensations presumably are compared with information stored in these templates, while at the same time these templates probably undergo updates in response to later incoming information. If this were not the case, it would be justified to say that organisms are mere physical automata whose behavior is directly caused by the environmental stimuli without the mediation of mental images and beliefs. Summarizing the discussion to this point, we can say that physical stimulations of the sense organs of an organism, the eyes for instance, create a mental presentation of the environment in the form of a sensory image. The information carried by this image may or may not cause a sensory belief in the organism. In less advanced organisms, this information may be stored only as knowledge made of sensory images; whereas in more advanced animals, the information may be stored both as image-­ based knowledge and as concept-based knowledge. Some animals use image-based knowledge to identify individuals, while they use concept-­ based knowledge to distinguish one type of objects from another type. In the next chapter, we shall look upon the other side of the coin. In this chapter, we have focused only on the side concerning sensory knowledge with respect to externally produced sensations. But animals have sensory knowledge of their environment for a reason. They need sensations in order for them to be able to move around successfully attaining goals they seek and on which their survival depends. Hence, if their locomotion is not accidental or purposeless, animals must be adapted to learn how to behave successfully. Thus, the opposite side of the coin covers internally produced knowledge involving behavior, competences, practices, and skills. As we shall see, the existence of these types of knowledge can be explained without any appeal to the formation of beliefs.

3 Experiential Knowledge Without Beliefs

Many animals obtain sensory beliefs in a reliable way, and therefore concept-­based knowledge is as much a natural phenomenon as is direct image-based knowledge. These animals are not only adapted to acquire knowledge based on sensory images; they are also adapted to make cognitive responses to the sensory resemblances between the content of these images, such that the success of their behavior becomes enhanced. Often animals know how to behave appropriately in given situations. Of course, much of this behavior is instinctual, but other parts are learned. It is both the fitness of information gathering processes, by which animals get to their sensations and beliefs, and the behavioral success that secure the general reliability of their sensations and beliefs. However, besides image-­ based knowledge, both human and non-human animals seem to possess other versions of knowledge, where the traditional evidential commitments to truth and justification is also not an issue, in spite of the fact that these versions of knowledge may sometimes involve beliefs. In the preceding Chapter, we differentiated between sensory knowledge of our environment that is image-based and concept-based, and we found that knowledge by acquaintance is an example of image-based knowledge without involving concepts or beliefs. This chapter focuses on © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. Faye, The Biological and Social Dimensions of Human Knowledge, https://doi.org/10.1007/978-3-031-39137-8_3

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a similar distinction between non-propositional and propositional knowledge in association with skills and practical competence. The phrase “knowing-how” refers to humans’ ability to perform certain actions. A surgeon knows how to operate on a patient, a flutist knows how to play her instrument, and a pre-school child knows how to speak her first language. Such practical knowledge is knowledge about how to behave in specific circumstances. The perfection of these abilities requires skills. My discussion will center on whether or not we can explain knowing-how avoiding of any reference to concepts or beliefs. Often persons who have one of these skills cannot describe in words exactly what they have the ability to do. Their knowledge is outside their conscious awareness; it is, so to speak, tacit, as Michael Polanyi named it. Also, it is common among psychologists and cognitive scientists to talk about embodied cognition as an expression of their assumption that practical understanding involves the activity of the body as much as the brain. Philosophers are used to making a theoretical distinction with respect to humans between procedural knowledge, expressed in terms of “knowing-­ how,” and declarative knowledge stated as “knowing-that”. A similar distinction has been made in various ways, sometimes as one between practical and reflective knowledge, between practical and theoretical knowledge, between non-propositional and propositional knowledge, or between tacit/implicit and explicit knowledge. Here I am in the process of cutting the cake in my own way. I shall distinguish between experiential, empirical, and theoretical knowledge by holding that experiential knowledge includes the sensory knowledge of our environment and the corporeal knowledge of our bodily responses and behavioral practices. In other words, I maintain that what philosophers normally call practical knowledge, and cognitive scientists embodied knowledge, is a kind of experiential knowledge covering information delivered by the internal senses. However, I want to make a distinction between embodied knowledge and practical knowledge by saying that we obtain embodied knowledge by having bodily experiences. As a disposition, this version of knowledge is activated by mere sensory and bodily stimuli. In contrast, practical knowledge, although still obtained by internal and external sensations, is a disposition defined in terms of a certain culture. Such a disposition becomes manifest whenever the agent consciously chooses to perform the

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corresponding action in the “correct” way to reach a certain socially invented goal. Therefore having practical knowledge demands that the agent possesses empirical and not only experiential knowledge. If so, practical knowledge has both a propositional and a non-­propositional part. An important consequence of defining a proposition as a thought, as we shall see, is that neither non-propositional knowledge such as image-­ based knowledge nor such as  embodied knowledge involve beliefs. Without conceptualization, there are no concept-based thoughts, and without concept-based thoughts, there can be no proposition to believe. So I also maintain that neither in humans nor in other animals does experiential knowledge need to have a propositional structure and that in those cases where it in fact has such a structure, it is not equivalent to empirical knowledge. Likewise, experiential knowledge in humans does not always presuppose either beliefs or propositions. What is characteristic of humans is that they also possess empirical and theoretical knowledge in addition to experiential knowledge. The difference between these types of knowledge has its roots in their different origin in that the experiential knowledge is a natural phenomenon, whereas empirical and theoretical knowledge are social phenomena. However, in order to lay out what it takes to have non-propositional knowledge, I shall make a distinction between ideas, beliefs and thoughts. In my usage of the term, ideas are any mental presentation acting as the object of some thoughts, whose content therefore may consist of the informational content of our sensations, but very often is generalized from this content. Simple ideas are, in my opinion, the content of an animal’s thoughts caused by elementary sensations, complex ideas such as composite images are the content of thoughts caused by a structured composition of several or many elementary sensations, whereas general ideas are conceptualized simple or complex ideas. In addition to these ideas we have the abstract ones that are derived from reflection upon those ideas just mentioned.

Ideas, Beliefs, and Thoughts Throughout its long history the empiricist notion of ideas has been used with various meanings. Here I am interested in the connection between ideas, beliefs and thoughts in a naturalistic setting. Whenever we think, our

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thoughts are about something, and this something is the idea, often called the intentional object of our thoughts. In recent times some philosophers, like Wayne Davis, associate ideas only with concepts, holding that “An idea, on my conception, is only one kind of mental representation. Whereas ideas or concepts are wordlike mental representations, images are picturelike, and conceptions are theorylike.”1 So Davis uses, as he himself mentions, ideas and concepts as stylistic variations with essentially the same extension. In contrast to his conception, I use “ideas” to refer to mental states that are objects of our thinking. They may include what have traditionally been called both perceptions and conceptions, or percepts and concepts, in the post-Kantian vocabulary in English, such that we can have both imaged-based and concept-based thoughts. In general, I shall say that when something causes a mental state, then this something becomes the content of that very (re)presentation. So if this something is already a mental state, say a sensation, and it causes another mental state, such as a thought, the sensation becomes an idea by being the object of this thought. An idea is a mental state that is the object of a thought (or rather the intentional object of a thought.) Many mental states never become objects of our thoughts and therefore do not produce beliefs because these mental states do no cause our attention. So a mental state is not an idea unless it is an object of a thought. The difference between ideas and thoughts is that ideas considered by themselves are neither true nor false, whereas thoughts must be capable of being true or false in order to be believed or disbelieved. However, thoughts can also be met by other psychological attitudes, like hope, desire, hate, fear, etc. When a thought is believed, then what is believed is the truth-value of the thought, which is determined by the informational content of the particular mental state that is the object of the thought. I shall therefore consider ideas to be the objects of thought and the informational content of these ideas to be the content of thought. Thus, I take the sensory images or bodily feelings of animals to form the subjects of pre-linguist thinking. On this foundation, human evolution empowered our predecessors to begin to communicate by language. Human beings can think about concepts as they reflect upon their own thinking, but in their most original form, concepts, even for humans,  Davis, W. (2003). Meaning, Expression, and Thought. Cambridge University Press, p. 408.

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signify the classificatory comprehension of sensations. Sensing similarities and differences among our sensations invites them to be classified by natural processes  regardless of whether we consider them as simple or complex mental states. Consequently, I shall say that a simple idea constitutes the object of a particular thought if the mental state is an elementary sensation of a color, a sound or a smell, or an elementary sensation of kinesthetic or vestibular stimulation.2 A complex idea is, for instance, a structured composition of elementary sensations being an object of a thought. Animals also have senses different from human modalities, like magnetoception, electroception and infrared sensing, that presumably cause their own type of sensations. As an object of thought, a simple idea may give rise to a belief stemming from the animal’s adaptation to to be able to classify the content of its external or internal sensations. But even though neither a simple nor a complex idea is necessarily conceptually apprehended, the function of the mental state is to create a response in the animal, which may be either innate or acquired. As mentioned earlier, very primitive animals learn to recognize various sensations from being exposed to them repeatedly, although we would hesitate to ascribe beliefs to them. This process of learning is possible, I maintain, because these animals become acquainted with such sensations by remembering them as elementary images. Now we must confront a problem: How do we identify simple ideas? The immediate response would be to say in virtue of the acquaintance. Whether an idea is the same or different from another idea depends on the adapted ability of the animal to react to its sense impressions. Animals seeing colors do not consciously identify the idea of red or blue in terms of determinate identity conditions. To an animal, as to us, the sensation of a certain color is the mental presentation of certain sensory stimuli. Both humans and color-sensing animals have evolved such that they are mentally able to react to this presentation by direct recognition without  Such an understanding is more in line with Locke’s than with Hume’s. Where Hume believed that simple ideas are faint copies of our sense impressions, Locke considered these ideas as the mind’s reaction to its sensations. A simple idea is in my view a sensation that has become the object of a thought. A perception, in my use of the term, is not like Berkeley’s usage. I use the term to refer to a simple or a complex of simple ideas we recognize when our cognitive faculties provide us with a mental presentation that consists of a simple sensation or a set of different sensations combined into a structured whole. 2

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being conceptually able to specify any identity conditions. However, this does not exclude the possibility that some of them, from acquiring a capacity to classify colors, have evolved the ability to have thoughts that are concept-based. Thus, my suggestion is that animals do remember simple or complex ideas without categorization. However, in those cases where an animal has the capacity to classify some of its ideas, the object of its thought is not merely particular sensations but a result of a categorization of these individual sensations. Categorization is the conceptual grasp of common aspects of individual ideas that enables animals to apprehend an idea to be of a certain type. Indeed, neither individuation nor categorization is possible without memory. The identification of any idea requires a working memory, which seems to rely on the capacity of imagery.3 Likewise, an organism cannot form a sensory belief about the content of its sensations, unless it possesses some cognitive mechanism that matches and compares the memory of earlier received external or internal ideas with currently received ideas. Images, we recall, seem to be faint copies of the original sensations. When we remember how an image like crimson or cramoisy looks, the image we recall is less vivid than our original sensation of these colors. The same holds for composite images that are mental replicas of structured sensations. Whenever you remember a family member (or any other person for that matter) by imagination, their faces are often dull and blurred. So far, neuroscience working with human perception has demonstrated that an activation of the early areas of visual cortex occurs when a normally sighted person imagines something that he or she has

 Keogh, R., & Pearson, J. (2011). Visual imagery and Visual Working Memory. PLoS One, 6(12), 1–8. Talking about the mental capacity of imagery seems reasonable in the case of “external sensations,” but what about sensations like pleasure, pain, hope, desire, etc.? These don’t seem dependent on images. So it might seem as if I give vision a dominant place which might be appropriate for humans, but may not be so central for other animals; some animals have lost vision altogether, who have adapted to cave life, having no use for it. However, I take imagery to be an animal’s ability to recall or reproduce sensations it had earlier, regardless of whether these sensations were internal or external, without such a reproduction is an effect of stimulations that originally caused these sensations. 3

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seen before.4 A likely interpretation of these results is that the imagery of familiar sensations is possible because the imagined sensations are caused by the brain’s ability to generate qualitatively a copy of visual sensations acquired earlier. Such a reproduction, I suggest, takes place without the involvement of any concepts. Imagine I have a visual sensation of some color, and then am asked to close my eyes and report the color I just saw. In this situation, I would immediately attempt to bring the color before my inner eye before reporting what I just saw. Thus, my report of the color would rest on this non-visual image of the earlier perceived color. A reasonable guess is that experiments on people who have been blinded by eye-injury would show a similar feature. I would also suggest that a brain scan would find normal activations in the visual system comparable to people with normal vision. If this proposal is true, it seems to indicate two things. First, our oral report about our actual images presupposes that we have the ability to conceptualize our sensations by which we grasp the type of our visual image. Second, the individuation of the content of any actual visual image takes place against the background of how well it conforms to the content of our earlier experienced sensations without the mediation of any concept. In other words, based on such experiments I assume we evoke an image for our inner gaze before we are able to report the content of what we once saw. Any description of an image would require concepts, while the image, we envision, is a copy of the sensations we originally experienced. Our visual system contains mechanisms of reproduction of individual sensations as images without the help of concepts, which means that we have this ability of identification as part of our biological heritance. Images, like sensations, are always particulars, thus their mental content informs about a particular too. The content of a belief to which a  Cui, X., Jeter, C.B., Yang, D., Montague, P.R., & Eagleman, D.M (2007). Vividness of Mental Imagery: Individual Variability Can be Measured Objectively. Vision Res., 47, 474–478; Kosslyn S.M., Alpert, N.M., & Thompson, W.L. (1997). Neural Systems that Underlie Visual Imagery and Visual Perception: A PET Study. Journal of Nuclear Medicine, 38, 1205–1205; and Kosslyn S.M., Alpert, N.M.,  Thompson, W.L.,  Maljkovic, V.,  &  Weise, S.B. (1993). Visual Mental-Imagery Activates Topographically Organized Visual-Cortex—Pet Investigations. Journal of Cognitive Neuroscience, 5, 263–287. 4

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particular image may give rise depends on the cognitive grasp that the corresponding sensations are of either a particular individual or a particular kind. What I am saying is that all images are particular images (no general ideas), but an image may be taken to directly “represent” what it is an image of when it is an image of a particular individual. However, once it is categorized, conceptualized, it is taken as an image of a type, a genus, even though it is still, like all images, a particular image. Or, in other words, there are no abstract general ideas: an idea is “made general” (Berkeley’s terminology) by being made to stand for any member of a set. The capacity to recognize an individual as an instance of a concept is learned by an animal’s ability to reason abstractly. Therefore, we may say that having beliefs involves conceptual knowledge that, I hold, differs from semantic knowledge. Conceptual knowledge is the ability to know which concepts to associate with which ideas. Hence a sensory belief is cognitively distinguished from a sensory image because it involves higher-­ level areas of the brain than, say, the visual cortex. To explain this claim a bit further, we can say that animals are able to recognize the content of their individual sensations, for instance in the case of being familiar with its mate or offspring, without forming a belief. A belief first appears in case the animal grasps this idea not in its individuality but in its generality, as for example it may come to believe other animals of one kind are predators while those of another kind are prey. Thus, in my opinion, a sensory belief is a psychological attitude to the content of a thought where the content of one’s actual sensations is conceptualized as a generic idea. Having an experience of a red fruit implies that the animal involved also forms a sensory belief based on its individual sensations if it is able to distinguish conceptually between fruits and leaves as well as red and green. An animal’s ability to grasp the redness of an experienced fruit is a necessary condition for its ability to generate a sensory belief on which it may react with a certain behavior. Acquiring this belief helps the animal to recognize the fruit as ripe, not that it has a red fruit experience. The same holds with respect to other general ideas. For instance, whenever a Diana monkey, familiar with leopards, sees or hears one, we have reason to believe from its behavior that its cognitive processes produce a sensory

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belief that this is a leopard and a non-sensory belief that it is dangerous. The sensory belief that this is a leopard and the non-sensory belief that a leopard is dangerous are possible only if the monkey knows how a leopard looks like, or sounds like, and knows that leopards are dangerous. The monkey processes its sensations such that it conceptually apprehends part of what it actually sees or hears as a leopard. Thus, the content of a sensory belief is a general idea formed by comprehending the sensory content as of a certain sort. Ideas are parts of the process of acquiring sensory presentations. The mental content of sensory presentations is what causes the conceptualized presentation of the experienced object in case the animal possesses the cognitive mechanisms for abstracting general ideas out of particular ideas. Indeed, these general ideas would not be particular images. Sensory presentations provide animals with only particular ideas, and whether the particular content has been comprehended. Therefore, to be precise, a sensory belief is a psychological attitude to the content of an actual sensation, in those cases where the comprehension of that content takes the shape of a general idea, because the nervous system presents the object or quality to an animal in a conceptual form. Nature and natural selection have made it such that although we experience physical objects and qualities by means of mental ideas, what we perceive are not these ideas themselves. Rather what we perceive are the objects and qualities, which the ideas are sensations or beliefs of, because the adaptation of human and other animals is such that the information imparted by a mental presentation is information about the object and not about the idea itself. A psychological attitude is not a kind of judgment; therefore, neither is a corresponding belief. In most cases, having a sensory belief happens automatically if the adaptation of an animal has endowed it with the capacity of presenting at least some of its most important sensations conceptually. The brain’s ability to categorize actual stimuli under a concept is not something that is true or false; nor is the conceptual knowledge that the actual stimuli have been categorized as of a particular sort. The latter is just a fact of biological learning. Conceptual knowledge is the outcome of an involuntary process that is reliable or unreliable depending on whether or not the process runs according to the adaptive fitness.

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However, a judgment is a voluntary act that results from a conscious attention to one’s attitude. A judgment is a conscious decision concerning the propositional content of one’s attitude, which requires self-­ consciousness; for instance, whether one‘s beliefs are true or not, or whether one’s desires are fulfilling or not. Finally, I shall say that a thought is the awareness of the content of an image or a belief (or another propositional attitude), i.e. a thought is the awareness of any simple, complex, or general idea, not to mention any abstract idea. When an animal actually entertains a particular idea, it consciously focuses on this idea and therefore it has a thought about the object or quantity that the idea is an idea of, i.e. its “content.” Certainly, I harbor many beliefs and sensations I do not focus on, consciously or even unconsciously. All these mental states are not objects of my thoughts; hence they are only potentially ideas until they becomes the focus of my thinking. Therefore, in the evolution of animals’ mental capacities, I suggest we find two modes of thoughts; namely image-based thoughts and concept-­ based thoughts, which correspond to the respective forms of knowledge. Based on what I argued in the previous chapter, concept-based thoughts have evolved much later than image-based thoughts. The image-based thoughts originate from the awareness of simple or complex sensory ideas, whereas concept-based thoughts stem from the awareness of general sensory ideas. When an animal actually entertains a particular idea, by perceiving or remembering it, it consciously focuses of this idea and therefore it has a thought about the object or quantity that the idea reveals. Neither we nor other animals need to be consciously aware of having a thought. This would require that one is aware of one’s own awareness. Thinking then becomes a temporally ordered series of thoughts structured according to certain cognitive schemas. Furthermore, much of our thinking seems to happen outside the scope of our conscious awareness as when we are unable to solve a problem before going to bed but we can after we have “slept on it.” However, the underlying processes behind thinking, the cognitive manipulation of ideas, may still take place regardless of whether or not the organism takes note of it.

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 xperiential Knowledge as Behavioral or E Actional Knowledge Although our discussion so far has concentrated on knowledge based on the external senses adapted to gain information from the environment, viewed more generally, experiential knowledge also includes information provided by the internal senses of our body. Often we think of these two types of sensations as giving rise to two distinct types of experiential knowledge. The external senses give us knowledge that, whereas the internal senses give us knowledge how, but this is undoubtedly an extreme simplification. My internal senses (together with my vision) tell me how to dance, they give me knowledge how to perform my body movements without loss of balance; but these senses also inform me whether or not I am dancing. Similarly with my external senses. My vision provides me with the idea that a stream is in front of me; but it also provides me with knowledge of how to cross it when I observe a ford. Nevertheless, knowing-­how seems to be based more on internal sensations, whereas knowing-that more often comes from the external senses. What else I have said about experiential knowledge in connection with the external senses also applies to such knowledge gained by the internal senses. Internal sensations are as much mental presentations as external sensations. Each of them may lead to various subcategories of knowledge. For instance, experiential knowledge brought by the internal sensations may be knowledge by acquaintance, as when a bird learns to fly or to catch prey. No beliefs take part in this mode of knowledge nor does the question of truth arise. Likewise, the internal senses may provide knowledge by categorization, as when an animal has learned how to perform a specific type of action in case it wants to deceive other animals. Hence, we have experiential knowledge with or without beliefs that stems directly from both external and internal sensations. Nevertheless, for the sake of this discussion, here I shall divide experiential knowledge into sensory knowledge and embodied knowledge even though I also hold that the acquisition of sensory knowledge is possible only by the assistance of body movements and that of embodied knowledge requires using, say, vision and hearing.

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Human beings obtain embodied knowledge such as knowing how to run, how to dance, or how to bicycle by memorizing the changing content of the internal sensations connected to the vestibular system, proprioception, and nociception. Earlier we saw that primitive organisms might know about their environment based on their external sensations alone. Equally, it seems reasonable to assume that such animals are able to know how to perform behavior according to their external sensations merely based on their internal sensations. As part of a learning process, the cognitive system helps an animal to coordinate particular sensations from its various external receptors with sensations from its internal receptors such that this coordination results in some specific form of behavior. This cognitive coordination is successful if the organism survives. As long as the sensations from the various receptors do not vary, but remain always qualitatively the same—due to the fact that the receptors can handle only discrete-valued signals—the organism has no need to be able to classify its sensations into distinct kinds. The learning process in this case is a simple stimulus and response mechanism. It is only first when an organism can receive continuous-valued signals by the same receptors that the need for conceptualization becomes an issue. It may appear that this analysis of what it means for a signal to carry information implies that knowledge and informational content are identical. This is not quite so. Knowledge is informational content obtained by learning, and the source of this process is quite often a mixture of information obtained by both the external and internal senses. Nevertheless, for analytical reasons, I shall divide acquired informational content delivered by these senses into different kinds, arguing that due to different types of cognitive processing mechanisms we have what I shall call sensorial/pictorial content, categorical content, behavioral and actional content. As we have seen, the sensorial/pictorial content is the presentational state into which an animal enters when physical stimulations of its external senses causally interact with the central nervous system and result in an individual mental sensation. The content of this sensation is either simple, complex, or general. As a simple or complex idea, the content yields knowledge by acquaintance in cases when an animal notices this experience. However, as a general idea the cognitive mechanisms in an animal categorize the content of its sensations into

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distinct types of ideas such that it grasps parts of its environment in a conceptual form. Therefore, an animal that is more primitive has experiential knowledge that stem only from its learned schemas of individuation, whereas higher animals, in addition, have experiential knowledge that requires the ability of categorical classification. The cognitive system of human and non-human animals also possesses informational content that flows from the internal bodily senses. The behavioral content is information we receive by learning how we must move our limbs and body in order perform a particular action, whereas the actional content consists of acquired information about what to do in order to reach successfully a certain goal, say, given some sensory inputs from the environment. The latter is also a practical form of knowledge learned by earlier experiences of how to coordinate our sensory-motor system in relation to achieving a certain goal. I shall say that such actional knowledge is concerned with affordances.5 However, attributing actional knowledge to an animal in the form of a disposition to present affordances requires that the animal possesses the capacity of identifying various affordances. In order to have actional knowledge, an animal must be able to recognize which type of behavior belongs to a particular type of affordance with respect to a given perceptual situation. Actional knowledge is not merely a causal response to some sensory stimuli; it involves a belief about the appropriateness of a particular type of behavior in a particular type of environmental situation, given the animal’s needs and intentions. As it turns out, I distinguish between actional knowledge and behavioral knowledge by arguing that the latter does not present affordances. Behavioral knowledge is just a result of an organism’s ability to recognize the informational content of its internal and external sensations as being identical to or different from that of earlier sensations. In this way, an  Originally, James J. Gibson coined the term “affordance.” In his 1979 book The Ecological Approach to Visual Perception. Houghton Mifflin, he uses the term for whatever the environment offers an animal according to its needs and intensions. In his version, “affordance” is very much associated with the possibilities of perception. However, Donald Norman, in his book The Psychology of Everyday Thing (1988), came up with a new definition where “affordance” stands for appropriate possibilities of action. It is in the later sense that I consider actional states as dispositions to present affordances. The collection of information about affordances happens by doing things guided by the environmental inputs. 5

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organism learns to adjust and coordinate its behavior so it fits a practical purpose like flying, chasing prey, or playing a piano. Learning without categorization of the content instantiates a change in behavior based on trials and errors, whereas learning by categorizing happens over time when the content of fluctuating sense impressions is associated with some recurring features. Some philosophers argue that we have learning by doing where an animal performs some behavior and learns to distinguish successful types from unsuccessful ones. If true, the informational content the animal acquires by its performances seems embedded in the cognitive system as actional beliefs. Thus, actional knowledge consists of some form of information gathered by an organism through its senses and motor system and prepared by particular cognitive schemas such that this information is retrievable for later actional purposes. In addition, actional knowledge includes information gained from an organism’s memories of its own behavior that is part of what some cognitivists call “embodied cognition.” Obviously, most behavior is impossible without sensory knowledge. One cannot demonstrate an ability to perform a certain action such as driving a car unless one gets sensory feedbacks and possesses some background knowledge. The violinist cannot improve her skills unless she receives auditory, kinesthetic, tactual, and visual feedbacks. However, for this discussion the central issue is whether behavioral and actional knowledge presuppose the existence of true beliefs. In epistemology, we usually separate knowing-that from knowing-how, two types of knowledge we gain in different manners, a view I shall challenge at the end of this chapter. Anyway, knowing-that is something we have learned through our external senses and by testimony, whereas knowing-how refers to a practice which we have learned by doing it. Nonetheless, we should treat behavioral knowledge differently from actional knowledge. I take it that the phrase “learning by doing” refers to behavioral knowledge more than actional knowledge. We know what we are doing when we are doing it because we receive the proper visual, kinesthetic, and tactual information, although we may not learn how to do it in other ways than by performing the behavior. Apparently, animals exhibit the same ability of knowing-how. Squids can learn to unscrew the lid of a jar even when confined inside the container, and some animals

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can learn to use tools to recover food and have been observed to do so even in nature, out of a lab situation. However, a squid also seems able to grasp what to do to succeed in reaching a goal. And observations of European jays have disclosed that they know how to get access to an acorn that floats in a narrow glass beaker half full of water by dropping small stones into the beaker until the water surface reaches the rim of the beaker. In both of these cases, knowing-how not only involves behavioral knowledge but also a capacity of categorization, which characterizes actional knowledge. As Sarah A. Jelbert summarizes the literature on tool using animals, “Examples of tool use have since emerged for all classes of vertebrates, and several invertebrate species, although reports remain most common among mammals and birds. However, for the majority of species, tool use consists of the use of one specific tool, for one specific purpose, and is subsequently thought to be under strict genetic control. There appear to be only a small number of exceptions to this rule. The flexible and varied use of tools by great apes and other primates is one clear example (and for a long period of time this was considered to be the only exception) and the behavior of New Caledonian crows is another.”6 Because of the variety of the tools used for different purposes by primates and corvids like the New Caledonian crow, it seems reasonable to assume that they can learn how to prepare and use different tools. Experiential evidence supports such an interpretation. In the case of the New Caledonian crow, Jelbert writes “In the wild, pandanus tool manufacture appears to involve some element of social learning (…) New Caledonian crows raised in captivity have not been observed to produce pandanus tools with adult-­ like proficiency (…), which suggests that juvenile New Caledonian crows may acquire their tool designs from their parents.”7 Does this process of learning involve true sensory beliefs? Reliable true beliefs yes, but justified true beliefs no. Certainly, neither primates nor corvids can acquire the skills of using tools without having both sensory and embodied knowledge. They must  Jelbert, S.A. (2016). Reasoning, Physical and Social Cognition in New Caledonian crows. Ph.d.thesis, University of Auckland. https://researchspace.auckland.ac.nz/handle/2292/29641, p. 16. 7  Jelbert, S.A., p. 37. The deletions in the quotation are several references to relevant literature. 6

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be able to recognize visually an object as a possible tool and another object as edible but outside their reach. However, they also need a belief that relates to how they should use the tool in order to perform successfully. Apparently, humans form most of their sensory beliefs based on visual information, they form sensory beliefs much less based on auditory, tactile, olfactory and gustatory information, and they seem unable to form more than a few sensory beliefs based on kinesthetic and vestibular information. Therefore, it seems correct to assume that the ideas we obtain by proprioception and equilibrioception play a smaller doxastic role in our cognitive system. Indeed, some may object that such an assumption focuses only on consciously obtained beliefs. This is correct. The reason for that is that a sensory belief is a conscious state expressing an attitude concerning the content of an actual sensation. The explanation of skills and competences needs necessarily no introduction of beliefs. For instance, I know how to drive a car physically, and I can do it safely in almost any normal situation. In doing so, I rely on my behavioral skills. I also have some knowledge about the traffic rules and expect other people to have the same. By driving my car, I change its position all the time in relation to the other cars, in relation to road signs, and in relation to the road itself. Although I continuously receive new sensory information, I cannot form sensory beliefs about everything I must do physically in order to drive safely in heavy traffic. My sensory beliefs may enable me to form non-sensory beliefs of what I could do, but this would require that I could form at once beliefs that presented everything I possibly had to do in the situation. Therefore, I do not rely on beliefs; instead, I depend on my behavioral knowledge. Nonetheless, sometimes the sensory beliefs I actually receive cause me to believe which particular kind of action is the appropriate behavior in the given situation. I realize that slower cars drive in the middle lane, and therefore I believe that I should steer my automobile in the outer lane rather than the inner lane. Likewise, I know how to speak, and while talking, I may form a belief that a particular sentence expresses what I want to say. Still I may have no belief about how to construct sentences and pronounce them correctly. Consequently, I know how to speak without having beliefs about how to perform linguistic actions. As I learned to drive or speak my language, my

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brain developed some dispositional states that instruct me to behave, according to the inputs I get from my senses, or according to my intentions. I gain behavioral knowledge by knowing (unconsciously) what to do and how to do it in a variety of situations. However, the lack of beliefs in connection with behavioral knowledge does not imply that it is impossible consciously to describe behavioral knowledge of an individual. We have constructed self-driving cars that can navigate just as well as human steered cars, we can build robots that can outperform human beings, and we can put together machines that speak nearly as well as human beings. However, the abstract theoretical descriptions that make these constructions possible are not necessarily descriptions of the cognitive state of behavior. The theoretical description expresses the engineer’s beliefs, not his or any others’ behavioral knowledge. Rather, the structure of biological organisms’ organization is so different from that of artificial devises that we have no reason to think that those descriptions, which allow us to construct these devices, are identical to the descriptions that would allow us to construct biological organisms. Intelligent machines prove only that in virtue of reflective and abstract thinking humans can design technologies that perform the same sort of tasks that humans and other intelligent animals can do mentally; such machines do not possess the cognitive apparatus of mental beings. They do not have the knowledge that humans need to have in order to have the same behavioral skills. In fact, assigning epistemic states to artificially intelligent machines is not well-defined because “having knowledge” is a property of organisms. So even if we agree on a definition of intelligence and that machines can be intelligent, this would only establish that other things than conscious beings can have intelligence. But the machines, though intelligent, do not think; they do not have mental states.

Why Instincts Are Not Knowledge Much of human knowledge is expressed in behavior, but not all behavior is knowledge based. Instincts are not acquired by sensory information and learning. Rather they consist of genetically transmitted information; thus, I do not consider instincts a category of knowledge but as schemas

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of action. Concomitant to instinctive behavior, we may nevertheless find sensory and behavioral beliefs that trigger an automatic reaction. A reflex behavior, for instance, is an involuntary and predetermined bodily reaction caused by a particular physical stimulation. The central nervous system does not need to be involved in reflex behavior. Reflexes are not instincts, although both reflexes and instincts give organisms innate dispositions for a certain behavior. Reflexes are innate bodily dispositions to react uniformly to a particular cause to which they have been adapted. This reaction does not involve acquired information. Examples of normal reflex behavior are many: such as the pupillary light flex, the corneal flex, and the knee jerk flex. Among reflexes are also more pathological ones such as slow and uncertain movements after drinking too much alcohol, and vomiting after eating spoiled food. In contrast to reflexes, I see instincts as innate cognitive dispositions to behave according to the specific information carried by external signals. However, we have to be more precise, since sharp light causes pupillary contraction. The contraction of the pupils is not the manifestation of a cognitive disposition, because it is the physical feature of light that releases the automatic behavior. The information carried by the light does not play any cognitive role in this process. Instinctive behavior includes, for example, honeybees’ communication by dancing, indicating the location of a profitable food source with respect to the sun to the other occupants of the hive, as well as birds using the sun and stars to migrate during the spring and autumn seasons. In both of these cases, the informational content of the processed signals plays an absolute role in determining the strength and the pattern of the instinctive behavior. For instance, honeybees have different types of dances depending on how far away the scout has discovered patches of flowers yielding nectar and pollen. The waggle dance is famous for containing information about the direction and distance from the hive to the flowers.8 Inside the dark hive, the waggling part of the dance takes place  Famously Karl von Frisch was the first to decipher the meaning of the waggle dance. See von Frisch, K. (1967). The Dance Language and Orientation of Bees. Harvard University Press. A more recent review article is l’Anson Price, R., & Grüter, C. (2015). Why, When and Where Did Honey Bee Dance Communication Evolve? Frontiers in Ecology and Evolution, 3,  125. https://doi. org/10.3389/fevo.2015.00125 8

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at an angle left or right to the vertical honey cups (reference to gravity) and the degrees of the angle inform the other bees about the angle between the direction of sun and the direction of the flowers seen from the hive. In addition, the duration of the waggling, the period before the forager returns to the starting point of the dance and does everything all over again, signals the distance to the target. Hence, the waggle dance contains at least information about the presence of the sun and the flowers, the angle between the sun and the flowers with respect to the hive, and the distances to the flowers. Evolutionary adaptation has hard wired this capacity of conveying information to other honeybees. This conclusion follows from the observation that the progression of the complexity of the dance corresponds to the phylogenetic development of the dance.9 Perhaps more significant in this context is that the bees’ ability to obtain information about the position of the sun and the location of the target flowers from the dance is the result of operant learning. When the respective scout actually received sensory stimulation from the presence of flowers and the sun that carries the relevant information, it gets some sensations that enable it to behave as adaptation has caused it to react. In order for instincts to come into play back in the hive, the world must be sensory presented to the bee in a very specific way such that memory of this mental presentation fits into some generically adapted cognitive schemas, which then triggers a genetic adaptation to react in the required way. Since the scout is able to identify the sun qua light and the flowers qua colors and smells, it is able to do so, not because the bee has some concept of the sun or the flowers, but because its memory has acquainted it with the rays from the sun, the colors and the scents from the flowers. The claim is that as long as the bee is able to recall its earlier sensations—a capacity generally conveyed—it does not need to master any concepts—it can do very well with knowledge of acquaintance and memory or previous acquaintances. Thus, instincts consist of an automatic behavioral reaction to some mental presentations of something in the environment. Some cognitive schemas that function as dispositions to behave in a specific way produce this reaction whenever the organism is presented with the relevant  See l’Anson Price, R., & Grüter, C. (2015).

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sensations of the external world. The actual sensory impressions of the bee most likely occur in company with the memory of the position of the sun and the location of the flowers. Back in the hive, this knowledge triggers the specific genetically imposed schemas of behavior. However, neither the bee’s ability to collect sensory information nor its bodily reaction to the informational content is a result of training or education but of the adaptation of a species’ cognitive system to behave in a certain way automatically when presented with some particular structural features of its environment. Being in a cognitive state of having a sensation may put any creature into a mental state that triggers an instinctive reaction to the information it receives about its environment, whereas being in a cognitive state of reaction may instinctively place a creature in a mental state without any behavioral options. Many forms of behavior involving non-humans as well as humans are involuntarily performed as automatic and immediate responses to internal or external stimuli. Some of these reactions are not even cognitive. Bodily reflexes are of that sort. They need only a physical cause to activate them into existence. Other reactions are definitely cognitive as when nocturnal migrators used the starry night to set the course. The disposition to follow the stars during the spring and during the autumn is genetically installed schemas in the birds’ brain cells. The manifestation of this disposition requires another kind of information, namely the physical input of the actual starlight.

Embodied Cognition and the Extended Mind In a situation where I say, “I know the color English red”, or “I know how to dance quickstep”, it means that I am able to identify English red whenever I see it, or that I can dance quickstep when asked to do a dance. I need not know that “The color English red with hexadecimal color code #ab4b52 is a shade of pink-red. In the RGB color model, #ab4b52 is comprised of 67.06% red, 29.41% green and 32.16% blue. In the HSL color space, #ab4b52 has a hue of 356° (degrees), 39% saturation and 48% lightness,” because this description does not express my knowledge of what English red looks like. Likewise, even if I know that quickstep is

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a lively and light-footed dance, carried out to 4/4 music of 48–52 measures per minute, such a description does not express what I have to know in order to perform the dance. As long as we are dealing with knowledge by acquaintance and knowledge of behavior, we are dealing with knowledge that does necessarily have a propositional content and is not necessarily articulable in a language. This knowledge is tacit. Hence, we may call these different versions of knowledge non-propositional, indicating that the informational content of those cognitive states does not exist in a conceptual form. Others have aired their opposition to non-propositional knowledge. Jason Stanley, for instance, argues that the practical knowledge how can be reduced to propositional knowledge that.10 Thereby he embraces that form of intellectualism that Gilbert Ryle so vehemently attacked.11 Apparently, intellectualism can easily be dismissed by pointing to the lack of propositional transference. Knowing the propositional truth that English red in the RGB color model is such and such does not transfer to knowing what English red looks like. Similarly, knowing the propositional truth concerning quickstep does not enable me to dance quickstep. Stanley defines “knowledge how” as a “practical grasp” of a propositional truth; meaning that an agent must know how a particular behavior realizes the action she wants to perform. This practical grasp does not require that the agent have skills to perform the action herself; it is enough that she knows how she could do it if she were not handicapped in some way or another.12 I have my doubts. First of all what is the designatum of “propositional truth”? According to Stanley, the intellectualist need not hold that the agent should be able to express the propositional content in words; it is enough for the intellectualist that her action implies the

 Stanley, J. (2011a). Know How. Oxford University Press, and Stanley, J. (2011b). Knowing (How). Nôus, 45(2), 207–238. For a criticism, see Felix, C.V., & Stephens, A. (2020). A Naturalistic Perspective on Knowledge How: Grasping Truths in a Practical Way. Philosophies, 5(1), 5. https:// doi.org/10.3390/philosophies5010005; and Stephens, A., & Felix, C.V. (2020). A Cognitive Perspective on Knowledge-How: Why Intellectualism is Neuro-psychologically Implausible. Philosophies, 5(3), 21; https://doi.org/10.3390/philosophies5030021. 11  Ryle, G. (1949). The Concept of Mind. Hutchinton, pp. 30–31. 12  Stanley, J. (2011a), p. 127. 10

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existence of such an abstract content.13 However, apart from some philosophers’ love to juggle with abstract concepts under weightless conditions, Stanley’s assumption that it makes sense to speak about the existence of “propositional truth” seems only to be true for a person who already lives in a sophisticated linguistic community. Otherwise, the existence of such a content is an illusion. For as Michael Devitt points out: “The foraging desert ant wanders all over the place until it finds food and then always heads straight back to its nest.” And he goes on to say, “On the strength of this competence, we feel no qualms about saying that it ‘knows where its nest is.’ But to attribute any propositional attitudes to the ant simply on the strength of that competence seems like soft-minded anthropomorphism.”14 I totally agree. Second, what does the “practical grasp” Stanley is talking about mean? Either it is a mental state, a “non-­ propositional” attitude, which has no “propositional truth” as its object, or this mental state is a “propositional attitude,” because it has a propositional truth as its object. In the first case, the agent has the ability to know how without having a true belief about how to perform this practical grasp (like the desert ant heading back home). In the second case, the agent is in a situation in which her “practical grasp” is equivalent to having a true belief about how she should perform this practical grasp. If so, she must have a practical grasp of how to perform a practical grasp and so on. Given the obvious regress generated here, Stanley has not shown that we cannot have practical knowledge without truth. The distinction between behavioral and actional knowledge aligns with the distinction between image-based and concept-based knowledge in the sense that behavioral knowledge and image-based knowledge are exemplars of knowledge without conceptualization. Behavioral knowledge is evolutionary as early as knowledge of acquaintance. We can explain behavioral knowledge just like acquaintance knowledge by the ability to memorize particular internal and external sensations in the form of feelings and images. In order to be remembered, it is not necessary that the content of these various sensations have any conceptual  Stanley, J. (2011b), p. 215.  Dewitt, M. (2011). Methodology and the Nature of Knowledge-how. Journal of Philosophy, 108(4), 205–218. 13 14

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organization or give rise to any belief. Actional knowledge, on the other hand, cannot be explained without reference to the ability of forming concepts. Since actional knowledge is defined as knowing the appropriate possibility of actions in a given context, it seems evident that one needs to have concepts in order to grasp which type of actions are appropriate and which are inappropriate in this context. Although actional knowledge requires some level of abstraction, it does not requires beliefs, and therefore it is not concerned with propositions. Earlier I made a distinction between embodied knowledge and practical knowledge. Some cognitive scientists regard practical knowledge of action and of contextuality—the fact that one knows what to do in a particular situation—as paradigmatic examples of embodied cognition. These people maintain that our bodily experience shapes many elements of our cognitive abilities; i.e. the experience we receive while using our body to accomplish specific goals. Nowadays few, if any, seriously doubt this. The motivation behind this stance can easily be found in biological evolution. As Margaret Wilson notes, “we have evolved from creatures whose neural resources were devoted primarily to perceptual and motoric processing, and whose cognitive activity consisted largely of immediate, on-line interaction with the environment. Hence human cognition, rather than being centralized, abstract, and sharply distinct from peripheral input and output modules, may instead have deep roots in sensorimotor processing.”15 However, although this gives us a motive for recognizing the significance of embodied knowledge in a naturalistic epistemology, it still leaves open the question of the role embodiment plays in cognition. The survey of embodied cognition that Wilson lays out mentions six positions that often are associated with this approach. Embodied cognition is situated, which means that it involves physical interaction with those things that are actually objects of one’s perception and action. Indeed, situated cognition does not characterize thinking concerning past and future events, nor fantasizing, dreaming, imagination or abstract thinking. It is also time-pressured in the sense that situated agents are  Wilson, M. (2002). Six Views of Embodied Cognition. Psychonomic Bulletin & Review, 9(4), 625–636. 15

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constrained in real time because they do not necessarily have time to think through all steps in a process evolving before their eyes before they have to react. This may hold for embodied cognition but definitely not for all cognition. A third thing is that we off-load cognitive work to the environment. We store cognitive information in our environment and may even let the environment do a lot of cognitive work for us to minimize the amount of information to remember and overcome our cognitive limitations. Also this strategy applies to other forms of cognition. Embodied cognition is said by some to be distributed across the mind, the body, and the environment forming one unifying system. We shall soon return to this assumption. However, Wilson’s objection is right to the point. The environment changes all the time, whereas the brain is a much more permanent structure and its different functions continue to be the same in spite of the changing environment. The brain is an open system receiving inputs and emitting outputs; it is that part of our body, which helps us to gain knowledge about our environment. Furthermore, Wilson discusses the claim that cognition is for action, pure and simple. If this were the case, all cognition would have a practical purpose. She admits that perception serves action, but she points out that perception has other cognitive functions that are only indirectly connected to behavior such as recognition and concept formation. The same, one might say, holds for cognitive processes like dreaming, having aesthetic experiences, and recalling perceptual and non-perceptual knowledge just for pleasure. Finally, she explores whether or not all off-line cognition is body based. Researchers have studied examples of abstract thinking, where the agent seems to make use of sensorimotor functions in a covert way. But where should we draw the distinction between embodied and non-embodied thinking? For instance, recalling visual, auditory or kinesthetic images are mental simulations of some physical aspects of the world that originally evolved for the benefit of perception. Such images are disconnected from external stimulations. Of course, such simulations together with recalling visual and other forms of non-­ propositional memories may be regarded as examples of embodied cognition, because all such presentations are off-line and may be compared to their perceptual counterparts. However, using the term “embodiment” that broadly blurs the distinction between knowing-that and

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knowing-­how. And since the purpose of our discussion of embodiment is to set up a naturalistic epistemology and ground the distinction between knowing-­that and knowing-how in cognitive science, it is in my opinion more constructive to confine the use of “embodied cognition” to behavioral knowledge or knowledge expressing the content of actional states that presents affordances. The term “embodiment” or “embodied cognition” has become so fashionable in psychology, linguistics, and cognitive science that many contributors have an exaggerated notion of the significance of bodily experiences. Consider Robert A. Wilson and Lucia Foglia’s characterization of embodiment. “Many features of cognition are embodied in that they are deeply dependent upon characteristics of the physical body of an agent, such that the agent’s beyond-the-brain body plays a significant causal role, or a physically constitutive role, in that agent’s cognitive processing.”16 This is undoubtedly true as long as we think of the mind as the outcome of information processing in the central nervous system. But as soon as we think that the cognitive processing also takes place in other parts of the body or think that cognitive processing is not even limited to the body but includes the agent’s life world, as the extended mind thesis postulates, we conflate the placement of the physical information processing with the placement conveyed by the informational content. The processing of information from our environment as well as from our body is extended neither to the body nor to the whole world. Instead, it is concentrated to the brain and to the nerve cells connected to the brain. But the processed information has either a sensory or actional content that may concern matters of facts inside or outside the body. The “cognitive system” that humans are said to have is a possession of a human person, the sort of an entity that can be said “to know.” Even though knowledge of something like playing piano is obviously embodied, we do not really think there is knowledge in the pianist’s fingers, although we sometimes speak metaphorically that way. The question of the locus of embodied knowledge is a kind of Rylean category error, like where is the university. Even embodied knowledge does not belong to 16

 Wilson, R.A., & Foglia, L. (2015). Embodied Cognition. Stanford Encyclopedia of Philosophy.

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bodies; it belongs to people or to elephants or kangaroos. Brains and bodies do not know a damn thing; they are just the hardware that are still there when the person is dead. It is the people who have a brain, who do the knowing. Being a naturalist in epistemology means bringing the person, the knower, into nature, not keeping him out, as dualism does. We need a naturalist theory of the “human person.” In such a theory, a person’s body act as a sensorium for human knowledge qua the various internal senses, but humans have no knowledge about their body before their brain has processed the signals from these senses. The extended mind thesis prolongs cognitive processes outward into the agent’s environment. In contrast, I have argued elsewhere in favor of the view called passive externalism, according to which sensory states and actional states cannot be individuated without reference to what has caused these states.17 However, proponents of the extended mind, like Andy Clark and David Chalmers, defend a much stronger thesis, which they call active externalism, maintaining that cognitive states arise through a link between the organism and external entities in an interaction.18 The coupled system, say they, “can be seen as a cognitive system in its own right.” Their argument is that active externalism provides a better and more natural explanation for all kinds of actions, because the actions become part of the overall cognitive system. Later, they claim, “In an explanation, simplicity is power.”19 In other words, when we come up with a natural explanation, it must be as simple as possible. Simplicity, however, depends very much on the subject who points at something as simple; and I for my part find their thesis too simple to be convincing. I find it ontologically much more compelling to argue that cognitive processes are sensory, behavioral and actional states related to brain processes. Also many examples within the history of science show that simplicity does not always lead to explanatory success. The example Clark and Chalmers use to illustrate their point is a comparison between a normal person and a person suffering from dementia.  Faye, J. (2019). How Matter Becomes Conscious. Palgrave Macmillan.  Clark, A., & Chalmers, D.J. (1998). The Extended Mind. Analysis, 58, 10–23. Reprinted in D.J. Chalmers (Ed.), Philosophy of Mind. Oxford University Press, pp. 643–651. 19  Clark, A., & Chalmers, D.J. (1998), p. 647. 17 18

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For an Alzheimer’s patient, Otto, an iPad plays the same role as the memory of a normally functioning agent, named Inga. Otto seems to know that 23 + 17 = 40 before consulting his iPad just as Inga seems to know the same result before consulting her memory. The authors admit that this is not how we normally use words like “believe” and “know”, that is, by ascribing a true belief to Otto. “We do not intend to debate what is standard usage; our broader point is that the notion of belief should be used so that Otto qualifies as having the belief in question.”20 By contrast, if one opposes their proposal, they call for an argument that demonstrates that there are any substantial differences between the two examples. One might ask if Otto’s cognitive system is mental? Usually we would say that the mind consists of mental states such as experiences, conjectures, notions, desires, etc., and that such mental states are parts of the happenings in a living organism. Besides these mental states, the mind also contains behavioral and actional states. However, the authors hold that, at least with respect to our beliefs, they may be partly constituted by features in our environment. They rightly reject that a possible objection is to be found in the observation that cognitive processes are usually linked to a consciousness. We are not aware of many of our cognitive processes; for example, how we remember to find the right words, how we ride a bike, etc. As we have seen, embodied knowledge consists of behavioral and actional states rather than merely sensory states. Also at any particular moment, we are unaware of almost all of our everyday knowledge and theoretical knowledge. Therefore, the mind is much more than our momentary awareness and consciousness. Nevertheless, I think it is simpler and more adequate to say that Otto does not know the mathematical result, but he knows where to find the wanted information. Inga knows the result. She need not know that she must consult her memory to get the calculation. One could also say that Inga has direct access to her own knowledge because her sensations and memories are private, while Otto would not have direct access to his knowledge in case the environment partly constituted his knowledge. Therefore, anybody else could have access to Otto’s knowledge, but not to Inga’s. This is not quite the same objection that Clark and Chalmers 20

 Clark, A., & Chalmers, D.J. (1998), p. 648.

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themselves raise, namely that Otto has perceptual access to his “memory”, while Inga has introspective access to her “memory”. What is important here is that Inga’s cognitive states are private, because her brain does the information processing and thereby confines her cognitive states to her. This same holds for Otto regardless of what is the source of his cognitive states. One could well ask whether the operator of The Large Hadron Collider at CERN or of Voyager 1 (21 billion km from the earth) does form a cognitive system with the instrument with which he or she is paired. The cognitive situation of the operators is not significantly different from that of Otto. It implies that the cognitive system, consisting of the operator and Voyager 1, forms a 21 billion km. long system. This reminds me of Bruno Latour’s suggestion that the recent discovery that Ramses II died from tuberculosis implies that Ramses’ death and the laboratory in which the discovery took place form one large cognitive system spanning more than 3000 years. 21 When Ramses died, no one knew the cause of tuberculosis, and therefore he could not have died at that time of that illness. It is only after the discovery of the tuberculosis bacillus that the bacillus came into existence in Ramses. Of course, the information that Voyager and Ramses’ mummy produce causes in the operator of Voyager 1 and in the microbiologist—who discovered that Ramses suffered from tuberculosis—to be in a private cognitive state in the form of their beliefs. These beliefs are private, as they exist contained in the nervous system that belongs to the two men physically independently of the information source. Shut down the brain and no processing happens. I see no explanatory advantage to go further than by claiming that we understand a cognitive system only as far as it comprises sensory, behavioral and actional states whose informational content either presents the state of our body and its environment or instructs us in our behavior. We receive information also  Latour, B. (1999). On the Partial Existence of Existing and Non-existing Objects. In L. Daston (Ed.), Biographies of Scientific Objects. University of Chicago Press, pp. 247–269. Here he claims: “Yes, the bacillus has been there all along, but only after the sanitary flight to Paris that allowed ‘our scientists’ to retrofit all of Egyptian history with a Pharaoh that, from now on, cough and spits Koch’s bacilli, even when disputing with Moses about how long the Ten Plagues will last …”, p. 266. 21

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by responding to the world and not only by watching it. The processing and coordination of this information takes place such that it helps the animal to move around and discover what its environment is like. Acknowledging embodied cognition is profitable in an explanation only if it is kept within the above demarcation by arguing that non-­ propositional knowledge is a genuine part of our individual knowledge system. Indeed, as natural phenomena it is presupposed that both non-­ propositional and propositional based knowledge share enough features to make sense of placing them under the same conceptual umbrella. One such feature could be stored information about the internal and external environment. The immediate reaction to such a proposal might be to point at a book or a computer, arguing that these items also contain a lot of stored information about how things are. However, we may say that a book and a computer contain information, not that these objects possess knowledge. The difference is that an organism has knowledge in the form of stored information because of the functional role this information plays as mental states in disposing the organism for action, whereas information contained by the book or the computer does not play such role. Apart from stored information based on earlier encounters, an organism also constantly gains new sensory and bodily information about the actual world as long as it is awake.22 In case we include robots or chatbots, we may perhaps attribute knowledge to them and the ability to think, because these machines are built to acquire and store information for the use of their own behavior. This may happen regardless of the reasons we may have for not attributing sensory experiences to any of them. Sensory experiences, and therefore the experiential knowledge we obtain from having them, are mental states; but, as I have argued elsewhere, the qualitative properties of these mental states are a result of biological adaptation, which compensates for the slow

 The brain continues to receive input from the external world even in sleep. It’s not conscious awareness, but enough to cause action responses such as rolling over or scratching an itch, etc. And, of course, knowing when you have to pee. 22

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information processing speed of the brain.23 Having this in mind, the kind of channel by which an artificial system receives information seems not relevant for classifying such information as knowledge. What is pertinent, however, is that this information is reliable and can be stored and used to guide the system to behave according to new information flowing into the system through its sensors. In the case of robots or chatbots, we have designed them so their internal processes, as well as their memory, are reliable. With respect to embodied cognition, I hold that propositional knowledge presupposes the existence of non-propositional knowledge such as acquaintance knowledge and behavioral and actional knowledge. I believe experiential knowledge expressed in a language builds on experiential knowledge not expressed (non-human animals) or directly inexpressible in a language. Assume an organism is by adaptation unable to behave but can receive, say, only visual and auditory sense impressions. Moreover, allow it to have a memory and therefore an ability to compare earlier sensations with later ones. All we can expect from such an organism is the ability to be acquainted with colors, shapes and sounds, and nothing more. Since it cannot move around and get different sensory perspectives on visual and auditory phenomena, and since it cannot interact with these visual and auditory phenomena, this organism could never be adapted to realize that there are objects and therefore develop a concept of sensations internal and external to its own body. Consequently, there would be no evolutionary forces working on this organism to develop a mental awareness of physical phenomena or of other organisms, and therefore to develop a system of communication, because such a cognitive apprehension requires a concept of the existence of independent

 Faye, J. (2019). How Matter Becomes Conscious. Palgrave Macmillan. Attributing thinking to machines implies changing the definition of thinking so that it no longer requires the manipulation of ideas in a consciousness, but includes following digital computational algorithms as “thinking.” When I “think” I do not do this. AI advocates essentially change the definition in this way, but somewhat slyly. A psychologist might examine my thinking, but to analyze a machine’s “thinking” (in this sense) no psychologist would be relevant; rather I would need a computer engineer. 23

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objects or subjects.24 Contrary to such an organism, we may imagine another organism deprived from both its visual and auditory sensations but having the capacity of moving around and sensing by touching. An illustration of such an individual would be the famous history of Helen Keller who became deaf and blind when she was 19 months old. Because she was able to move around, she had a capacity to develop her sense of objects and her sense of locomotion, and because she had a sense of touch, she was able to learn that each object surrounding her had a name. This happened when Keller understood that the word written in her palm by her teacher’s moving fingers stood for such objects that she could touch with the other hand. Until then she automatically learned to recognize things by her tactile and kinesthetic sensations. Eventually Keller learned oral and written communication by connecting types of signs to her types of sensations. Had Keller been paralyzed in addition to her visual and auditory inabilities, she would almost certainly not have had any comprehension of something outside her own body. In fact, she would have had only a little grasp of her own body, and therefore she would not have been in a position to learn anything. We may conclude that experiential knowledge that comprises true beliefs presupposes experiential knowledge of acquaintance (Helen’s tactile sense) and behavioral knowledge that are reliably required but neither believed nor justified.

Blending of Knowing-how and Knowing-that From an evolutionary point of view, I have argued that image-based knowledge evolved before concept-based knowledge. Often when we are in doubt about how to perform a certain action, we consult our imagination rather than any propositional thought. But does it make sense to say that knowing-how developed earlier than knowing-that? I think not.  Expanding on this observation, we see that our capacity of intervening into the passive structure of our experiences is even more urgent whenever science wants to establish the independent existence of various invisible but more hypothetical entities. The need of practical knowledge for establishing a representation is exactly what Ian Hacking calls upon in his book Representing and Intervening. Cambridge University Press, 1983. Here he argues that the existence of an entity be represented by some scientific hypothesis requires that scientists can use this entity in their experimental manipulation of other entities. 24

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Earlier I identified four modes of experiential knowledge, but the distinction between knowing-that and knowing-how does not match the two sensory modes and the two embodied modes respectively. It seems impossible to acquire knowledge of how without also having an image of the object that is the aim of one’s behavior, but an organism does not need to know anything generically about the object. The ability of knowing-how cannot function without interacting with the presence of some form of image-based knowledge. Does this not imply that knowing-that is reducible to knowing-how because knowing-how is more fundamental? Apparently not. Because our knowing-how is often about an action that is defined in terms of a goal, which the action intentionally accomplishes, but which we know about in virtue of the definition. Moreover, such a reduction also requires that knowing-how can be regarded as a natural kind of knowledge. The distinction between knowledge-how and knowledge-that is deeply embedded in traditional analytic epistemology, but it not as clear-cut as it may seem. It immediately signals an epistemic distinction rather than one discovered empirically by comparative psychology or cognitive science. Gilbert Ryle denied that these two kinds of knowledge were reducible to each other, whereas Stephen Hetherington claims that knowledge-that can be reduced to knowledge-how: “I call this the practicalist reduction of knowledge-that. One’s knowing that p is one’s knowing how to perform various actions.”25 Thus, Hetherington’s practicalist reduction stands in opposition to the intellectualist reduction, we discussed above. However, I disagree with both Ryle and Hetherington, just as I do not agree with those who want to argue that knowledge-how is reducible to knowledge-that. The issue for them and others is that ‘knowledge-how’ and ‘knowledge-that’ label an alleged ontological distinction within epistemology, with some arguing that these forms of knowledge are metaphysically distinct, while others contending that they are identical, since one is reducible to the other. In contrast, I think we should make a distinction between ‘knowing-how’ and ‘knowing-that’ only for analytic  Hetherington, S. (2011). How to Know. A Practicalist Conception of Knowledge. Wiley-­ Blackwell, p. 28. 25

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purposes to describe differences in our justificatory practices concerning human knowledge. The distinction does not refer to some pre-existing metaphysical kinds. ‘Knowing-that’ denotes mental states whose content we are able to express in language and able to justify by the use of language, whereas ‘knowing-how’ denotes mental states whose content we can only describe in language with great difficulty, and which we cannot justify by the use of language. So experiential knowledge manifests itself to us as either capable of being articulated in ordinary language or not. Because of this, we treat these various cognitive manifestations distinctively. However, the different manifestations of sensory and embodied knowledge may help us to understand why some non-occurrent knowledge is retrievable spontaneously by consciously thinking of a belief or an image acquired earlier, or by a willful mental act, whereas other non-­ occurrent knowledge can be retrieved only by bodily performance. Originally, experiential knowledge had only an adaptive function to help animals to survive. There was no need for an animal to be self-­ conscious about having sensory or bodily acquired experiences. Later, the experiential knowledge of human beings became social and extended to areas that had no connection to our direct survival. During this process of evolution, humans gained a particular awareness of those parts of their experiences that were beneficial for others in social cooperation and therefore had to be articulated in language. Experiential knowledge, expressed in language, became part of our discursive communication and eventually engendered an oral justificatory practice manifested as knowing-­that. In contrast, experiential knowledge that was not expressed in language, because it was not needed for others, resulted in a bodily justificatory practice or knowing-how. The former variety of experimental knowledge, knowing-that, relied on evidence represented by language, whereas the latter, knowing-how, rested on the evidence of corporal enactment. However, the different practices with respect to experiential knowledge expressed as knowing-how and knowing-that do not indicate that we are dealing with distinction between natural kinds to which a naturalist must be committed. The fact that little of our embodied knowledge can be/is expressed in language is probably due to evolution, because our predecessors had little use for conceptualizing and communicating this part of their experiential knowledge that was not object of their conscious

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thinking. For instance, today we know that it is theoretically possible to construct robots that are able to do what we can do. This shows, however, that human beings’ embodied knowledge can be grasped theoretically such that it can be expressed in an algorithm in order for the robot to behave as a human—not that the robot is experiencing the cognitive states that a human would experience when doing the same action (or indeed that the robot has any cognitive states (any consciousness at all.)) Indeed, the evolution of language introduces a third justificatory practice produced by the psychological insight that we may call ‘knowing-­ what’. Much empirical and theoretical knowledge exist only because such knowledge is about social constructions made possible by language. Being married in a modern society, say, is a social construction specified in legal texts. I know how to become married if I know what it means to follow the instructions of these laws. I show my knowledge of what it means to be married if I am able to say that I must intentionally do this and that to be married and that this is a correct rendering of the meaning of the law. I know that I must do this and that to become married, because I know what it means to perform those actions that the law prescribes. Whether my knowing-how, knowing-that or knowing-what has priority with respect to the others, in a given epistemic situation, depends on whether I am in a situation in which I have to justify my knowledge about what the instruction means, or about how to act according to the instructions, or that one is married if one has intentionally followed the instructions. Thus, the traditional distinction between knowing-that and knowing-how marks a distinction that characterizes our different justificatory practices depending on whether our knowledge is or is not language-­based. Neither has metaphysical priority over the other nor do they mark ontologically distinct kinds of knowledge. Traditional analytic epistemology has asked the wrong question; it should ask which form of justification is the appropriate choice on a specific occasion—a question that is entirely contextual. Since the various distinctions of knowledge are made for different purposes, it is not that surprising that they do not map neatly on each other. We have just argued that knowing-how versus knowing-that is not a distinction about two kinds of knowledge but an analytic tool to understand our cognitive abilities to access various modes of knowledge. There is also

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knowing-by-acquaintance versus knowing-by-description, a wellploughed field, and it does not fit neatly onto either the practical/theoretical, the practical/reflective, or the how/that distinctions. So that is why it is easy to get lost in this jungle. For instance, when a gazelle picks up a certain scent, it knows that a lion is near. I would be willing to call the gazelle’s knowing that, when a lion is present, it should flee “reflective,” but its knowing-that is not reflective. So I think there is both reflective and non-reflective knowing-that. Likewise, I think that there are both reflective and non-reflective versions of knowing-how. Much scientific knowledge concerns the way things develop, how they function, react, or are structured to the extent that that some experiences justify our expectations that we will have other experiences. Although this knowledge is gained by theoretical reflection, and not by doing, it is still knowledge of how things would proceed justified by our experience. Just as there is little reason to think that reflective knowing-how can be justified in terms of non-reflective knowing-that, the same holds with respect to whether the former can account for the latter. Rather these varieties of knowledge may support and enhance each other. To see how let us consider an example: a musician plays her instrument. Long before they speak a language, children learn very early on to coordinate the movement of their fingers, hands, arms, legs, tongue, and the rest of their bodies to be able of fulfilling certain unintended goals. We may think of these movements as basic behaviors involving no more than behavioral knowledge. We practice basic behavior whenever we use our body parts to drink, eat, talk, walk, etc. The only knowledge, we need for these basic forms of behavior, is knowing how to carry out these basic movements, like grapping a thing, lifting an arm, or placing one foot before the other, none of which require any conscious understanding of what we are doing in order to do it. But, in contrast, when a flutist plays her instrument, she not only does have a conscious understanding of what she is doing, but also it seems necessary for her to understand what it means to play a flute. She must know what do with the flute before she knows how to do it. She must have an idea of a flute, an idea of where to place her fingers and an idea of what it means to play music. In other words, her embodied knowledge has become socialized and organized into practical skills.

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Many of our skilled actions involve very complex behaviors that consist of a series of more basic behaviors. So even though we think of swimming, dancing, performing surgery and playing a flute as examples of knowing-how, one could argue that such more complex behaviors would not be possible unless the actor has a concept of swimming, dancing, carrying out surgery and playing flute and that the person is aware of the implications of these concepts. Indeed, this does not tell against the assumption that doing these complex actions require only non-­ propositional knowledge. A counterargument might be that knowing-how cannot be identified with basic activities that are purely physical (say, movement of your arms and legs). What matters is the coordination of these basic activities into a purposeful performance (swimming instead dancing), and this coordination requires knowledge about what it means to swim, knowing that these movements bring you forward in the act of swimming. As an intellectualist, Stanley holds that “knowing-how to do something is a kind of propositional knowledge, a kind of propositional knowledge that guides skilled actions.” 26 A person could insist that propositional knowledge helps us to organize the basic activities, the behavioral atoms, so to speak, such that they follow each other in the correct order and in the right number. Knowing-how to perform actions like swimming, dancing, driving, or playing piano does not appear until we have ideas of what swimming is, what dancing is, what driving is, or what playing piano is, and we learn these ideas in terms of non-reflective knowing-that.  Stanley, J. (2011a), p. 150. This view does not stand unchallenged. In a couple of papers, Felix, C.V., & Stephens, A. (2020), and Stephens, A., & Felix, C.V. (2020) discuss much of the literature within psychology and cognitive science supporting their claim that knowing-how is not reducible to knowing-that. The authors focus on what they take to be basic activities such as moving one’s tongue while speaking as the paradigmatic example of knowing-that. In addition, they say that slips of the tongue reveal the existence of such basic activities. For instance the slip of the tongue where you intend to say one thing but say something slightly different. I agree in general; although I also think that Stanley could argue that slips are a species of propositional knowledge where the knowledge of the practical performance has a different content from the knowledge being expressed by the performance. Why should he deny that beneath a person’s knowledge structure and the ability to make basic inferences there is a causal structure? If there is a causal relation between these sets of beliefs, this might explain why people sometimes say something they do not intend but something closely similar. Knowing to speak a certain sentence causes you to utter that sentence properly most of the time, but you may sometimes fail to do so properly due to other factors that may causally influence the content of your utterance. 26

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I acknowledge all of this! The examples given here are culturally defined actions where we sensually, intentionally, consciously and perhaps reflectively have learned to combine basic actions into more complex actions as specified by linguistic definitions. But even though we admit that complex actions within a socially constructed sphere of actors could not exist without propositional knowledge, that admission does not get us to the conclusion that knowing-how is reducible to knowing-that. In order to get there one has to argue, which Stanley also does, that there is such a thing as propositional knowledge, which is not capable of being verbalized, and that knowing-how to do something is a form of conceptual knowledge. But this a straw that does not break the camel’s back. Conceptualization of sensations and feelings stemming from external and internal inputs is a comprehension of the world by their sorts, which in and by itself does not imply any particular form of knowledge. Such presentations happen automatically as expressions of some fundamental cognitive mechanisms. Therefore, the capacity for conceptualization is rather a natural necessary precondition for having experiential beliefs. Moreover, it seems obvious that two people may possess the same amount of knowing that one has to perform such and such in order to dance quickstep. However, such propositional knowledge does not inform them about how to coordinate the basic movements of their muscles, and how to administrate their bodily forces, to bring forth the required movements. As an introduction to quickstep, the dancing teacher may provide the students with knowledge of the steps, by which the community understands dancing quickstep, but then again such performances are just as physical as they are mental. Those couples of students learn how to move around and use their bodily muscles in our gravitational field according the dance’s rules by doing it and not just by thinking about it. This is not to say that either the actors themselves or an observer of the action cannot reflectively describe these forces and movements in propositional terms. Indeed, we can. The same holds for our general use of language. The claim is only to say that the conceptualization “propositional knowledge” arrived with our capacity of describing our knowledge by language and that non-propositional knowledge, based on simple external and internal sensations, is enough to bring about purposeful actions.

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Ultimately, the distinction between knowing-how and knowing-that is not to be found in nature but in our culture. It reflects different epistemic practices of demonstrating that we actually know what we pretend to know, something that depends on whether our knowledge is linguistically or not linguistically formulated.

4 Human Sensory Knowledge

The epistemological discussions of most Western philosophy continue to debate knowledge in the tradition of René Descartes, according to which knowledge is a uniquely human characteristic, distinguishing those who have souls from the beasts who do not. One should not choose to tell the story of how animals have been treated in epistemology without mentioning the historical fact that all of this was very connected to the older religious dispute of whether animals have souls, and that thanks to Plato and Aristotle, the notion of the soul was very much tied to mind. These religious questions do not influence contemporary epistemology, but they very much did influence the history of epistemology. Thus, epistemologists have generally ignoring that natural science no longer looks upon animals as fundamentally biochemical automata. And even though most modern philosophers accept animals as conscious beings or distance themselves from Descartes’ representationalism, they still hold that the cognitive states of non-human animals do not reach the status of being epistemic states, because they are not subject to any normative commitments of justification. In both cases, epistemology is an area that covers only human cognitive states and not that of other animals. Moreover, all these philosophers consider those epistemic states to be restricted to holding beliefs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. Faye, The Biological and Social Dimensions of Human Knowledge, https://doi.org/10.1007/978-3-031-39137-8_4

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The outcome is that we find two major schools of thoughts in philosophy concerning human knowledge. Anti-naturalists follow the tradition, going back to Descartes emphasizing the differences between humans and other animals and the justificatory and normative character of human knowledge. The standard analysis is the key to understanding traditional epistemology. In contrast, naturalists side with Hume in pointing to the similarities between humans and non-humans in their main approach to understanding epistemology. Indeed, anti-naturalists have their reasons: they hold that knowledge requires mental states such as beliefs and not mere sensory information, and that the ascription of knowledge depends on epistemic norms such as being individually responsible for holding a belief to be true, commitments no animal is able to meet. But also naturalists follow the long tradition of epistemology in assuming that sensory knowledge must be explained in terms of the acquisition of beliefs, though they replace the demand of rational justification with that of reliability due to the influence of pragmatism. Moreover, naturalists have a tendency to hold that we often form beliefs in the context of a social order and a worldview that depends on others. As already mentioned, I part company with anti-naturalists in virtue of supporting the naturalists’ claim that animals have sensory knowledge, as they are able to learn about the environment to which they are adapted. The information non-human animals acquire by their senses has exactly the same function that sensory knowledge has in humans. In both cases, the purpose is to help the subjects in their environmental orientation for the benefit of survival. So unless sensory information in humans has characteristics other than the functional ones they share with sensory information in non-humans, there is no reason to maintain that human sensory knowledge is radically different from that of non-human sensory knowledge. Of course, the anti-naturalist might argue that one such characteristic feature could be that human knowledge involves beliefs, and since beliefs may be false, a theory of knowledge requires commitments to norms of justification. Sensory information that does not engender beliefs is disqualified as proper knowledge because sensory information is not subject to a justificatory process. Sensory impressions may cause an organism to behave in a certain way without necessarily involving any beliefs at all,

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much less beliefs about the content of one’s beliefs. Sensory impressions contain information about the environment, but the organism does not need to react to that informational content by forming a belief as I discussed in connection with sensory acquaintance and behavioral knowledge. In non-human animals, the causal chain leading from sense impressions to a particular behavior may altogether avoid belief-­ formation. In the same way, one could argue that the lack of truth-­ carrying beliefs marks the difference between the object of cognitive science and that of epistemology. Cognitive science does not care whether beliefs are true or false; truth and epistemic responsibility are not its concern. Instead, it pays attention to the causal roles of various cognitive mechanisms from the environmental impact on an organism to its behavioral change within its environment. Therefore, epistemology can never be a branch of cognitive science. I agree with this line of argument that epistemology is not an older version of what cognitive science is today. It has merits quite independent of cognitive science or comparative biology. Although, as a naturalist, I hold that sensory knowledge is a ubiquitous phenomenon in the animal kingdom, I also believe that a philosophical theory of knowledge has to provide an account for the normative aspects of knowledge we meet among people in social communities. As already argued, it makes sense to ascribe both external and internal knowledge to non-human animals, despite these animals cannot justify possible beliefs by pointing to evidence. I shall argue that the epistemic situation does not change with respect to humans, even though the standard analysis presupposes that humans and non-humans are epistemically distinct with respect to cognition. Epistemology should not ignore the biological function of sensory knowledge with respect to individual organisms in the first place. Nevertheless, it must also be able to elaborate on how and why the ascription of knowledge to humans in a social setting has, as an empirical fact, developed commitments to certain epistemic standards. My account of the significance of both biological and social functions unfolds in some of the later chapters. In the present Chapter, I will explain why the standard analysis of knowledge fails in general. In this connection, it is essential to remember the difference between sensory and empirical knowledge. Sensory

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knowledge is concerned with what I directly perceive, while the much larger category of empirical knowledge includes all those beliefs that are inferentially supported by the sensory foundation. The sentence “I see the elephant” expresses my sensory belief, whereas “Elephants live in Africa” states my empirical belief that is justified by evidence such as sensory beliefs, testimonies and other empirical claims. So some form of justification seems to be required for having empirical knowledge; however, I maintain that concept-based sensory knowledge is “obtained directly” without any justification as long as humans and non-humans classify correctly what they see. You might say that the “justification” of a sensory belief is normally the perception itself, because its reliability is not engendered by holding further beliefs but in virtue of its adaptation. The latter claim is exactly what some philosophers question. But, as we have seen, no belief is needed to account for knowledge of acquaintance or embodied knowledge. And, as we now see further, that neither is justification needed to account for sensory knowledge in all those experiential situations in which a cognitive agent conceptually apprehends what happens in its environment. While I attempt to counter the standard analysis, I shall especially challenge an influential view of Wilfrid Sellars’ on sensory knowledge that seeks to accommodate naturalism with the justification of sensory beliefs. The problem with his view is that he associates sensory knowledge with the uniquely human ability to report one’s beliefs and to commit oneself to the implications of these reports.

Knowledge as Justified True Beliefs Commonly we take knowledge in humans to be a mental state, which is accessible for conscious deliberation when we merely think of it or need it for practical purposes or social communication. The content of human knowledge is expressible in plain language or in technical terms as soon as it becomes a subject of our conscious awareness. Thus, traditional epistemology sees knowledge as consisting of justified true beliefs, and only as such. Prior to the nineteenth century, Western philosophers associated knowledge not merely with truth but also with certainty. Knowledge had to be not only true but also necessarily so. However, modern

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epistemology is open to treating as genuine knowledge inductively established assumptions, which as we know all too well are not certain. The requirement is merely that to ascribe truth to our belief it must be in principle justifiable or perhaps even justified. The standard analysis builds upon some explicit or implicit a priori presuppositions. Primarily human knowledge consists of conscious beliefs that have to be non-accidentally true. Beliefs have to be conscious because were we not aware of having them, we could not be responsible for their justification in terms of further beliefs. A person’s knowledge is confined to that person only and that particular knowledge is immediately accessible only to this very subject. No person knows something that he or she cannot consciously retrieve from his or her memory. Knowledge not retrievable is forgotten knowledge. Traditional epistemology must have some substantial reasons for claiming that an analysis of knowledge must include beliefs as an essential component, reasons that also seem convincing to many naturalists. Apparently, these reasons have to do with mispresentations, that is, cases where things appear to be other than what they really are. Think of the barn façade example, first made famous by Alvin Goldman.1 Henry drives through a landscape of cows, sheep, horses, and barns, which he points out to his son, while they pass by. Without Henry’s knowledge, he begins to drive through a landscape that does not consist of real barns, but of fake barns consisting of only barn façades that are indistinguishable from real barns from the road. Before Henry meets the first dummy, he knows what he sees, but when he sees the first fake one and mistakes it as a real barn, then he does not know what he sees. However, he believes, although incorrectly, that the dummies are real. So it seems natural to think that beliefs are more fundamental than knowledge, and that we characterize knowledge by adding certain constraints such that beliefs must be true and justified or reliable. There is also the semantics of the relevant terms. In English, it would not be a well-formed sentence to say “S knows that P, but does not believe that P.” If someone were to say such

 Goldman, A. (1992). Epistemic Folkways and Scientific Epistemology. In Liaisons: Philosophy Meets the Cognitive and Social Sciences, 155–175. MIT Press. 1

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a thing to me, I would immediately assume he was using the words with an ironic, unconventional meaning. Indeed, higher animals may also fail to present the world correctly, say, whenever they miscategorize the content of their sensations. I remember my mother’s cat once threw herself over a cork on the kitchen floor because it apparently thought the cork was something edible that had been dropped on the floor. As soon as it discovered its mistake, it spat the cork out of its mouth while coughing, hawking, and shaking its head. In such cases, it seems natural to explain animals’ behavior with a reference to a wrong belief. But because our senses occasionally fail to give us true beliefs, it would on this background be unreasonable to demand in general that our sensory beliefs must be justified beyond that these are generally reliable due to natural selection and adaptation of our cognitive faculties. Thus, I do not intend to discuss how philosophers have tried to solve the challenge that the facade example raises for traditional epistemology. Instead, we need to ask ourselves what must apply to having sensory beliefs. Humans and other animals must first be aware of the content of their sense impressions. Then, second, they must be able to recognize that particular content according to what they have already learned. It seems obvious that an organism must be able to be aware of the content of its sensations before it can learn to recognize its reappearance. So we shall say that having a sensory knowledge requires both conditions being fulfilled. Thus, if reliable processes carry out the recognition, an organism has sensory knowledge that is image-based. But if the image is additionally recognized in virtue of the work of a reliable schema of conceptualization, an organism has sensory knowledge that is concept-based. What is important is that neither image-based nor concept-based sensory knowledge needs justification, because natural processes, which are adapted to provide information from the environment, produce such knowledge. However, traditional epistemology presupposes that the justification of a person’s empirical beliefs follows some a priori standards. One is that there must exist some adequate evidence supporting the truth of a given state of belief. A person, who holds beliefs about what he or she experiences, must refer to some other beliefs that may act as evidence for the

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given belief in order for it to be rationally justified. In addition, traditional epistemology assumes that everything a person knows must form a consistent and coherent system of well-separated beliefs and that any belief, which is not consistent with this system of beliefs, shall eventually be rejected. Finally, traditional epistemology considers beliefs as mental presentations of states of affairs that can be articulated in a language. The requirement is that we must be able to judge the numerous beliefs we have acquired to be individually true, and such judgments can take place only if we understand the propositional content of our beliefs, which we can do  only if the content is expressible in language. Hence, the only proper type of knowledge that exists is concerned with propositions. Indeed, some of these a priori presuppositions behind the standard analysis exclude animals from having proper sensory knowledge and thereby ignore that human cognition may contain other more basic types of knowledge than empirical knowledge that can be tracked back to the evolution of hominins or even further. Likewise, traditional epistemology disregards evidence that animals are most likely capable of forming concepts in spite of their lack of language. In general, since we have an overwhelming amount of evidence to attribute sensory and non-sensory knowledge to animals, the ability to articulate that knowledge linguistically should not be seen as a defining feature of knowledge, not even of conceptually based knowledge. As mentioned in the previous chapter, we are often able to visually imagine how to get from one point to another in a city we know well without being able to describe the route in comprehensive linguistic terms. A similar kind of image-based knowledge is probably widespread among animals. This claim excludes the demand that image-based knowledge can be described in linguistic terms; it implies only that acquiring image-based knowledge does not presuppose the existence of this possibility. Nor does concept-based knowledge necessarily have need of the presence of a linguistic capacity of the knowing agent. Higher animals seem to be in a position to develop concepts applying to the content of their sensations. Also embodied knowledge, which is widespread within the animal world, may not be easily expressible in linguistic reports. The acquisition of embodied knowledge such as skills and competences happens via bodily actions and thereby corporeal knowledge becomes embodied. We

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acquire this version of knowledge by doing, not by reflection, and we retrieve it again by repeating the same action. Only some versions of knowledge, such as empirical and theoretical knowledge, exist in virtue of being linguistically expressible, whereas sensory as well as embodied knowledge exist as dispositions for bodily actions. The fact that visually and (to a certain extent) kinesthetically acquired knowledge in humans may partly be articulated in language is not an essential defining characteristic of any of them.

Sensory Knowledge and Belief-acquisition The differences in origin and articulateness between experiential knowledge, on the one hand, and empirical and theoretical knowledge, on the other hand, raise several questions about knowledge in general and about sensory knowledge in particular. For instance: (1) Is it possible to have propositional knowledge that does not involve beliefs; i.e. can an animal acquire an internal state of information whose content does not cause a belief, although the content still counts as a sort of knowledge? (2) Does it make sense to ascribe sensory knowledge to humans if they are unaware of having that version of knowledge? And (3) If both animals and humans can be unaware of their own knowledge, what is it other than awareness that distinguishes knowledge from mere beliefs? To begin, we might recall, Lewis’s claim that we may have propositional  knowledge without beliefs because the timid student may not believe that he knows, when in fact he does. At first sight, Lewis seems to confuse the mental state of knowing something with the state of being aware of being in this mental state. A better way to express the above claim is to say that people may have propositional knowledge, even when they do not hold a belief in the content of this knowledge. In such cases, people are unable to retrieve what they once learned, and it is therefore the student does not believe that he knows, but this does not imply that he does not believe in the content of his knowledge. If we want to argue for the latter conclusion, we must be able to show that having a belief about the same content demands that one is aware of it. One such argument might be that since I can only be aware of this content whenever it

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is consciously present to me, I cannot have beliefs concerning a content about which I am not conscious at that moment. Hence, a person may have propositional knowledge even without belief. Certainly, one may question this argument. Humans do not consciously entertain all their propositional knowledge at once. At any point in our lives, we are not aware of most of what we know. Nonetheless, in common parlance we are still ready to say that we believe or disbelieve this or that in spite of the fact that we are not at that moment aware of what we believe or disbelieve. I know, for instance, that Mozart is a famous composer who was born in Salzburg. It is not often I think about this fact, but it is reasonable to say that I believe that Mozart is a famous composer who was born in Salzburg, even when I do not think of it. In fact, I might believe that Mozart is a famous composer who was born in Vienna, and still not be aware of it. Also in that situation it makes sense to attribute a wrong belief to me but not knowledge regardless of whether I am aware of this belief or not. However, when it comes to sensory knowledge, is it then possible to be unaware of his type of knowledge? Briefly told sensory knowledge is formed in two steps. First, humans receive some sense impressions, which is the result of a reliable process or not. Then we grasp the ideas of this presentation by applying the conceptual knowledge we have obtained earlier. The cognitive process of comprehension is our name for this process of automatically applying the conceptual to the perceptual. I cannot force myself into a state of not seeing a car, when I see one, or into a state of not seeing a human being, when I see one. I cannot, partly because I do not choose to have those particular sense impressions I have (they are not amenable to my will), and being in these sensory states causes me to have particular concept-based knowledge about what I see. So given I am familiar with cars, I cannot avoid seeing a certain orderly set of sensory impressions as a car when I see one in front of me, because my sense impressions and my comprehension of their content automatically cause me to believe that what I see is a car. The second question we have to answer is what makes a mental state a state of knowledge if one might not be aware of that very state. The response is that there is a huge cognitive difference between being aware of the content of one’s sense experience and being aware of having such an experience.

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Furthermore, the awareness of the content presupposes not only that one has a sensory presentation, but also that one has learned to recognize the content as a particular type of idea. Whenever I see a car, I immediately get the idea that it is a car, because the concept of a car has become an integrated part of the knowledge I acquire in such a perceptual situation where I have sense impressions of a car. I cannot see that X is a car unless I already have conceptual knowledge of what it is that makes something be a car. Through learning the concept of a car, the concept has become an integral part of my perceptual grasp of the world due to how my cognitive system classifies it during its processing of sensory information. We are accustomed to almost everything in our daily life environment. This is possible because our sensory knowledge becomes concept-based when we learn which sensory ideas are associated with which concepts. In all those cases, earlier acquired conceptual knowledge acts as unconscious dispositions to identify what we perceive, and we almost never doubt that things are what we experience them to be. As long as we are equipped with the proper conceptual apparatus, our cognitive system automatically presents things according to how we have learned to identify them. Walking down a busy street, we see people, buildings, shops, and cars, because we have learned to distinguish these things, although we usually form no beliefs about these things in this situation. Saying this I mean that we see what happens, but we need not take note of what happens. In other words, we have to be aware of what we see in order to have sensory knowledge, but we need not be aware of the fact that we see it. This leads me to characterize concept-based sensory knowledge as the immediate awareness of the content of one’s actual sensations where the awareness consists of a reliable conceptual recognition that depends on previously received external and internal information. From insight into our own thinking and that of other people, we know that at any moment we are unware of almost all of our knowledge. Non-sensory knowledge is stored in memory, but some of it can be retrieved by a cognitive act that makes use of that memory whenever our environmental stimulation activates our sense organs in a certain way. Non-sensory knowledge consists of non-sensory information concerning conceptual and factual matters. Thus, a large proportion of our cognitive states have an informational content that is not a presentation of learned facts, but consists of learned

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instructions about what we are sensing, how to sense something under given external or internal stimulations, and what to do and how to do it in order to accomplish a certain task. Usually, we are unaware of these instructional schemas as well. It is only when asked about the information we receive that we may become aware that we are sensing, how we do things, or how we react to a certain incident. However, this sort of awareness is impossible without self-reflection. Moreover, if we include so-called tacit knowledge like chicken sexing as sensory knowledge, we may even face sorts of concept-based knowledge whose rational justification is inaccessible to our self-reflection or self-awareness, but where the beliefs are reliable due to the cognitive processes by which this ability of recognition has been developed. Recognition and knowledge by acquaintance are in general reliable. If I say “That’s Joe” when looking at someone, my identification will be highly justified if I have intimate and long established knowledge of Joe, and if I see him in good lighting for a fair amount of time, etc. However, my identification is highly justified, not because I am necessarily able to provide such a justification myself, but because the mechanisms behind my face recognition are reliable, i.e. these mechanisms function according to why they were selected and adapted in the first place. This solution suggests there are different kinds of justifiers: propositional and non-propositional. Propositional justification can be expressed linguistically, while non-­ propositional justifiers cannot be so expressed but can only be pointed to. If I believe something based on what I have seen; therefore, I do not say it is not justified. I say instead that it was justified by my perceptual experience, but not by another proposition, because, given the optimal conditions, perception is in and by itself reliable. Also justified as “true” presents issues because “true” is defined, usually, propositionally. I would not say a perception is “true” or “false;” instead, it is “veridical.” Veridical perceptions lead to true beliefs; hallucinatory or illusory perceptions lead to false beliefs. So even among people, there are many examples of knowledge where beliefs are beyond propositional justification. In all those cases where the informational content of our sensations is due to perceptual competences that evolved before the development of the reflective power of our secondary consciousness, the grasp of this content seems to constitute a

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mental state that cannot be propositionally justified as true. Nevertheless, assuming that all these different types of informational content have something in common, what is it, then, that makes it reasonable to regard them as examples of knowledge distinct from awareness of recognition? The answer, says the naturalist, is that sensory knowledge is reliably acquired. As a natural phenomenon, sensory knowledge has been obtained by certain innate mechanisms to provide fitting sensory information that enables an animal to succeed in its behavior. Therefore, for a naturalist the correct account of reliability has to be in terms of adaptation and natural selection. Hence, sensory knowledge is reliable if, and only if, it is gained by cognitive processes that function as they were adapted to function by natural selection. The sensory system has to work as the adaptation for which it was selected in order to give the organism an informative presentation that is useful for a successful interaction with the environment. This holds for both the physiological processes that generate sense impressions and the cognitive processes of comprehension that make possible the conceptual recognition of the ideas provided by these impressions. This analysis of reliability is reasonable so far. However, it does not help us to explain the epistemic difference between seeing a real barn and a barn façade as long as the sensory belief, one has, is the same in both cases. When Henry crosses from barn country into barn façade country, his cognitive system continues to work flawlessly in the way it was originally adapted to do. But in the first case, it yields knowledge, while in the second case it produces a false belief. Henry makes a mistake in his categorization of the content of his sense impressions. How can we explain this result within the framework of reliability? It is important, I think, to keep in mind that Henry’s miscategorization is the one, which causes him to have a wrong belief. Making the particular categorization of something as a barn is an ability we have learned, whereas the general capacity of categorization is inherited. Therefore, his cognitive system generates a wrong belief when he mistakes fake barns for real barns, because his sensory system provides him with too little sensory information to make a correct distinction. Instead, his cognitive system relies on a reasonable non-sensory belief or expectation (learned by experience) that without changes of the visual sensations,

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things are as they normally are, and sensations of barn facades are sensations of facades of real barns. The concept of a barn originally stems from seeing this kind of thing from the perspective of three dimensions. In almost all sensory contexts in our normal world, the sensory information Henry received from barns, while he drives by, is sufficient for him to categorize correctly that informational content as of barns. Only in fictitious cases is it insufficient.2 However, if Henry wants to be certain, he could stop and get out of his car and walk over to what he assumed to be barns. That would give him additional information by which he would discover that what he had considered to be real barns might really be dummies. We may compare this to the change in history of science, where humans believed that the Sun moves around the Earth, until astronomers gained the belief that the Earth moves around the Sun. Both before and after the Copernican revolution people trusted their senses, but with more sensory information available (such as the change of size of Venus), the astronomers could explain why less sensory information naturally led some people to believe that the Sun revolved around the Earth. Where does this discussion leave us? Apparently, we cannot blame the cognitive mechanisms of conceptualization for not being trustworthy in cases like these since they do not change. The mechanisms of a particular animal are adapted to function successfully with respect to survival and reproduction in most environmental contexts that this particular creature faces in this world. This holds for humans as well. The problem comes acute when the sensory system does not deliver enough sensory information for an unambiguous categorization due to the lack of enough external or internal stimulations. Or due to the lack of any need for the animal to make such discriminations in the world in which it evolved. In a world where making such discriminations was a life or death matter, you would expect natural selection would have chosen organism capable of making this distinction, or the putative species would have died out. The conclusion we are able to draw is that sensory beliefs are reliable, only as far as the cognitive processes that make beliefs available to us operate with a  The example is not completely fictitious. During the WWII the Allies made dummies of airplanes and tanks to fool German scouts or pilots. 2

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sufficient amount of sensory information. In those cases where the sensory information is sparse or insufficient, beliefs based on this information may not fit with further sensory information, in spite of the fact our cognitive processes are functioning as they usually do when we actually do have epistemic success.

The Logical Space of Reason Empiricists hold that while we experience external objects, these objects cause in us via a particular physical medium some mental states called sense impressions. Later empiricists characterize these sense impressions as “sense data.” Sense data were considered to be mind-dependent entities whose existence and properties were directly known to us. We may falsely believe that we are seeing a scarlet pimpernel, but we could not possibly be mistaken that we are seeing something scarlet, because a sensation of scarletness is an incorrigible feature of our subjective experience. Our perception might sometimes be unreliable, but our sense impressions cannot be. Since they had their own properties, sense data were distinct from the external objects which they supposedly “represented,” but which had different properties. Because there is no one-to-one correspondence between the properties of the sense datum and the object, like other representations, sense data might not correctly represent what they allegedly stood for. Sense data were apparently used by the mind in its construction of the external world, but they did not determine, by themselves, the properties of that world. Our immediate experience of them provided us with an incorrigible foundation based on which we perceived physical objects. It might be difficult to see why this empiricist story about perception does not fit into the story I have told until now. Other animals have sensory impressions as well. Some appear to react to the same stimuli that we do and by doing so, we infer that they see the same colors, hear the same sounds, or smell the same odors. So the presence of certain sense impressions, which these animals are adapted to produce given the physical stimuli, may cause them to believe the content of their experience. My dog recalls the sound coming from me handling its food bowl, and when

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it hears this sound, it associates it with being fed and turns up immediately by my side. Apparently, an audial impression appears in the dog’s mind and the recognition of the sound enables it to infer the implication of being fed. Nevertheless, since Wilfrid Sellars gave his seminal criticism of the myth of the given, the empiricists’ sense-data theory has been in ruins. Sellars argued there is no incorrigible foundation of sensations. No knowledge, not even sensory knowledge, can be constructed from sense impressions. Sellars rejects that sense impressions as sense data are given as a self-vindicating and a foundational basis for justifying empirical knowledge. Even sensory knowledge presupposes normative standards and a rational act of thinking that results from upholding these standards. Sellars has inspired several modern philosophers to the extent that they all refuse to ascribe knowledge to animals. Robert Brandon and Michael Williams are well known devotees. Brandon denies that animals have beliefs since they are unable to be participate in the game of asking and giving reasons.3 Michael Williams, being less radical, denies non-human animals knowledge, but not beliefs. Like Brandon, he subscribes to Sellars’s suggestion that knowledge presupposes the cognitive resources require engagement in linguistic communication. As Williams argues, “Epistemic rights and privileges accrue to us in virtue of induction into a linguistic community, with its shared epistemic practices. This is one reason and little children don’t have them. If you can’t learn the game, you don’t get to play.”4 I would grant that Williams’s claim is true when it comes to empirical and theoretical knowledge, but not with respect to sensory knowledge. My criticism of Sellars’s argument is that it contradicts what we know about human evolution.5 Placing sensory knowledge outside the causal structure of the world implies that the evolution of human beings presents a quantum leap—in the sense of a discontinuous, non-natural  See Brandon, R. (1994). Making it Explicit: Reasoning, Representing, and Discursive Commitments. Harvard University Press, p. 214. 4  Williams, M. (2000). Dretske on Epistemic Entitlement. Philosophy and Phenomenological Research, 60(3), 607–612, p. 609. 5  For a detailed criticism of Brandon, Davidson, and Williams’ views, I refer the reader to Kornblith, H. (2002). Knowledge and its Place in Nature. Oxford University Press. 3

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change in the evolutionary development of the human capacity for understanding of the world. It leaves animals, infants, and the mentally retarded on the epistemic sidelines. I hold that sensations produce a form of episodic knowledge on the basis of which other versions of knowledge may be justified. As Sellars correctly argued, sensory states are not belief states. But, in combination with information about its bodily interactions, these sensory states may cause an organism to generate concepts and perhaps beliefs about its environment. My suggestion is this: sensory information in coordination with memory and bodily information enables an organism to acquire sensory knowledge. Before we look closer into this assumption, I will first discuss Sellars’s sophisticated objections in detail. It is part of the myth of the given to assume that non-inferentially known facts do not presuppose “other knowledge of either particular matter of facts or of general truths.”6 In his attack on empiricism and the empirical given, Sellars concedes that we have beliefs that are not acquired by being derived from other beliefs. These non-inferential beliefs are elicited in response to some non-linguistic, non-epistemic (environmental) circumstances. Thus, according to Sellars, there exist non-inferential beliefs and some of these spontaneous beliefs may concern the sensory content of our experiences. He also agrees that the non-inferentially acquired beliefs constitute the final basis of appeal and the ultimate justification for any factual claim. They are decisive by having epistemic authority. What he denies is that particular or general beliefs do not presuppose other beliefs. His argument for this denial is a claim that it is necessary that we understand the propositional content of any non-­ inferentially acquired belief. Moreover, we understand the propositional content of a belief only if we have a concept of what this belief entails; i.e., if we know what it presupposes and what follows from it. As he says, “In characterizing an episode or state as that of knowing, we are not giving an empirical description of that episode or state; we are placing it in the logical space of reasons, of justifying and being able to justify what one says.”7  Sellars, W. (1997[1956]). Empiricism and the Philosophy of Mind. Harvard University Press, pp. 68–69 (sec. 32). Originally printed in H. Feigl and M. Scriven (Eds.), Minnesota Studies in the Philosophy of Science, Vol. 1. 7  Sellars, W. (1997[1956]), p. 76 (sec. 36). 6

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Consequently, being in possession of a concept implies being prepared to commit oneself to inference-based reports. Sellars is very convinced that the use of concepts comes only with the mastery of a language. No language, no concepts. Thus, Sellars maintains that there is a gap between non-epistemic circumstances, in which there are only sensory responses to a physical object, and the epistemic circumstances in which the sensory content can be conceptualized in a language. Knowledge cannot be a pre-linguistic phenomenon because we must be able to understand the propositional content of our beliefs. For Sellars knowledge is not so much about the quality of a given observation as about the ability to grasp it in terms of a linguistic framework and thus to understand the implication of such an observation. Concepts, as Sellars defines them, are what we acquire when, and only when, we learn the use of a language, and until we possess some concepts, we cannot form any beliefs concerning our sensations. Because whenever S experiences x having a red sense content, S must believe that this particular sensation x is red, but S cannot form such a belief unless S possesses the specific linguistic concept by which she can categorize this x as red. In contrast to Sellars I am, in effect, proposing to use the word “concept” in a naturalistic way such that if an organism is able to discriminate between X’s and non-X’s, then it has a concept of X-ness, and that does not require a language. Thus, my naturalism drives me away from Sellars’ commitment to the linguistic approach to knowledge that is so central to analytic philosophy. Forcing the empiricists to come clean, Sellars sets up a trilemma whose alternatives he rightly asserts cannot be upheld all at once:8 A. S senses a red sense content x entails that S non-inferentially believes (knows) that x is red. B. The ability to sense sensory content is unacquired. C. The ability to have classificatory beliefs, i.e. to know facts of the form ‘x is F’ is acquired.

 Sellars, W. (1997[1956]), p. 21 (sec. 6).

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He then addresses how the empiricist can possibly react. First, if the empiricist abandons A, the sensing of sensory contents becomes a non-­ epistemic fact that may be a logically necessary condition for sensory knowledge, although it can never become a logically sufficient condition for such non-inferential knowledge. Second, instead of abandoning A, the empiricist can give up on B, which implies that one must hold that it is through the practice of sensing red, pain, etc. that we acquire the notion of red, pain, etc. Finally, rejecting C entails that the empiricist grants that the existence of universal concepts such as ‘redness’ or ‘painfulness’ is innate. The latter does not sit well with the empiricist tradition. Sellars himself rejects A, and accepts B and C. The sensation of a red sensory content is part of our biological constitution, but how we think of this sense content depends on the linguistic community of which we are a part. His reason for arguing against A is this: it is a necessary condition of any non-inferentially acquired belief that we understand the propositional content of this belief. In other words, we understand the propositional content if we have a concept of what the belief entails and of what entails it: i.e., if we know what it presupposes and what follows from it. Furthermore, the ability to possess such a concept implies the ability to commit to inferentially based observational reports. Because he accepts B, Sellars argues that every non-inferential belief appears in a person’s consciousness as a reaction to some non-linguistic, non-epistemic circumstances. Sellars holds that the tradition of empiricism assumes that in general empirical statements can be stated correctly even though they may not be true. Moreover, he thinks that observation reports about our sense impressions are similar to analytical statements, because the honest assertion of them is both a necessary and sufficient for their truth. Therefore, non-inferentially acquired beliefs about our sense impressions constitute the final court of appeal (the ultimate justification) for any factual claim. Both kinds of sentences, observation reports and analytical statements, have authority. The intrinsic credibility of these statements follows from the fact that either we understand an analytical statement correctly as a type (meaning analytic) or that we correctly understand an observation report as directly presented (tokened) to the mind.

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Sellars, however, rejects the idea that correctness should be understood as following from a linguistic rule.9 He accepts that many concepts are known by ostensive definitions, but he claims that these definitions should not be understood as rules defining the meaning of, for example, “red”, because there is no language in which this rule can be formulated. Ostensive definitions should be understood as practices that are regular but not rule-governed. The view that the authority (or inherent credibility) of non-inferential observation reports rests on non-linguistic, and therefore non-conceptual, attention, which the linguistic utterance then expresses (the ostensive definition), rests precisely on the acceptance of A. Thus, Sellars argues that there is a gap between a non-epistemic circumstance, a sensory response to a physical object, and the sensory content being given epistemic status. Sensory knowledge cannot be a pre-linguistic affair because we must be able to understand the propositional content of the belief. For Sellars, sensory knowledge is not so much about the quality of a given observation as about the ability of expressing it linguistically and thus understanding the observation. An observation report such as “This is red” in the presence of a sensation of red is an expression of observational knowledge only if it is made manifest by the particular disposition to produce similar reports (sentence tokens) in the same or similar circumstances. In order to serve as a basis of knowledge, such non-epistemic dispositions must be reliable, discriminatory and reactive. However, photocells, cameras and parrots also meet this necessary condition. Therefore, according to Sellars, in order for such dispositions to express observational knowledge, we must also require of the report that it is not only reliable, but also that it must be known to be reliable. This last demand makes certain that the cognitive subject (if he/she is asked to do so) can always point to the standard conditions as fulfilled for being disposed to assert the sentence. As a child, we have learned to respond, just as a parrot does, for example, to the sensation of a color by saying, “This is green”. This is a simple case of conditioning that induces a practice. What matters, Sellars holds, is not the reactive disposition, but the ability to consent. The disposition may well be found at a later date than when the child hears the phrase  Sellars, W. (1997[1956]), p. 71f (sec. 32–33).

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‘This is green’. Only when we are able to discuss and assess our own reliability as an observer can we claim to have what Sellars calls “sensory knowledge.” Eventually, there is a transition from the child producing a mere reactive statement to the child who produces a more reflective one, knowing that the sentence “This is green” is the right thing to say in the presence of a green object and not the right thing to say in the presence of a red object. A consequence is that it does not make sense to say that children have sensory knowledge before they are able to engage in a discourse with others about whether or not they are reliable in their reporting. Of course, the requirement of consent excludes animals from having sensory knowledge. It also does so with respect to adults suffering from intellectual defects. Sellars claimed that before we can be rightly said to have sensory knowledge we have the epistemic obligation to being capable of asserting sentences about our impressions. The reliability of our assertion can be justified only on the grounds that we know that we are predisposed to use the term, say, “green” in certain situations and that we are reliable reporters of green things, because we use the term in agreement with the acquired disposition. So reliable means that we will accept an inference from reporting something as green to claiming that this something actually is green, knowing what such a claim might entail with respect to other claims. Notice that Sellars understood the concept of reliability differently from a proper naturalist’s understanding. The naturalist takes an externalist approach by merely demanding that beliefs are reliable because the belief-generating mechanisms work according to an animal’s physiological and cognitive adaptation to its environment. In contrast, Sellars claims that the verbal justification is what makes beliefs reliable, implying that one must know that one is a reliable observer before it makes sense to ascribe knowledge to that subject. So on this point Sellars’s view is in closer accord with the internalist approach to epistemology, namely that one knows that one knows. But how is it possible to have knowledge that the phrase token of “This is green” is a reliable symptom of being predisposed to respond to green things without having any prior knowledge of such facts as one’s sensation is actually a sensation of green and it corresponds to “It’s a phrase token of ‘this is green’”? Sellars’s response is that

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we do not automatically link the concept of green to a sensory experience of something as green, it does not happen as a result of an ostensible rule to use the term “green” that is established because each person realizes what green is, before he or she learns to use the term. We call green things “green,” because we have been socialized by the behavior of others in a linguistic community to do so. The term “green” refers to many sensory experiences, and “green” derives its meaning from the system of color predicates and the concept of color, as it is constituted within a language. Our ability to use color predicates is the result of a long process of concept formation as we learn to master a language. Now, Sellars and like-minded philosophers may have something further in mind when they claim that language is necessary to have knowledge. Humans learn from having experiences as well as from making logical inferences based on these experiences. Knowledge involves not only experiences but also the ability to reason about sensory beliefs. But the capacity of making logical inferences we see only in animals with language. What we see in all other animals, on the other hand, is that their behavior is determined by an expected reward associated with a particular choice. In other words, it is the case with animals that their past experiences entirely condition their present thinking. However, logical reasoning requires that an organism to have learned some rules, as evidenced in its thinking, according to which some conceptual constructions follow from other such constructions. Language not only provides its user with the proper conceptual constructions, but due to its syntax, language also yields the rules for correct inferences. Since rewards are nearly a universal ingredient in all animal cognition experiments, it is very hard to demonstrate whether non-human animals are also able to learn by logical reasoning. Nevertheless, some recent experiments suggest that monkeys are able to make transitive inference without any guidance of award association.10 As the authors explain, “’Transitive inference’ (TI) broadly refers to this non-associative learning ability … and it has been displayed in every vertebrate species in which it  See Jensen, G., Alkan, Y., Ferrara, V.P., & Terrance, H.R. (2019). Reward Associations Do Not Explain Transitive Inference Performance in Monkeys. Science Advance, 2019(5): eaaw2089. 10

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has been tested.” Thus, using a series of sophisticated designed ­experiments with macaque monkeys and a complicated statistical analysis of the data obtained their conclusion is, “This is the first study to test reward-based explanations of TI performance in a paradigm in which subjects have to ignore the experienced magnitude of reward to choose the correct response. Subjects’ success in learning under the reverse reward gradient adds to a growing body of demonstrations that nonhuman animals can solve inference-based problems by a more cognitive means than favoring whichever alternative has the highest experienced value.” With such results in mind, we have no good evidence to claim that logical reasoning presupposes language and therefore that animals are excluded from having even sensory knowledge.

Knowledge Before Language In spite of the fact that many philosophers are sympathetic to Sellars’s analysis I think, as just indicated, it is partly misguided, and that both philosophical arguments and empirical evidence speak against it. The analysis is a symptom of the heavy explanatory burden analytic philosophy has put on the use of language in understanding knowledge and consciousness since the linguistic turn at the beginning the last century. At that time, only a few philosophers realized the impact Darwin’s insights might have on our understanding of the evolution of human cognition. Consequently, later analytic philosophy ignores the fact that animals comprehend their world without being socialized into a linguistic community and therefore being bound by some rational commitments, which follow from being a member of such a community. My disagreement is only limited, but fundamental nevertheless. Thus, I agree with Sellars that his A should be rejected as it stands, but I also reject his C. Of course, the empiricists were wrong when they believed that we sense our sense impressions. However, as the evidence from non-human animals indicates, the ability to form classificatory sensory beliefs is not acquired, but inherited. Before we learn any language, we already have sensory concepts based on the same abilities that we find in higher animals to

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individuate and identify colors, sounds, smells, etc., and thereby discriminate between perceptual objects. For a naturalist, there is a difference between knowing that a certain thing is green and knowing that you are a reliable reporter of the fact that the thing is green. The former is revealed by your behavior, being the same in similar sensory situations, whereas the latter is shown by your tendency to express the same sentence in similar sensory situations. We could also say that the first version of knowledge is associated with first order consciousness, which is merely the capacity of an organism to be aware of things and properties in its environment, about which its sensory apparatus delivers information. In contrast, the second version of knowledge is possible only because humans as self-reflecting beings have secondary consciousness. Humans can think about our own thoughts and therefore we can learn a language. The philosophical argument that pulls the rug out from underneath Sellars’s claim C is as follows: His naturalistic description of how we acquire a disposition to respond to sensory impressions is that as children we are conditioned to associate a sentence such as “This is green” with a particular sense impression. Each time we experience that sensation and hear the sentence “This is green”, the connection between our sensation and the utterance is strengthened, and after a number of times, we become disposed to utter the same sentence under similar circumstances. Thus, Sellars believes that observation reports are non-inferentially generated because, as a result of training, they occur immediately: the disposition to utter a particular observation report is a causal consequence of certain aspects of our environment. Such assertions do not depend on any inference from evidence. We may well grant Sellars’s main conclusion that observation reports are not inferred from other beliefs than those they express, but this does not exclude these beliefs as sensory knowledge from playing a role in causing a disposition to utter such reports. Observation reports are only symptoms of sensory knowledge. In order for a child to be able to learn to associate a certain sense impression with a certain observation report, several capabilities must be already present in that child before the learning of language. The subject must have the capacity to individuate some visual impressions and the

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capacity to remember having sensed similar visual impressions earlier. Likewise, the child must be able to individuate the sound of the linguistic report being uttered and remember how it sounded. In order to establish an inductive association between the visual impressions and the auditory impressions, the child must be able to identify the content of both its visual and auditory impressions. But the ability to identify the content of one’s sense impressions as types is exactly what is needed, according to naturalism, for a child to have concepts. The child is disposed to treat its particular but different sense impressions as exemplifications of different types because of its naturally evolved capacities, and as soon as the cognitive system becomes conditioned to treat a particular sense impression as belonging to a specific type, it acquires a piece of sensory knowledge. Elaborating on this issue, we may add that human beings are able to form pre-linguistic concepts in those cases where sensory impressions appear to us to be natural kinds to which what Nelson Goodman called “projectable predicates” apply. We do not form these kinds of concepts across distinguishable boundaries between different sense impressions. To use Goodman’s famous example, there is no natural concept of “grue.” Goodman called a predicate “projectable” if it is not time-dependent and therefore it can be used in inductive inferences. As Quine puts it, “A projectable predicate is one that is true of all and only the things of a kind.”11 Shortly afterwards he tells us: “Green things, or at least green emeralds, are a kind.” However, non-projectable predicates are linguistically defined rather than having their roots in our sensory experience. Quine thinks that the question of a natural kind becomes a matter of similarity. He argues that similarity cannot be defined in terms of set theory—basically, because everything belongs to many different sets, and therefore we cannot use properties that determine to which sets a thing belongs to define similarity. “The notion of kind and the notion of similarity seemed to be substantially one notion. We further observed that they resist reduction to less dubious notions, as of logic or set theory.”12 But are the concept of similarity and the concept of a kind  Quine, W.V.O. (1970). Natural Kinds. In N.  Rescher et  al.  (Eds.),  Essays in Honor of Carl G. Hempel, 5–23, D. Reidel, p. 6. 12  Quine, W.V.O. (1970), p. 8. 11

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identical? Quine denies that they are, because we cannot use set theory to show that the one is reducible to the other.13 Instead, he argues that the notion of similarity or kind is fundamental to our thinking, and how aliened this notion is to logic and set theory. Quine holds that the use of simple words such as color names and terms of things are acquired through ostensive learning using induction. Our ability to discern similarities and differences is innate, as is the ability to draw inductive inferences. As Quine famously remarked: “Creatures inveterately wrong in their inductions have a pathetic but praiseworthy tendency to die before reproducing their kind.”14 My suggestion is therefore that when an animal is able to discriminate between similarities and differences among its sensory inputs, it may learn to identify various kinds of sensory properties and in this way form naturally established concepts. So when a specific sense impression appears after the animal has acquired such concepts, and its content falls under one of the acquired concepts, this animal is able to produce beliefs and have sensory knowledge. Sellars was partly correct in his rejection of the empiricists’ claim that particular sense impressions in and by themselves entail knowledge. An animal may have sensory inputs without having the ability to be aware of its environment by means of concepts. In these cases, concept-based knowledge does not cause the animal’s behavior, whereas, in my opinion, it would be image-based knowledge that causes its reaction, as a mental consequence of the physical simulations of its sensors. But I think Sellars got it wrong when he argued that observation reports are logically associated with sensory knowledge, because (i) they act as grounds for further reasoning and assessment; (ii) they may themselves be subject to assessment and may require defense. Sellars did not consider a behavioral reaction as in itself an expression of knowledge. A certain response is necessary, but not sufficient, for having observational knowledge. In addition, the reaction requires a linguistically grounded understanding, and with it comes a complex practice of arguments and conclusions. Therefore, it is impossible to see observation as a foundation that empiricists would like. 13 14

 Indeed, it depends on which kind of reduction we are considering.  Quine, W.V.O. (1970), p. 14.

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Contrary to Sellars, but in accord with Quine, I have argued that we can establish a linguistic practice only because we already have sensory concepts.

Empirical Evidence in Support The conclusion of the above discussion is that biological evolution eventually has selected organisms who not only behaviorally react directly to physical stimulations, but also are able to attain images and beliefs and think about what is going on in their habitats and behave accordingly. As an alternative to Sellars’s view, I suggest that our basic sensory concepts and beliefs concerning objects are natural, non-linguistic, epistemic states. They are different from sensory states like sense impressions but partly formed in virtue of an animal’s ability to recognize the content of its sense impressions. I shall also argue that such an ability to recognize this depends on the bodily experience of objects that cause sense impressions. Apparently, the recognition of the content of sense impressions happens in two steps. First, there is the conceptual identification of colors, shapes, sounds, touches, and odors, the natural constitutive and presentational features of our  sensations. But the presence of some of these recognizable features alone does not constitute sensory knowledge of objects. Therefore, and secondly, the conceptual recognition of an object demands that the actual sense impressions combine with the memory of the actional states associated with these sensory features before an organism perceives an object. It is in particular with respect to the process of individuation and identification of objects that bodily experiences and actional states are so important. The color spectrum is continuous, but empirical evidence indicates that human beings already categorize color perception into distinct colors before they learn a language. The boundary between these categories does not change substantially when a child learns a language. Anna Franklin and her co-workers performed a series of experiments in which they were able to show that the various color categories did not change between

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pre-linguistic and post-linguistic toddlers.15 Nor did they find any changes across culture. However, following up on this study, she found that the linguistic representation of color categories partly changed the way we perceive colors; apparently, because the laterality of the categorization of color perception is the right hemisphere in infants, but the left hemisphere in children.16 The conclusion we may draw based on these studies is that the classification of colors into distinct categories is a genetically determined capacity, and an infant before it learns a language can identify the basic categories of colors. Franklin’s observations correspond well with earlier studies indicating that the naming of colors is not arbitrary but has a physiological basis.17 Therefore, it is no surprise to learn that Brent Berlin and Paul Kay found that 98 languages across different societies exhibit strong similarities in semantical color classification.18 These findings accord with recordings that non-human animals, like the great apes, experience colors and demonstrate their pre-linguistic knowledge of colors in taught behavior. It would be very counterintuitive to argue that learning a color language provides humans not only with a semantic understanding of the meaning of color terms, but also enables us to grasp these colors for the first time. Instead of learning two things at once, namely learning to use color terms and learning to identify colors, it has greater explanatory simplicity to argue that while learning the use of color terms, humans pick up only one thing. We are able to learn color terms because we can associate their use with something in our experience that is invariant over time. That is, of course, a pre-linguistic identification of basic colors. The visual system of chimpanzees works not much differently from normal human beings. This is the reason why it has been possible to teach chimpanzees at least 11 different names of  Franklin, A. et al. (2004). Color Term Knowledge Does Not Affect Categorical Perception of Colors in Toddlers. Journal of Experimental Child Psychology, 90(2), 114–141. 16  Franklin, A. et al. (2008). Categorical Perception of Color is Lateralized to the Right Hemisphere in Infants, But to the Left Hemisphere in Adults. Proceedings of the National Academy of Science U. S. A., 105, 3221–3225. 17  See Bornstein, M.H. (1973). Color Vision and Color Naming. Psychological Bulletin, 80, 257–285. 18  Berlin, B., & Kay, P. (1969). Basic Color Terms: Their Universality and Evolution. University of California Press. 15

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various colors.19 Summarizing his results, Tetsuro Matsuzawa concluded, “that there is a common basis of colour classification not only across human cultures but also across primate family lines, Honfinidae and Pongidae.” He then adds, “These experiments suggest that chimpanzees have sufficient cognitive abilities to use arbitrary codes as colour names, and that they are capable of describing the perceptual world by using these codes. It is further suggested that the chimpanzee and the human recognize their world in similar ways by categorizing some of the [same] features.”20 Visual perception is the main sense of normal human beings. The same holds for great apes. But making concepts of external objects out of color experiences requires more than mere sensory impressions. In addition to an object’s colors, vision gives us shapes and how the object is moving, what background it appears against, and other contextual factors. In the case of other people, very often we can see their intent, and it would appear animals can as well. How do we get there? Just as our general knowledge of colors develops very early in our life so does our general knowledge of objects. Here is what one researcher, Elisabeth Spelke, and her team have to say about the maturity of object perception: “Developmental studies of object perception and object-directed action provide evidence that knowledge of objects begins to emerge in the first months of life and that this knowledge has a particular content and organization.”21 As they point out, object perception demands the ability to perceive a bounded figure against an unbounded background, but this is a fascinating achievement because, as they note, “the boundaries, internal unity, and persisting identities of objects are radically underdetermined by the visual information available in the natural scenes.” Both perceivers and objects move around, and because of these activities the appearance of an object, as well as the object itself, may change its shape, color and its spatial relation to the perceiver and other objects. An object  Matsuzawa, T. (1985). Colour Naming and Classification in a Chimpanzee (Pan troglodytes). Journal of Human Evolution, 14(3), 283–291. 20  Matsuzawa, T. (1985). 21  Spelke, E., Vishton, P., & von Hofsten, C. (1995a). Object Perception, Object-directed Action and Physical Knowledge in Infancy. In M.S. Gazzaniga (Ed.), The Cognitive Neurosciences. MIT Press, 165–179, p. 165. 19

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frequently disappears from the perceiver’s visual field, returns into it later, just as it may sometimes be seen far away, and sometimes close up. And the backside of an opaque object is hidden from the perceiver’s eye and the front may be partly concealed by other objects. In spite of all these variations and changes of our visual impressions, we perceive objects to be stable, persisting, and solid. How do animals learn to recognize a ­permanent object if the visual information specifying it is incomplete and changing all the time? Moreover, the object itself, its inherent properties, not its perspectival ones, can change—at least up to a point. What point? When you know that, you have the concept of that thing.

The Sensorimotor Space Obviously, before I can identify some particular sense impressions as a particular instance of seeing an object, I need to have some general knowledge about objects, colors, etc. I must know that there exist objects (just as I later learn that there are different types of objects) and I must know that there are colors. Thus, we should distinguish between general knowledge and particular knowledge. Sensory knowledge is an example of particular knowledge; it is also episodic, because it lasts only as long as the sensory impressions causing a belief last. We may have other particular knowledge that is more permanent. This could be about particular events or specific states-of-affairs I remember. However, general knowledge consists inter alia of knowledge that concerns common features of our environment. General knowledge is knowledge about types and not particulars. As we automatically begin to distinguish our sense impressions into different types, due to our naturally evolved cognitive mechanisms, we learn that there exist things corresponding to these pre-linguistic concepts. This learning process generates the first forms of general knowledge about the world and its sensory properties. So the learning process consists in the accumulation of beliefs about how things are and is determined by how the evolutionary adaptation of our cognitive system presents our physical environment to us. There are physical objects, or green and red physical objects. But what allows us to form such beliefs, since our color sensations of things change depending

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on the time of the day and being exposed to direct or indirect sunlight? Hence, our sense impressions of what we learn to call the “same color” differ even though we believe that we see the same color. Similarly, even though our sense impressions differ, because the intensity of light might change, or the objects move around, or sometimes even disappear only to reappear a moment later, we still believe that we see the same objects. In both cases, the content of our transient impressions becomes classified as (semi)permanent colors and/or (semi)permanent objects and therefore general beliefs about the existence of such a content will be (semi)permanent. How is such a cognitive transition possible? The development of object perception is one of the most experimentally studied human capacities. In the earliest research on concept formation based on his own psychological tests, Jean Piaget suggested that infants initially have no conception of objects as entities independent of their actions. Although the methods behind the psychological experiments have improved, recent research points to essentially the same results. After making a series of experiments on object perception with four-month-old infants and comparing them with the results of other researchers who had performed experiments based on different methodologies, Spelke and coworkers summarized their conclusion. “We suggest that infants’ ability to perceive object identity over occlusion, as assessed in preferential looking tasks, and to track objects visually, as assessed in visual search tasks, do not draw on a single system of knowledge. At present, studies of cognition in infancy appear to be consistent with at least two characterizations of the knowledge underlying visual search.” 22 The two versions of knowledge seem to relate to a philosophical distinction between what we may call synchronous identity and diachronous identity although the authors do not make a distinction in this way. The first one is that “infants’ patterns of visual search may not depend on any knowledge of objects and their motions; developmental change in search patterns may reflect developmental changes in infants’ action  Spelke, E., Kestenbaum, R., Simons, D., & Wein, D. (1995b). Spatiotemporal Continuity, Smoothness of Motion and Object Iidentity in Infancy. British Journal of Developmental Psychology, 13, 113–142, p. 137. See also Spelke, E., Gutheil, G., & van de Valle, G. (1995c). The Development of Object Perception. In Visual Cognition: An Invitation to Cognitive Science, Vol. 2. MIT Press, 297–330. 22

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capacities and skills.”23 This version of knowledge seems to indicate that visual gaze and motor skills working together provide the infants with the first notion of an object, which again helps to develop visual search patterns. As soon as an infant learns to coordinate its perceptual and behavioral systems with respect to objects it can see, touch, grab, suck on, and let go again, evolution has given it the capacity to form a notion of an object, and therefore to acquire general but restricted knowledge of objects. The second form of knowledge is the one the authors demonstrate in their various experiments with infants. In those experiments, infants are supposed to follow an object moving behind some opaque screen, and the experiments show that “infants extrapolate the motions of hidden objects on paths that are continuous and unobstructed, in accord with the continuity principle.”24 In cases where the hidden objects do not follow a linear path, some experiments suggest that a smoothness principle can function as an alternative. Nothing in these experiments indicates that those two cognitive principles are not adapted mechanisms of our perceptual system that help the infant to coordinate its sense impressions with its memory system and its behavioral system. Eventually, given this coordination, an infant learns to identify a moving object over time. Until then you can fool human infants by moving the object behind a screen. Indeed, initially, the child may evince surprise that the object reappears. The working of the same cognitive principles across various species is witness by a similar development in higher animals. A mature cheetah does not stop chasing its prey if it disappears behind another animal for a short while. Although these authors talk about establishing knowledge of physical objects, we should distinguish between conceptual knowledge and general knowledge in spite of the fact that they may be difficult to separate because their function is developed simultaneously under the influence  Spelke, E., Kestenbaum, R., Simons, D., & Wein, D. (1995b), p. 137. They add: “In particular, young infants’ visual search patterns in the experiments of Bower et al. (1971) and Moore et al. (1978) may not depend on a conception of objects as smoothly movable but on a motor skill for tracking smoothly moving objects, developed either over infants’ normal experience with objects or over the course of the initial test trials in which a smoothly moving object appeared repeatedly.” 24  Spelke, E., Kestenbaum, R., Simons, D., & Wein, D. (1995b), p. 138. 23

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of each other. In this process, adapted cognitive schemas operate on sensations, and together with behavior such as reaching and grabbing, help the infant to form a robust concept of objects as concerning everything that is confined, stable, solid, and movable with respect to a visual background. There are things the infant sees such as shadows and light patterns on the floor that she cannot grab, and these she comes to learn are not objects. So seeing is not a sufficient sense for establishing the concept of objecthood. We learn it is real when you can also touch it. At the same time, the infant learns that there are physical objects. Thus, it gains general knowledge of the existence of physical objects, while it acquires conceptual knowledge of what counts to be such objects. The distinction between conceptual knowledge and general knowledge is perhaps blurred in practice as long as we consider the basic knowledge of experience; i.e., the knowledge needed to survive in the natural environment to which a species is adapted. But if we see general knowledge as a form of knowledge the scope of which transcends our immediate experience, and conceptual knowledge as an ability to identify something as of a sort, it makes sense to make such a distinction. What we have said about physical objects presumably also holds for sensory qualities like colors. Species able to distinguish colors have this capacity because they learn as infants to recognize the same color each time they see it. This is all it takes to have a concept. Physiologically, a normal infant is capable of experiencing various colors, but it probably has to see the same color in different lighting and instantiate different hues, before it gets a robust concept of red, green, blue, etc. Here it also seems reasonable to assume that schemas, like the principle of continuity and smoothness, play a role in the formation of color concepts. The same object keeps its color constantly over a certain amount of time, regardless of changing light or of the way in which an infant handles the object. Thus, the infant in this way acquires general knowledge that there are objects that are red, blue, green, etc. Later we shall dwell on general knowledge based on a conscious reflection. Concepts that apply to our immediate experience are unconsciously learned in virtue of the working of some sensorimotor mechanisms in reaction to the sensory inputs. Infants and non-human babies develop

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such concepts as part of their maturation, and likewise the general knowledge they thereby gain is unconsciously learned. The particular knowledge that X is an object, that X is an object of a certain kind, or that X is red, is true for an animal in the sense that this knowledge fits with the actual conditions of environment to which its cognitive capacities are adapted. We shall say of an animal’s sensory knowledge that it is fit if it improves the animal’s ability to live, survive, and pass on its genes to the offspring. Probably for many animals identifying an object type has more to do with odor and smell than vision or sound. Many animals are nocturnal or live underground or in caves. So identifying objects is not identical to seeing them. It may be deadly for an animal if its belief about X does not fit into the environment. Indeed, animals are not conscious of the fact that they are conscious. Yet animals need not be conscious about their sensory knowledge in order for their beliefs to function as knowledge. Even a human infant is not aware of its own beliefs or conceptual capacity until its capacity of self-reflection matures well after infancy. It eventually learns to speak a language, and thereby becomes consciously able to create new concepts not abstracted from its immediate experience. These new concepts enable humans to acquire empirical and theoretical knowledge. However, this ontogenetic development is possible only because the phylogenetic evolution of the cognitive capacities of higher animals happened to arrive at the capacity to acquire concept-­ based knowledge that was shareable, although not linguistically sharable, with other members of the same species. All for the benefit of the individual’s capacity to reproduce.

5 Linking Experiences to the Social World

First, there was the thought, and then the word came. In other words, speech is thinking with other means. In the present chapter, my concern is with the transition from conceptual thinking in animals to linguistic thinking in humans. Language is the link between individual knowledge and social understanding. Language evolved to express our sensorily determined beliefs such that our fellow beings could come to grips with what each of us might be thinking. But before our ancestors gained the ability to create a language, natural selection and adaptation among primates had already evolved complex methods of conveying information about their beliefs ranging from grunts to body language. All animals living in hierarchically structured groups form societies, where a society is a group of individuals bounded together by the coordination of the members’ thoughts and behaviors in virtue of some sort of communication. For the purpose of such a coordination, verbal language has turned out to be evolutionarily a more successful means of communication than any other means. Nonetheless, nonverbal communication among higher

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animals living in social groups, like elephants, dolphins and chimpanzees, is immensely sophisticated.1 Thoughts are subjective in the sense that they are private, but because of our common origin, the content of human sensations is similar in the same experiential situation. In order to express the content of these thoughts, any means of communication must be associated with some form of intersubjective representations of those thoughts, which is accessible to other humans. This is possible due to natural selection. Although sensations are subjective (i.e. private and not directly accessible to others), their biological fitness consists in providing information about the environment, and because of the genetic heritage of this fitness, it is reasonable to assume that these subjective sensations deliver in general the same information to every subject among conspecifics. And because of the genetic heritage of this fitness, the individual has the capacity to produce the same sensations as reactions to the same physical stimulation of its sense organs. Indeed, after a basic language representing the basic ideas had evolved among our predecessors, humans were able to develop complex concepts of an abstract character. Those thoughts would not have emerged had language not assisted its users to develop new categories. Hence, language follows image-based thinking and conceptualized thoughts, but also facilitates an abstract social comprehension of our thinking. The evolution of language extended the range of our thinking many times. Before the first human language could evolve, some cognitive tools had to be in place. A rich conceptual understanding of the environment in which humans lived was mandatory, and the capacity of understanding the intention behind giving expression to oral sounds had to be—not necessarily equally—distributed among individuals. Because different humans attended the same objects, qualities, and events, they more or  An article written by Rachel Newer (2021). “The First ‘Google Translate’ for Elephants Debuts”, Scientific American, June 9, informs about the ethogram, ElephantVoices. She begins by stating: “Elephants possess an incredibly rich repertoire of communication techniques, including hundreds of calls and gestures that convey specific meanings and can change depending on the context. Different elephant populations also exhibit culturally learned behaviors unique to their specific group. Elephant behaviors are so complex, in fact, that even scientists may struggle to keep up with them all.” The digital website ElephantVoices is an attempt to help scientists to improve their understanding of elephants’ communication. 1

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less shared the same conceptual understanding of their physical environment. In addition, most members of a group should be able to bring other members’ attention to focus on something that they had in mind by various forms of communicative behavior. This capacity requires that humans have the ability to imitate others’ sounds and to know the intention behind various gestures. Especially important was understanding the use of pointing gestures to direct conspecific individuals’ attention to something outside their own body. Finally, human cognition had to possess a strong faculty for pattern recognition that allowed pre-linguistic hominins to recall repetitive structures. These assumptions were, as Robbins Burling claims, “as essential when language was first getting started as they are now.”2 As I have argued, like other organisms humans have evolved with the capacity of finding perceptual similarities and differences in their environment. We see different colors because natural selection has given us a physiological ability to discriminate between different electromagnetic wave lengths. The same holds for the other sensory modalities. Whenever we see two particular colors, we are able to judge whether they are similar enough to be regarded identical of sorts. Equipped with memory we recall earlier encounters of the same and different colors. Originally, the capacity of seeing two particular colors as the same color was what gave the organism a concept of colors. From a naturalistic perspective having a concept, as I have suggested, is nothing but an organism’s ability to regularly separate particulars that are similar from particulars that are dissimilar. Identifying two particulars as of one sort is the beginning of conceptual thinking. This merely requires that the neuronal mechanisms behind induction be in place. Thus, language evolved in accord with the comprehension of their environment that our ancestors already possessed; the corresponding terms got their meaning by expressing what they perceived and recalled. However, it is one thing to account for how sensory terms get their meaning; it is quite another thing to explain how we learn the use of such experiential terms. Here I side with Quine in saying that we learn simple  Burling, R. (2005). The Talking Ape. How Language Evolved. Oxford University Press, p. 69.

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words such as color terms, words for behavior or locomotion, and words of visual objects through ostensible learning and the use of induction. Our ability to distinguish similarities and differences is innate; i.e., human’s capacity to make such a distinction has been selected because of survival/reproductive advantages, and the same is true of our ability to draw inductive inferences. If we did not have the capacities for sensory discrimination and inductive inference, we could not get to know anything and much less master a language. Thus, my claim, as argued in this and the following chapter, is that each and every human has the capacity to learn to use terms that directly refer to qualities, behaviors, and visual objects by ostension and induction, because modern humans’ learning of the use of these terms undoubtedly reflects how the reference of these terms was originally established. Moreover, I hold that self-awareness is a precondition for making sense of verbal sounds. The ability to think about our own thoughts is a necessary condition for the evolution of language as we see it today. The ontogenetic mechanisms behind language acquisition mirror the phylogenetic mechanisms that once provided basic language with meaning. In all cases, the meaning of our experiential vocabulary stems from pre-linguistic thoughts about our physical environment.

The Evolution of Language Chapter 3 developed a distinction between ideas, beliefs, and thoughts. I proposed that simple and complex ideas are the content of particular mental presentations, which, if the mental presentation is a sensation, may be an object of image-based thoughts. Furthermore, I suggested that general ideas, in case we again talk about sensations, are the conceptual presentations of this qualitative content, and that such ideas are the objects of concept-based thoughts. A concept-based thought concerning a particular experience is a mental state whose content is the result of conceptually processed sensory information. Later in this chapter, I shall discuss how such thoughts may have both a narrow and a broad content. However, in case an organism grasps its sensations as exemplifying general ideas, it is the same as the organism has concept-based thoughts. Neither an idea nor

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a thought needs to be believed, just as having a belief need not be something one thinks about in order to have it. Therefore, either image-based or concept-based first order thoughts can be objects of second-order thoughts in all cases when we are focusing on first-order thoughts with a sensory or behavioral content. For instance, the object of a mental state might be, while we see a leopard, the combination of the sensory belief “leopard” and the retrieved belief that “it is dangerous,” and the second-order thought would be “a leopard is dangerous.” I shall say that the actual awareness of the conceptually structured content of sense impressions of a leopard is a complex first-order thought. In short, a sensory belief is about conceptually grasped sensory information, or about a general idea, and the awareness of this information is a concept-­based thought.3 We may not be aware of our thoughts, or rather its content, as an awareness of second-order but the thought we are aware of is always a first-order awareness of something. The conceptualized content of our sensory thoughts causes our sensory beliefs or disbeliefs  given our background knowledge. A concept-based thought involving sensory or behavioral information is almost automatically believed in case the sensory information is reliably picked up the moment an animal becomes conceptually aware of the content of this sensory information. However, there may be cases where the context enlightens an animal that its current concept-based thought should not be believed such as cases of deceptive appearance or behavior of other animals. A concept-based thought is a mental state in which an organism tacitly comprehends the content of its sensory presentation on the basis of the perceptual context and its background knowledge.  In the philosophical tradition going back to Frege, we see that the meaning of words is identical to an idea, whereas the sense of a sentence is equivalent to a thought, and the sense of a predication is a concept. Wayne Davis (2003). Meaning, Expression, and Thought. Cambridge: Cambridge University Press, pp. 555 ff. criticizes this assumption as absurd by pointing out that the meaning of a word is a property of that word, and that the sense of a sentence is a property of that sentence. Neither an idea nor a thought, as mental states, can be a property of words or sentences. Instead, he holds, on the one hand, that a property of words and of sentences is that they express ideas and thoughts respectively. On the other hand, Davis thinks that ideas are parts of thoughts, since he regards ideas being equivalent to concepts, and “Thoughts are propositions in the sense in which belief and desire are propositional attitudes … All other propositional attitudes are different relations to thoughts. Thoughts have constituent structure in a literal sense that beliefs and desires do not.” (p. 6). A consequence of Davis’s proposal is that propositions are mental states, which is in alinement with the view displayed here. 3

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Hence, we might well ask, what is the evidence that thoughts predate language and that language evolved as a means of communicating these thoughts? A growing number of linguists and biologists believe that human language did not evolve from animal communication but from animal cognition.4 One of them, Robbins Burling, bluntly states, “We will learn more about the antecedents of language by studying primate minds than by studying primate communication.”5 His argument is that we find many gesture-calls in human beings that are inherited and homologically similar to gesture-calls in non-human animals, something we would not have expected if language had evolved from our ancestors’ gestures, signals, or calls. Moreover, he points out that gesture-calls in human are less culturally determined than words. He also says, “We use words as names for objects, qualities, and actions, and we use these names to call one another’s attention to what we are thinking about.”6 Nevertheless, studies of primates indicate that some alarm-calls exhibit some of the basic mechanisms behind the evolution of language. In spite of the fact that so little evidence exists that can guide us in the search of a proper account, any explanation of the evolution of language must take into consideration that the function of verbal language as a system of communication consists in its coordinating the role of both a speaker and a listener. The latter is just as important as the former. The listener must understand the meaning, which the speaker wants to communicate with spoken sounds, just as the speaker must have a belief that the listener understands the sounds. Indeed, a shared environmental context helps to establish such a common understanding, but that alone would not be enough. If it were, we would be facing Quine’s problem of 4  In de Waal, F. (2016). Are We Smart Enough to Know How Smart Animals Are? Granta Publications, the author remarks, “It is now widely accepted that, even though language assists by providing categories and concepts, it is not the stuff of thoughts”, p. 102. Ib Ulbæk is an early voice in this choir who in his unpublished Ph.D.-thesis Evolution, sprog og kognition (1989) argued that human language evolved from animal thinking and not animal communication. See Ulbæk, I. (1998). The Origin of Language and Cognition. In J.R. Hurford, M. Studdert-Kennedy, & C. Knight (Eds.), Approaches to the Evolution of Language, 30-43. Cambridge University Press. Other early voices are Bickerton, D. (1990). Language and Species. University of Chicago Press, and Pinker, S. (1994). The Language Instinct. New York: Morrow; London: Penguin. 5  Burling, R. (2005), p. 63. 6  Burling, R. (2005), p. 50.

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the underdetermination of reference.7 For instance, his Gavagai thought experiment does not hold due to his misbelief that observation is the only source of fixation of meaning. Presumably, humans have the same pre-­ understanding of their perception grounded in a shared world of experience, because the organization of each individual’s cognition is the result of the same successful adaptation as their common ancestry underwent. So it is clear that the whole rabbit is a better candidate for such a fixation than all the observational alternatives. More importantly therefore is common thoughts. Some linguistic scientists think that language evolved in response to the need for sharing thoughts, rather than to a need to refer to objects. This makes sense, because if our sensory thinking among individuals of a species is similar (which it is due to natural selection and adaptation), the individual is in a much better position to grasp what another intends to express when hearing unfamiliar sounds uttered in the presence of familiar visual cues. Most likely language could evolve because our capacity of sensation and our manner of thinking were very much generically synchronized among our predecessors. The uniformity of sensory knowledge in addition to the physical context enables different individuals to establish inductively a common reference of those words that have direct experiential reference. This aligns with the semantic comprehension of meaning as consisting of sense and reference. The thought characterizes the sense and the object of thought is the reference. Here our experiential knowledge establishes the causal link between a speaker’s intentions and the listener’s grasp of these intentions, thereby creating semantic knowledge. Thus, meaning depends as much on what happens inside our head, as outside of our skull. A likely scenario is that based on an already established complex conceptual system among our forerunners, these individuals improved their capacity of social interaction, and thus their chances of survival as soon as natural selection and adaptation gave them the ability to convey verbally their thoughts to others. The crucial step was apparently naming things that all individuals in a tribe could see, touch, and therefore already  Quine, W.V.O. (1960). Word and Object. MIT Press, pp. 51–57. Indeed Quine’s attempt to avoid reference to sense and meaning and instead offer a stimulus-response model of our linguistic behavior is based on his strong empiricist point of view. Such a behavioristic approach is foreign to naturalistic epistemology and naturalistic semantics since naturalists have no problem with invisible but concrete entities.

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conceptually comprehended. Apparently, much in the same way as when Helen Keller realized that the sign for water, written in her palm, referred to water she felt on her arm. She already had pre-linguistic knowledge of water when she learned to associate water with a sign for water. Pointing, feeling, naming, and induction provided her, as well as the first Homo sapiens, with a small lexicon. Had a given tribe of Homo sapiens not shared a common conceptual system concerning their physical environment and a mutual understanding of each other’s intentions and behavior, the members would not have anticipated that the regular production of the same arbitrary sound had a certain purpose. We have argued that the act of comprehension emerges as induction brings different beliefs or information together. In Keller’s case, it was apparently her recognition of the generic sign as a particular type of action that was brought together with her actual experience of touching something. Comprehension among hominins covers not only an animal’s understanding of its physical environment but also the grasp of its social environment; that is, the behavior of other animals with which it interacts. Because such a great deal of comprehension was already in place a long time before any linguistic system developed, the listener had little difficulty in coming to grips with the referential nature of a particular vocalization and what it was in fact intended to stand for. Of course, language is more than a lexicon of experiences. Our thoughts are not only concerned with particulars we actually perceive, but also with what we remember and anticipate (not mentioning generalization and abstraction). Language is demanded to express thoughts that transcend the actual perception. This requires the development of syntactical rules that are far more complex that simple connectives. Remembering uniformities, regularities, and changes gives rise to different expectations such that the communication of these thoughts requires different expressions for referring to ones thinking of the past, the present, and the future, and for referring to one’s thinking about the actual, the possible, and the unlikely. When all this happened is open for conjectures. My guess is that a good deal of this was already present with the earliest hominins, millennia before the genus homo emerged. Since all known human languages in the world often contain diverse words for the same thing, we can draw the conclusion that it is arbitrary what sound or symbol we use to refer to

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a particular thing. Language is in this sense conventional. A certain number of individuals merely have to agree to a suggested sound or symbol to make it a convention. We also know that modern Homo sapiens is approximately 200,000–300,000 years old and that the Exodus out of Africa happened less than 100,000 years ago. If true, it may seem to indicate that most proto-languages emerged after Homo sapiens sapiens had spread into Asia and Europe. However, another possibility would be that after the development of a proto-language, it began to differentiate into many languages when the Homo sapiens sapiens spread across the African continent and outside Africa. However, one should keep in mind that the Neanderthals, Homo sapiens neaderthalensis, who roomed Europe and parts of Asia hundred thousand of years before modern humans, also carried a variant of the “language” gene FOXP2 and were equipped with a hyoid bone that allows speech production in humans. And if one takes into consideration the relative advanced technology they possessed, it seems impossible not to assume that the development of this technology required a high level of coordination of thoughts and knowledge that came from the use of some form of language. Thus, it seems to me very probable that language use—at a rudimentary level—appeared in our lineage well before the first human of any species. Although a vocabulary is arbitrary and conventional, the manner in which names, verbs, and adjectives assembles into sentences may be less local and more universal, just as Noam Chomsky has proposed. One of his claims is that humans cannot learn a language without some generically inherited structures irrespective of their sociocultural differences. The cognitive linguist, Ib Ulbæk, gives an argument for such a claim: “if the child had only inductive strategies for constructing the rules of language, it would either be stuck in an enormous search space looking for consistent rules, or (perhaps) would come up with a language structure different from its parents. Some prestructuring in the child’s search lightens the burden of induction and explains why parents and children speak the same language after all.”8 In keeping with Chomsky and Ulbæk, one might say that some syntactical rules of language are in part innate. An  Ulbæk, I. (1998), p. 32.

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explanation for this is that, while thinking, a human being is structuring his or her thoughts according to some inborn rules of processing information and it is partly these rules that structure the syntax of all languages.9 However, to the extent to which the rules of language may be partly inborn, they reflect our pre-linguistic habits of thinking, semantic knowledge of a vocabulary is something we acquire entirely through learning. The reason is that the meaning of speech sounds is conventional and each individual has to learn how these sounds are associated within his or her language community to common experiences. Here it all begins with the coordination of knowledge of sensory experience, pointing behavior, sound production, and inductive inferences. These intentional acts secure that vocal sounds express the producer’s thoughts in coordination with the listener’s comprehension in virtue of causing the sounds to refer to objects of his or her thoughts that were also objects for the listener’s thoughts. Eventually, as we shall see, semantic knowledge developed to be more than the inductive recognition of the association between speech sounds and the object they are intentionally denoting. The meaning of well-­ established terms changes as we learn more about the structures of the world. Additional empirical knowledge also generates fresh thinking and therefore the invention of novel vocabularies. But just as our reflection on empirical knowledge influences our vocabulary and rules of language, the reverse process is also common. The use of words makes an influence on our thinking as well.

Becoming Sapiens A Darwinian maintains that our cognitive capacities evolved over eons by natural selection and adaptation. Long before our ancestors separated from the great apes, adaptive selection seems to have installed many of our basic conceptual schemas and dispositions. So some of our basic cognitive mechanisms were already part of our genetic heritage when our  Such a view is the topic of Fodor’s language of thought hypothesis. See Fodor, J. (1975). The Language of Thoughts. Harvard University Press. Because I argue that the conceptual understanding of the environment predates any linguistic representation, I would rather talk about the thought-­ like structure of language instead of the sentence-like structure of thoughts. 9

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predecessors split off from the common ancestors we share with the bonobos and chimpanzees. These animals are our closest relatives among the present living species; our common ancestors divided from one another around 5–7 million years ago. The capacities of perception, memory, imagination, concept-formation, and intentional action are some of the cognitive dispositions we share with them. More specifically, capacities such as color vision, sensing unities and differences, recognizing spatial and temporal identity, perceiving movements, classifying various kinds, feeling empathy, and setting up strategies for action to gain imagined goals are all basic cognitive mechanisms that we find in human beings as well as in bonobos, chimpanzees and other higher animals. In their analysis of whether chimpanzees have a theory of mind, Josep Call and Michael Tomasello conclude that although chimpanzees do not understand false beliefs, based on the result of several experimental studies: [a]ll of the evidence reviewed here suggests that chimpanzees understand both the goals and intentions of others as well as the perception and knowledge of others. Moreover, they understand how these psychological states work together to produce intentional action; that is, they understand others in terms of a relatively coherent perception–goal psychology in which the other acts in a certain way because she perceives the world in a certain way and has certain goals of how she wants the world to be.10

The authors then add that it might be possible that a few other mammals and birds have a similar understanding. Linguists and cognitive scientists can be divided into those who believe that natural selection and adaptation explain the evolution of language and those who consider the rise of language as a side effect of other evolutionary mechanisms such as exaptation.11 Among the first group, some scientists hold that language developed as a means of communication of pre-linguistically evolved categories of thinking, and the closest we can come to discovery of such innate pre-linguistic categories is to focus on  Call, J., & Tomasello, M. (2008). Does the Chimpanzee Have a Theory of Mind? 30 Years After. Trends in Cognitive Science, 12(5), 187–192. 11  Pinker, S., & Bloom, P. (1990). Natural Language and Natural Selection. Behavioral and Brain Science, 13(4), 707–727. 10

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bonobos and chimpanzees. As Ib Ulbæk states in his comments to Steven Pinker and Paul Bloom: The prospect of providing a theoretical, coherent, and plausible account of the origin of language by natural selection is fine if (1) we have as a starting point a complex cognitive ancestor who can map a language onto his conceptual structures, and (2) if we can show how the cognitive mechanism demands certain social structures to communicate in a cognitive way. Then we may hope to be able to give an account of a very stable protolanguage onto which the language module has adapted, thereby becoming a biological structure to be inherited by future generations. 12

In a similar vein, the anthropologist and linguistic scientist Robbins Burling states that his “central argument” regarding the evolution of language: “is that comprehension, rather than production, was the driving force for the evolution of the human ability to use language. To put comprehension first bumps up against a widespread, but barely recognized, bias that usually consigns comprehension to second place.”13 Indeed, the order is far from settled. However, given the fact that language is a presumably beneficial adaptation of human beings and that humans share with chimpanzees many of the same experiential categories and schemas of thought, it is natural to seek an explanation of the origin of language in some selective features that arose in humans after their forebears separated from the chimpanzees. Brian MacWhinney has proposed a set of four such features: bipedalism; dexterity; neoteny, and social bonding.14 Another such precursor feature is having a theory of mind; i.e., the ability of attributing mental states to oneself and others.15 The epistemological  Ulbæk, I. (1990). Why Chimps Matter to Language Origin. Behavioral and Brain Science, 13(4), 762–763. 13  Burling, R. (2005), p. 4. 14  MacWhinney, B. (2008). “Cognitive Precursors to Language.” In O. D. Kimbrough &U. Griebel (Eds.), Evolution of Communicative Flexibility: Complexity, Creativity, and Adaptability in Human and Animal Communication. MIT Press. 15  Higher animals like crows, elephants, dolphins, and chimpanzees seem to have a theory of mind. In a review study, Josep Call and Michael Tomasello writes: “On the 30th anniversary of Premack and Woodruff’s seminal paper asking whether chimpanzees have a theory of mind, we review recent evidence that suggests in many respects they do, whereas in other respects they might not. Specifically, there is solid evidence from several different experimental paradigms that chimpanzees 12

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conclusion that we are to draw from these evolutionary facts is that human language is adapted to a previously established complex of perceptual and behavioral categories. A natural language is sometimes estimated to have evolved between 350,000–150,000 years ago.16 If this is true, it means that a common language evolved roughly during the period our forebears became Homo sapiens sapiens. Another estimate holds that language, as we know it, emerged with what has been called behavioral modernity around 150,000–50,000 years ago.17 Accordingly, Homo sapiens may have evolved from being speechless to be speaking between 200,000–100,000 years understand the goals and intentions of others, as well as the perception and knowledge of others. Nevertheless, despite several seemingly valid attempts, there is currently no evidence that chimpanzees understand false beliefs. Our conclusion for the moment is, thus, that chimpanzees understand others in terms of a perception–goal psychology, as opposed to a full-fledged, human-like belief– desire psychology” (2008), p. 187. 16  The evidence for any such a claim can only be indirectly and very uncertain, since no first proto-­ language remains today. The present estimate stems from a statistic analysis of phonemic evolution where the phonemic diversity between the oldest African languages and some Southeast Asiatic languages are compared. See Perreault, C. and S. Mathew (2012). Dating the Origin of Language Using Phonemic Diversity. PlosOne 27 April, https://doi.org/10.1371/journal.pone.0035289. However, some generic and physiological evidence indicates that not only early Homo sapiens was able to speak a language but that Homo neaderthalensis also had the same capacity. Some anthropologists and neuroscientists even suggest that Homo erectus used a pre-modern language based on studies of their brain size, the interior of their skulls, and the presence of hyoid bones. See Hillert, D.G. (2015). On the Evolving Biology of Language. Frontiers of Psychology. https://doi. org/10.3389/fpsyg.2015.01796. 17  See, for instance, Chomsky, N. (2004). “Language and Mind: Current thoughts on ancient problems”, Part I & II. In L. Jenkins (Ed.), Variation and Universals in Biolinguistics. 379–405. Elsevier; and Chomsky, N. (2005). Three Factors in Language Design. Linguistic Inquiry, 36(1), 1–22. Noam Chomsky imagines that a single mutation in a single individual about 100,000 years ago was enough to create the ability for language proficiency. For him, the language skill consists solely in being able to construct and process recursive data, which is equivalent to counting by constantly adding one to the number one already has, i.e. work with discrete, potentially infinite amounts of data. Admittedly, geneticists have discovered that the FOXP2 protein is important for language learning, as malformation of the FOXP2 gene causes loss of language proficiency, but the same protein is found in mammals as well as songbirds. See Enard, W. et al. (2002). “Molecular evolution of FOXP2, a gene involved in speech and language”. Nature, 418, 22. August, 869–72, p. 870. The protein of man differs from chimpanzee in the substitution of two amino acids, from that of the mouse in substitution of three and from the songbirds of seven amino acids. Such a supposition about a single gene being responsible for our linguistic behavior seems far too simple. It is based solely on a purely cognitivist conception of language, namely that language use and thinking alone function as an algorithmic process. Language involves so many different complex traits that it can hardly be due to a single gene change. Many other cognitive mechanisms need to be in place for a language to emerge, mechanisms that are at least as important to language formation. Understanding is just as important as performing.

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ago. However, none of these suggestions seems to be correct if we count Homo sapiens neanderthalensis and some of their as well as human beings’ predecessors among language or proto-language users. The exact period in which language first appeared does not affect the point of my argument. What matters is that evolutionary reasoning points to the conclusion that the capacity for language is part of our genetic heritage and that language evolved gradually from primates’ conceptual thinking in order to express human thoughts. In my opinion, as I have already argued, it makes sense to say that if an animal has a notion of a type, i.e., has an ability to recognize an individual object as belonging to a certain class of objects, then it has a concept of that object. Equipped with this functional definition of a “concept,” I maintain that animals’ capacity for forming concepts predates the ability among the great apes to distinguish between various kinds of colors, kinds of fruits, and kinds of animals, as well as their ability to count small numbers. All of these forms of perceptual thinking among the great apes find their expression in different behaviors and indicate that our capacity of constructing concepts had developed long before our non-linguistic forebears were set on the trail to become language users. The cognitive development that took place among hominins in virtue of natural selection evolved toward an increasing capacity for abstract thinking in combination with proper language skills. For this process to be successful, the evolution of ordinary language had to adapt to the pre-­ existing natural concepts by which our non-linguistic predecessors already grasped their sensory experience. Hence, the perceptual and behaviorally oriented part of our natural language includes distinctions and classifications, which our non-linguistic ancestors already possessed a long time before the appearance of hominins. Therefore, I think a plausible reconstruction would be that first our distant ancestors among the primates adapted not only physically but also cognitively to cope with their environment, including comprehension of the social order of their own species. It seems likely that in such a social context behavioral commands and warnings would be the leading candidate for our first rudimentary referential expressions based on prevailing beliefs and thoughts. Next, when natural selection physiologically gave Homo sapiens a verbal chance to share their thoughts with their fellow beings, different sounds became

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associated with the already existing categories of perception and schemas of thought. Much later, the development of language under the influence of imagination and high-level social interaction gave us the capability of reasoning about things that were not directly connected to our sensory experience.

Ostension, Induction, and Correlations The positivists were correct in holding that ostensive definitions give us the meaning of singular terms and experiential predicates. Even more importantly, they claimed that we understand such terms by associating them with sensory qualities because humans have the perceptual ability to isolate objects that possess such qualities. However, under the influence of the late Wittgenstein, philosophers of language have more or less accepted that the meaning of a simple term like “red” is not acquired through observation. Their reason for rejecting the positivists’ reliance on ostension has been that it is impossible to discern the common element of red things and thus to understand the property of being red unless we already know which things are red. The set of perceptual experiences arising from the sight of red things does not select itself. In order to arrive at the concept ‘red’, we need a criterion to help us in selecting which things have to be included and which have to be exclude from the set. However, such a criterion is not available, because it presupposes the very notion of redness whose procurement the criterion is supposed to explain. Individual red things become similar to one another as instances of redness only when we know what it means to be red. Indeed, Wittgenstein would not deny that we could explain to a small child the meaning of “red” by pointing to various red objects while saying that these things are red, and by pointing to some non-red objects while emphasizing they are not red. Nevertheless, the act of pointing is rather ambiguous, since it does not signal that it is the color of the object and not the size, shape or position one wants to name. Things are also similar or dissimilar to each other in infinitely many ways. Those things selected, because they are examples of red objects, will also bear other sorts of resemblance to one another. Hence, the argument goes, which of the

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infinitely many properties one points at is indeterminate for the listener. And finally one has to know the intention behind the act of pointing; one already has to know a language game, Wittgenstein would say, in which the act of point has been institutionalized by grasping its significance, before it can be used to pick up the meaning of a term by means of ostension. This argument against the fundamental role of ostension is well known. But that does not prevent one from having serious doubts about its scope. If it is sound, it puts the learner of a first language in a Catch 22-­situation. One has to know the rules of some language game before one can participate in any, but one cannot know any rules until one takes part in at least one language game. How do we break the circle? Though it is correct that things may be similar to one another in many, perhaps even infinitely many ways, that does not establish a claim that there are infinitely, or even merely immensely, many aspects in which things visually resemble each other. For we are not talking about all kinds of abstract or artificial resemblances. We are merely interested in those among all these qualities that reveal themselves in our sense experience. The cognitive mechanisms of humans and the functions of our sense organs, all are adapted to collect information about a particular environment in which hominins evolved. Thus, it is quite doubtful that we are able to characterize the experiential features of an object in countless many ways. Rather we perceive only a limited number of natural qualities such as few basic colors, sizes, shapes, positions, and depths of which animals have obtained knowledge long before we human beings have developed linguistic responses. Moreover, pointing may not be a biologically adapted gesture in contrast to gazing and howling, but it may be more precise in its purpose of aiming at the target. Dogs, elephants, and chimpanzees can learn to respond to human pointing. However, bonobos and chimpanzees kept in captivity point to draw humans’ attention, whereas in the wild these animals never or very rarely do so. Since no changes in the genome exist between individual in the wild and captivity, pointing is an epigenetic phenomenon that depends on environmental variations. Nature has disposed the great apes to catch the attention of other individuals, especially if their access to food depends on these individuals. I suggest that this

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disposition stems from apes and monkeys’ ability to “reach out for” food when as juveniles they wanted to have their share of their mother’s diet. The overt meaning is obvious in those cases, namely drawing the mother’s attention to the object and the infants’ needs for food. Later, if successful, induction then transforms the understanding of this behavior to cases that involve their caretaker. Pointing attempts to direct another individual’s attention to something in the environment whose presence the pointer realizes. The intention behind pointing is either to share common perceptual thoughts with other individuals or to induce new perceptual beliefs into an individual. Thus, we all know red by experience because we are conscious of the color red before we have a term for red. Animals with color vision like ours know what red is because their vision has adapted to discriminate between various wavelengths in form of seeing different colors and to behave accordingly. Human beings have inherited a natural capacity to recognize recurrent patterns of stimulation and to discriminate between them. Even animals much less developed than vertebrates are able to recognize very complex patterns where different sorts of qualities enter into these patterns. Some of those qualities seem to be similar to the ones we are able to recognize. Monkeys, for instance, show their ability to react to different shades of colors when they learn to respond differently to various painted trap doors according to their expectation of finding food behind them or not. Apparently, monkeys and human beings share the same (or at least very similar) quality space of colors; they have the same neurological and behavioral capacity to discriminate between color stimuli and between different shades of them. Hence, colors are for some species a natural, and highly important, quality.18 It seems very likely that what happens, when somebody begins to pick up his or her first words, is that one learns to associate a particular type of sound with your thinking of some naturally given type of sensory stimuli. Experiments with pre-linguistic toddlers strongly support such an  In his book, MacKinnon, J. (1978). The Ape within Us. Collins, the author gives a fascinating description of the orangutans’ long travel between fruit trees that delivered ripe fruits at different times of the year. Their travel is optimal in the sense that they have accurate knowledge of the terrain they inhabit and they have similar knowledge of the different times of the ripening of the fruit—indicated by a change of color. Hence, colors matter.

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interpretation.19 Teaching conditions a correlation between the experience of a certain type of quality and the experience of a certain type of sound by establishing a causal connection between them. Seeing the same colors repeatedly forms our concept of that color and hearing the same sound repeatedly in the context where we see that type of colors, we learn to associate a certain type of sensory quality with a certain type of sound. Such correlations, however, establish the extension of color terms, but not their sense. The sense is the content of the thought we associate with the use of a sound. The thought determines the reference of the sound by fixing that it is the object of one’s thought that is the referent of the sound. However, these correlations form the first steps toward understanding a language. It is not until one eventually comes to a grasp of the correlation between a color term and a certain quality that one begins to understand its linguistic meaning. One has to develop a comprehension of the existence of such correlations before one realizes that the extension of a particular name of a color in a certain language is its meaning. It is through such cognitive processes, it seems, that we learn to master the use of color terms in a correct manner. Only when one can predict, say, which verbal sound another speaker of the same language will apply to a certain color, and which one he would not apply, does one knows the meaning of color terms. Applying verbal sounds more or less flawlessly in discourse with other people, we show knowledge of what these sounds mean. Nevertheless, from these remarks it is a long way back to the positivist doctrine that ostensive definitions would automatically provide us with the meaning of terms concerning simple sensory qualities. The same holds for nouns. The vervet monkey (Chlorocebus pygerythrus, previously Cercopithecus aethiops), for example, has at least three or four non-iconic vocations, which denote “leopard”, “snake”, “eagle”, and

 See Franklin, A. et al (2005). Color Term Knowledge Does Not Affect Categorical Perception of Colors in Toddlers. Journal of Experimental Child Psychology 90(2):114–141; and Franklin, A. et al. (2008). “Categorical Perception of Color is Lateralized to the Right Hemisphere in Infants, But to the Left Hemisphere in Adults.” Proceedings of the National. Academy of. Science. U.S.A., 105, 3221–3225. 19

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“baboon”.20 Such referential calls are learned, I shall propose, whereas signals are innate. Other calls like affective calls, contact calls, and display calls are probably all inherited and are closer to signaling. Undoubtedly, a monkey’s use of its particular form of sound for denoting “leopard”, denoting “snake”, etc. is congenital, but its referential meaning is something the monkey learned by watching other members of the troop while growing up. Vervet monkeys learn to make, as juveniles, the variety of alarm calls from observation of the context alone. Different acoustical sounds become associated with different observable objects, but only after the sounds become meaningful as the individual monkey learns the representational status of each particular sound. Learning its meaning requires that an animal uses its pre-existing conceptions to form a correlation between a type of sound and a type of object. Mere signals, I submit, are not linked to an animal’s conceptual system due to the generic heritage of its meaning. A signal system works to the mutual benefit for the sender as well as the recipient without any further understanding, whereas a call system is mutually beneficial only if it also produces a referential understanding in the recipient. A call can be considered “reliable”, if the call contains conceptual information that is useful to the recipient, regardless of whether the recipient is a relative or an enemy. “Unreliable” calls are information merely for the benefit of the sender, because this information misinforms the recipient. Experimentation with unreliable callers show that vervet monkeys became accustomed to the incorrect calls from a specific individual. As the authors conclude, “Vervet monkeys who had learned to ignore an unreliable leopard alarm call did not later ignore an eagle alarm call, even when the signaller [caller] remained the same. Results suggest that vervets, like humans, process information at a semantic, and not just  Seyfarth, R.M., Cheney, D.L., & Marler, P. (1980). Vervet Monkey Alarm Calls: Semantic Communication in a Free-Ranging Primate. Animal Behaviour, 28(4), 1070–1094. Comparable results have been found among Campbell’s monkeys; see Ouattara, K., Lemasson, A., & Zuberbühler, K. (2009). Generating Meaning With Finite Means in Campbell’s Monkeys. In Proceedings of the National Academy of Sciences, 106(48),: December 7; and among Diana monkeys, Zuberbühler, K. (2000a). Causal Knowledge of Predators’ Behaviour in the Wild Diana Monkeys. Animal Behaviour, 59, 209–220; Zuberbühler, K. (2000b). Causal Cognition in a Non-human Primate: Field Playback Experiments With Diana Monkeys. Cognition, 75, 195–207; and Zuberbühler, K. (2002). A Syntactic Rule in Forest Monkey Communication. Animal Behaviour, 63, 293–299. 20

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an acoustic, level.”21 The benefit of an unreliable call could be the possibility of stealing some food when the remaining group flees into the crown of trees. Unreliable alarm calls seem to indicate that vocal sounds of vervets are connected to the belief states of both the caller and the respondents and not to their sensory states. It is not the sensory state stimulated by the presence of a leopard but its belief state that directly causes the caller to set off the alarm. Likewise, the respondents react to the thought they associated with the sound just like the caller who, in addition, must be able to imagine the reaction of the other members of the troop. Joseph M. Macedonia  and Christopher S. Evans have proposed the term “functional reference” to classify cases like these together with a criterion of production and one of perception.22 The first is that referential signals should exhibit stimulus specificity; the second is that the signal should bring about the same response as the eliciting stimuli even in the absence of supporting contextual cues, i.e. without perceptual contact with any intruder. Based on the research with vervets, I conclude that the referential function of the alarm call works without any direct causal relation to the sensory stimulation that originally produced it, because the content of the thought that also were associated with the sensory state now plays an independent role as the sense of the alarm call, determining its intentional reference. Alarm signaling is a behavioral adaptation through natural selection, and it is only when the acoustically distinct sounds become coupled with a deliberately purposeful behavioral response that a creature begins to have a language. The evolutionary benefit of an alarm call instead of an alarm signal is that the meaning attributed to a call varies according to the animal’s belief, which changes according to the shifting sensory  Cheney, D. L., & Seyfarth, R.M. (1988). Assessment of Meaning and the Detection of Unreliable Signals by Vervet Monkeys. Animal Behaviour, 36(2), 477–486. Elsewhere, I have made a distinction between conceptual presentation and semantic representation such that conceptual presentations are associated with pre-linguistic thoughts, whereas semantic representations are related to linguistic thinking. See Faye, J. (2014). The Nature of Scientific Thinking, Palgrave Macmillan, p. 295n.42 for the experimental evidence in favor of such a distinction. Therefore, in my opinion, an account of the evolution of language has to explain how semantics evolved out of concepts, how language grew out of thinking. Apparently, what happened was that conventional rules of language partly replaced pure biological rules of thinking. 22  Macedonia, J. M., & Evans, C.S. (1993). Variation Among Mammalian Alarm Call Systems and the Problem of Meaning in Animal Signals. Ethology, 93, 177–197. 21

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context. A blackbird has different alarm signals for aerial predators and ground predators but these are not learned. Played back to juveniles in a nest they react immediately by being quiet. When a breeding blackbird catches sight of a cat, or a person disturbs it, it sends out a warning signal without signifying whether “cat” or ‘human” is the reference. However, this does not rule out the possibility that conceptual mastery is present even though it plays no role in signal delivery. It may very well be that blackbirds are able to distinguish a cat from a human every time they see a cat or a human being. Only when an animal is able to interconnect the concept of ‘cat’ with an acoustically specific sound for the cat, an interconnection it has to learn, does the sound refer to a cat. At this point, we can begin to see the first evidence of the basic elements of a linguistic system. In that case, we can talk about an alarm call.

Narrow Content and Broad Content Naturalists hold that there is a fact about what a person S thinks when he utters the sentence “It is raining” in order to express his concept-based thought. We have a mental state that constitutes S’s thought, whose content determines that there is a correct answer as to whether S thinks it is raining or is mere overcast whenever S utters the phrase “It is raining”. A consequence of such a claim seems to be that the content of a particular image-based thought is entirely fixed by the object that causes one to be in this particular state. In this manner, a perceptual state functions as indicating an effect of the object that causes it. We find similar indicators among animals. When a human and a vervet monkey see a leopard in good lighting up close, presumably both are brought into a state of having a sensory image-based thought, which indicates the presence of a leopard. In virtue of being causally correlated with the visual presence of the leopard, the image-based thought indicates its existence in the same way as a properly working thermometer indicates the temperature.23 However, their sensory beliefs caused by their sensory image-based 23  This comparison is due to Fred Dretske. See his Naturalizing the Mind. MIT Press, 1995, pp. 48–50.

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thoughts may be very different. We would expect that a human’s concept-­ based thought in virtue of seeing a leopard might be many times more faceted and complex than a vervet’s concept-based thought, although their sense impression or visual presentation is more or less qualitatively identical. Where the object, the sensory conditions, and the organism’s sensory apparatus determine the sense impression of the organism, what governs its concept-based thought is its sense impression, memory capacity, conceptual sophistication, and background knowledge. Accordingly, I maintain that human sensory image-based thoughts of a leopard are no more complex than those of a vervet. The difference between humans and vervets is that humans’ concept-based thoughts may be much more complex than those of vervets because the content of our thoughts of leopard normally includes conceptions relating this leopard to everything else we know and believe about leopards and the world in which they and we live. The semantic content of our expression ‘leopard’ is therefore much richer than the velvets’ alarm call. The human conception not only reflects the particular sensory image humans have of a leopard, but also what human beings today believe characterizes a leopard. Nevertheless, even though the number of a vervet’s alarm-calls is quite limited, it does not necessarily correspond to its discriminatory capacity. The authors of a recent study indirectly confirm that the vervets’ belief system and conceptual understanding of their environment is much larger than their ability to produce vocal calls: Clearly, the animals have rich [sensory] representations of the world they live in and are able to categorize different predators, members of different social groups, and to recognize unreliable signallers. Yet, their vocal repertoire is rather limited, just as in the case of other animals, such as dogs, which may understand an enormous array of different verbal commands and referents, but whose vocal production is confined to a few call types such as barks and growls.24 (My insertion)

 Price, T. et al. (2015). Vervets Revisited: A Quantitative Analysis of Alarm Call Structure and Context Specificity. Scientific Reports, 5,13220. https://doi.org/10.1038/srep13220. 24

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Moreover, this study also emphasizes that the conceptual content of some of a vervet’s alarm-call depends on the context, such that two calls can be acoustically identical but have different meanings depending on the visual situation in which they are made. A similar use of contextual cues to disambiguate the meaning of identically pronounced words is a common phenomenon among human languages. In general, this indicates that both vervets and humans rely on their image-based thoughts both when they produce vocal sounds and when they as listeners understand their reference or their meaning. Sensory image-based thoughts distinguish themselves from sensory concept-based thoughts, because the content of image-based thoughts correlates with the objects that the sense organs and the brain present to the animal. But a concept-based thought may fail in cases where image-­ based thoughts do not fail. A human being and a vervet monkey both see a leopard because both have the capacity to form a thought of a leopard, because they have this thought due to the evolutionary adaptation of a capacity to conceptualize their sensory states. However, the capacity may malfunction such that a human as well as a vervet can be mistaken in its concept-based thoughts. I shall propose that the requirement for not being wrong in a given context is the condition: (C) An animal A has a sensory concept-based thought with a reliably achieved content ‘p’ if, and only if, (1) p exists in A’s perceptual vicinity; (2) the content ‘p’ is caused by p in the given context (under optimal perceptual conditions and with a perceptual mechanism working properly); and (3) A would apprehend the same content as ‘p’ in all similar contexts in which p is the actual cause of ‘p’.

The optimal conditions mean not only that the concept-based thought with the content ‘p’ is correlated with the existence of p, but also that the thought with this particular content is caused by p. It excludes the thought ‘p’ from being reliably correlated with other than p; for example, with what constitutes p, or with non-separated parts of p. The sensory image-­ based thought that instigates the belief that p acts as an indicator of p, and not of what constitutes p, and not of parts of p, because the perceptual mechanisms behind the sensory state are adapted to have this function given optimal perceptual conditions.

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This account also gives the naturalist an explanation of errors, even though (C) may seem not to allow errors in the circumstances, because A has a thought with the content ‘p’ if, and only if, p exists. The answer is that a particular mental-neural state, a presentation, P, has the function of indicating p because evolution has selected it to indicate p. This explanation applies to sensations, sensory beliefs and sensory thoughts. Each naturally adapted mechanism does not always attain the goal for which it was selected; if it is broken, for example, or if the optimal conditions under which it is adapted to work correctly (“as intended”) are not fulfilled. Thus, the naturalist approach to sensory thinking extends into an evolutionary approach to language. Sensory concept-based thoughts constitute the foundation for the semantic content of some terms regardless of whether they are primates’ alarm-calls or terms referring to basic human perceptual experiences. However, during human evolution our concept-­ based thoughts about the same observational entities have developed such that the content of our thoughts has partly changed or has partly expanded as our knowledge of that particular entity has increased. Therefore, our conception of a leopard is different from that of vervets as is the conception of iron of today’s metallurgist with respect to that of the blacksmith of the Iron Age. Following up on the distinction between concept and language and the assumption that hominins were capable of thinking and reasoning long before the evolution of language, we must consider the issue of how we should specify these thoughts in relation to  linguistic meaning. Nowadays philosophers talk about thoughts as having a narrow content and a broad content. The narrow content is identified only in relation to what happens inside the individual, but the broad content is identified in relation to what happens outside the individual. Thus, the narrow content refers to the sensory-conceptual presentation of which an organism is aware, whereas the broad content also designates parts of the object this sensory awareness does not concern. In this distinction, I think, we find the difference between a conceptual presentation and a semantic representation. The presence of the narrow content is cognitively necessary for us to individuate an object, conceptualize it, and recognize it as an object, an event or a property, which is sensorially presented to us. In contrast, the

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broad content seems to be cognitively necessary for the semantic specification of a term by including some relevant non-sensory beliefs or thoughts about how the world is; in other words, the two sense impressions may be indiscernible, but the beliefs these two impressions produce can be false and true respectively. The classic example is Hilary Putnam’s Twin Earth argument.25 Assume that Alice experiences water here on Earth as we all do, and she knows that water here on Earth consists of H2O. Then she visits her twin sister, Talice, at another planet where everything seems like it is on Earth. However, what she experiences as water on Earth does not exist on Twin Earth, although Alice has similar water-like experiences on Twin Earth. This time her experiences are of twater and not water, because twater consists of XYZ and not H2O. There must be something that Alice and her twin sister Talice share if they agree that ”water” is water at Alice’s home planet and “twater” is twater at Talice’s home planet. What they agree on is that the manifest properties of water and twater are the same. It makes no sensory difference for either Alice or Talice, whether they are on Earth or on Twin Earth. Similarly, Tyler Burge’s counterfactual thought experiment might seem to tell us that the content of a belief is partly dependent on the language community in which we place a given utterance.26 In the actual world, Peter believes he has arthritis (inflammation of the joints) because his thigh hurts (misunderstanding). In the counterfactual world, Peter believes he has arthritis (inflammation of the bones) because he has a painful thigh (correct understanding). In both cases, Peter (A) and Peter (C) are in the same physical-psychological state. But in the actual world, Peter’s belief is false because the content of his thought does not correspond to how the linguistic community defines the word “arthritis,” whereas in the counterfactual world it does. In this case, it could be true that Peter wants to say that he has a sore thigh but simply uses the wrong word. So his belief that his thigh hurts is true; only his belief that the word “arthritis” refers to the cause of a painful thigh is false. Burge’s  See Putnam, H. (1975). The Meaning of ‘Meaning’. Reprinted in K. Gunderson (ed.) Language, Mind, and Knowledge, 131–193. Minnesota University Press. 26  See Burge, T. (1979). Individualism and the Mental. Midwest Studies in Philosophy, 4, 73–121. 25

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argument merely shows that Peter in the actual situation has two beliefs, one of which is true, and the other false, whereas in the counterfactual situation both of Peter’s beliefs are true. Putnam’s example does not face the same shortcoming. It does not demand the use of language. His thought experiment presumably shows: (1) that the meaning of our thoughts does not generally supervene on our inner, or inherent, physical-psychological states; and (2) that the content of our beliefs and other intentional states does not necessarily supervene on internal physical-psychological states. Since content individualizes thoughts, the water thought and the twater thought may not be the same thought, even if Alice is in the same physical-psychological state regardless of she is staying on Earth or on Twin Earth. Consequently, Putnam’s example invites us to make a separation between a narrow content and a broad content of Alice’s thoughts. However, such a distinction requires, so it seems, that we can specify the narrow content of her thought in virtue of two characteristics: (1) A subject’s mental states solely determine the narrow content; and (2) the mental states consist of the extrinsic properties of the physical state of the subject. How should a naturalist react on the distinction between a narrow content and a broad content of our thoughts if he also separates sensory images from sensory beliefs? A sensory belief is about the thought that is caused by what the sensory image presents, and not about this sensory state as such. However, normally we think that things are just as our brain presents them to us. Both Alice and Talice are in a similar sensory state; that is, they have the same sensations, but their sensory belief is apparently different because one concerns water and the other twater. Still not quite. For as long as Alice and Talice know nothing of the constituents of water and twater, they will think of water and twater as the same stuff because this is how their senses present it to them. Therefore, the content of their sensory beliefs are similar. If they respectively know the constituents of water and twater, the content of their non-sensory belief is dissimilar. But if they both know the difference between water and twater and visit each other, the content of their belief would again be similar but change according to whether they stay on the Earth or the Twin Earth. So for a naturalist, the content of their sensory belief does not change— what may change is the non-sensory beliefs about the constituents of

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water and twater, which Alice and Talice associate with their sensory belief, and which depend on the other beliefs they already possess. Hence, their conceptual presentation of the sensory world is the same but their semantic representation of the sensory world differs, since the specification of each of them also includes non-sensory beliefs about the difference between water and twater. Notice that Alice and Talice’s visual agreement relies on external information, namely that the manifest properties of water and twater are the same, because Alice and Talice are in the same sensory states. How Alice and Talice see water and twater depends just as much on the properties of water and twater as on the neuronal structure of the sense organs and brain. Assume Alice and Talice are adapted to experiencing their respective environment by natural selection, in addition to the assumption that they cannot visually distinguish water from twater, those two assumptions imply that some common properties of water and twater produce a similar visual sensation in both of them. Indeed, we can have some beliefs, even though they refer to nothing external to the subject who has those beliefs. It may be beliefs that I exist, that I am in pain, that Pegasus does not exist, and that one plus two is equal to a prime number. Therefore, the external-internal distinction seems irrelevant to the distinction we are considering. What is important is the distinction between sensory and non-sensory beliefs. Our sensory beliefs stem from reliably acquired sensory information, regardless of whether our sensations concern internal or external states of affairs with respect to our body. Sensory beliefs have a content as they function as an expression of a conceptual comprehension of sense impressions. Thus, we should keep the content of sensory beliefs apart from the content of non-­sensory beliefs. Thus, a vervet monkey and a human being, due to their evolutionary proximity, have a sensory belief with almost identical content whenever they see a leopard, but their non-sensory beliefs about the leopard may differ with respect to their content. In the case of the vervet monkey, its non-sensory beliefs may be rather limited depending on how many non-­ sensory beliefs it may be able to remember from earlier experiences. This could be a belief, for instance, that a leopard is dangerous and should be avoided. A knowledge each young vervet monkey has once learned from seeing the behavior of older, more experienced individuals. For human

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beings the distinction between sensory and non-sensory belief is essential because we have beliefs about objects we can see existing simultaneously with beliefs about invisible aspects of these visible objects, aspects to which we have actually or perhaps even in principle no sensory access. Thus, non-sensory beliefs result from the naturally evolved ability of human beings to present their environment conceptually in non-­ perceptual categories. The need for expressing these thoughts publically was presumably a determining force in the evolution of language. Assume Alice truly believes that water is H2O, and Talice truly believes that twater is XYZ. Assume also that each has a sensory belief similar to the other when they see water and twater respectively. What then does the term “water” and “twater” refer to in their respective languages? In other words, what is the linguistic meaning of the two terms? Likewise, what is the reference of the vervet monkey’s leopard alarm call “chirps” and the English term “leopard”? An appropriate naturalist answer seems to be that the users’ intention determines the reference and their intention is partly determined by their knowledge. If one argues that these sounds refer to the same, because they intentionally refer to what you see, it means that “water” and “twater” have the same linguistic meaning, and that “chirps” and “leopard” have the same linguistic meaning. In contrast, if one argues that they intentionally refer to two different things, since they do not refer to what you see, at least not only so, though we may not even know that there is an invisible difference, then they have a different linguistic meaning. The problem with the intentional reference of “chirps” is that although younger vervets learned from older members of the troop that “chirps” stands for “leopard”, the use of that vocal sound is not conventional in the way that we usually think the term “leopard” is. Rather the sound “chirps” has been selected by natural selection to denote a particular conceptually grasped part of the content of their sensations, whereas “leopard” has its meaning as a result of artificial conventions. However, as we shall see in the next chapter, the conventionality of human sensory language may not be as obvious as people usually claim. Clearly, human knowledge of leopards vastly exceeds that of a vervet, but most of this knowledge concerns more abstract or unobservable features. It goes without saying that vervets may have sensory established

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knowledge about the leopard’s behavior that we don’t have. However, imagine a jaguar released into the territory of a troop of vervet monkeys. Most likely they will use the same alarm call “chirps” when they see the jaguar. This does not imply that they cannot see a difference, but in case they cannot, they will just believe that jaguars and leopards are identical just as Alice and Talice believe that “water” and “twater” is the same before they know anything about atoms and molecules. Nor does it imply that “chrips” does not mean leopard. If they cannot perceptually distinguish a leopard and jaguar, the alarm call still means leopard because this is the evolutionarily connected meaning.27 The vervets are only mistaken in their sensory belief. If they can experience a difference, it seems to show that the intentional function of the alarm-call is the same, regardless of whether the vervet sees a leopard or a jaguar, and this is what matters. The alarm call may now function as a generic term “a predator”, just as “fish” does in English and thereby gets an additional meaning. Such a functional extension of a term also happens among humans depending whenever they see something new sufficiently similar to something they already know. Nevertheless, one could argue quite reasonably that there is a difference between the ability of conceptual categorization of invisibles and the ability to manage categorical perception. The former is intentionally driven and has in it an essentially conventional element, whereas the latter is the product of evolutionary adaptation. Therefore, a vervet cannot have a generic concept of a predator because establishing such a concept requires too many non-sensory beliefs. Even if it can see a difference between leopards and jaguars, the difference is not functionally important to have two different calls. In general, sensory knowledge is partly determined by the organism’s external circumstances and its previous (historically determined) interactions with the environment to which it is adapted. In the case of humans, such an interaction has eventually produced a huge amount of knowledge about the external world that cannot be reduced to knowledge of sensory states.

 This is its proper function as Millikan calls it. See Millikan, R.G. (1989). Biosemantics. Journal of Philosophy, 86,281–297.

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Meaning just ain’t in our head, as Putnam reminds us.28 Unless, I would add, if one thinks of meaning as a mental program that identifies the referent. We can agree with Putnam and still think that the meaning-­ determining thoughts and desires are in our head. Sensory and desires determine the pre-linguistic meaning of our most basic empirical expressions in virtue of fixing the reference of these terms to objects or features presented by our sensory states. The more non-sensory thoughts we justifiably add to our knowledge about those sensory objects or features, the more changes will happen to the semantic content that we associate with the use of these terms. Eventually this provides these terms with a full linguistic meaning. A specification of the content of thoughts and desires is one that describes what this content informs us about. Regardless of whether we consider thoughts to be caused by sensory or non-sensory states, their content is identical to a description of the sensory properties associated with these particular states. We can describe our sensory states by referring to well-known external or internal factors that help to individuate the content presented to us. It is pointless to argue that, in principle, we can be unaware of these external or internal factors. The content of our belief cannot consist of a relation between a conceptual account of a sensory presentation and something completely unknown to us. The conclusion is that the dual distinction between the narrow and the broad content of our thoughts  reflects a pre-linguistic meaning and a post-­ linguistic meaning, since the content of our sensory beliefs always depends on those entities or phenomena our thoughts concern. No belief has intrinsic properties but only extrinsic ones that individuate them. Putnam’s caution that meaning is not in our head presupposes a distinction between sense and meaning. The sense of a term denoting a sensory object can then be associated with the content of a sensory belief that causally determines the word’s reference and thereby provides it with a meaning. The content of such a belief comes from a relational specification of its conceptual role. The naturalistic approach advocated here holds that the extension changes with knowledge because the intention changes. First, “water” refers to the empirical features that make us individuate something as water. These features function as criteria for  Putnam, H. (1973). Meaning and Reference. The Journal of Philosophy, 79(19), 699–711.

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determining the word’s reference, and these criteria help to determine the extension of the word “water.” But as humans discover that water consists of a chemical element, H2O, our beliefs about water grow, and the criteria for determining the word’s extension expand with our knowledge of H2O. Thus, once the linguistic meaning of “water” and “twater” would have been the same, but after the discovery that water consists of H2O and twater of XZY, their linguistic meaning separated. Now the new knowledge concerning water became a part of the defining characteristics of water. Studies of vervet monkeys show that their vocal repertoire is very small compared to the amount of knowledge they have of the external world and the social order among them. Other studies of Campbell monkeys show that they added a suffix to their alarm-calls to indicate specific threats and thereby change the linguistic meaning of the alarm call. For instance, “krak” means a leopard is present, while “krak-oo” indicates unspecified danger, such as a falling branch or another troop of monkeys encroaching on the caller’s territory. Diana monkeys living in the same areas have learned to react to this vocal difference by matching it with their own belief system.29 The finding hints at a universal system of communication among some monkeys that includes some of the basic mechanisms of human language. From this point, however, it is still a long way both physiologically and mentally before the appearance of a modern human language with its open-ended syntax and symbolic qualities. Our closest relatives are chimpanzees and bonobos who have a sophisticated system of thoughts about their physical environment, about the behavior needed to uphold their living and the social structure around them. Although they can learn to master several hundred pictograms, which presupposes a rich understanding of the sensory world in which they live, they are still largely bounded to here and now in their thinking.30

 Coye, C., Ouattara, K., Zuberbühler, K., & Lemasson, A. (2015). Suffixation Influences Receivers’ Behaviour in Non-human Primates. Proceedings of the Royal Society B, https://doi. org/10.1098/rspb.2015.0265. 30  de Waal, F. (2016), p. 107 presents a similar view. 29

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Shared Intentions We saw above that Call and Tomasello had no problem in ascribing intentions to chimpanzees and even an ability to recognize other chimpanzees’ intentions. But Tomasello refuses to accept that they are able to share common intentions and therefore that they can cooperate. Instead, he holds that “Based on much research reported here, the critical difference now seems to be that humans not only understand others as intentional agents but also put their heads together with others in acts of shared intentionality, including everything from concrete acts of collaborative problem solving to complex cultural institutions.”31 Others interpret the data differently, and some even claim that the comparative studies between chimpanzee and children sometimes relied on incomparable set-­ ups that make any assessment misleading.32 A position similar to the one Tomasello holds can be found among some linguists. The two Danish linguists, Peter Harder and Peter Widell, argue that the crucial leap to linguistic meaning does not come via increased experiential content, but via the social contract established around meanings and exchange of meaning.33 They believe that the willingness to cooperate and the interest in sharing the world of thought is a key prerequisite for language. In non-human nature, it does not make sense to act declaratively because there is no interest in sharing thoughts— just as animals have little interest in sharing food. I am skeptical of this negative view of animal cooperation. As far as I understand, there is little evidence for such a bold claim. Among bonobos and chimpanzees, scientists have found many examples of cooperation and shared intentions. Of course, private intentions, knowledge and goals among non-human animals are communicated from one individual  Tomasello, M. (2014). A Natural History of Human Thinking. Harvard University Press, pp. ix–x.  de Waal, F. (2016), p. 192. 33  Harder, P., & Widell, P. (2019). Formal Semantics and Functional Semantics. In K. R. Christensen, H. Jørgensen, & J. Wood (eds.), The Sign of the V: Papers in Honour of Sten Vikner, pp. 735–757. Århus: AULibrary Scholarly Publishing Services. https://doi.org/10.7146/aul.348. See also Harder, P. (2010). Meaning in Mind and Society: A Functional Contribution to the Social Turn in Cognitive Linguistics.De Gruyter. 31 32

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to another not by language, but by various sounds, bodily gestures and other behavioral signs.34 Gradually, individuals became able to learn to align their interests for the common good and communicate their intentions back to the others. Not only do I think that the observed behavior among some animals might be interpreted as examples of shared intentions, I really believe that this is the best explanation as far as it is simpler and more in the line with an evolution without discontinuity between human and non-human animals. Scientists have reported coordinated actions and cooperation among, say, chimpanzees, orcas, humpback whales, and ravens. Chimpanzees participate in highly coordinated battues on colobus monkeys in which they take on different roles. Afterwards only those who participated in the ambush share the game, while the highest ranked members of the troop have to wait if some parts are leftovers.35 Orcas have learned to help one another in creating a unison wave to wash a seal off an ice floe.36 A small group of humpback whale hunting a school of fish coordinate their behavior as the leading whale blows a bubble net that encircles the fish, while the other whales from beneath within this rather small circle force the fish to the surface, where all the whales are able to catch them with their giant mouths.37 Likewise, it has been reported that a pair of ravens was able to use the shape and the glass façade of two buildings to hunt  A recent experiment made by Marno, H. et al. (2022). Learning from Communication Versus Observation in Great Apes. Scientific Reports, 12, 2917, https://www.nature.com/articles/ s41598-022-07053-2, shows that just like human infants tend to interpret the information communicated to them by others as being relevant to them and worth acquiring, the great apes seem to have a similar tendency of understanding communicated information to be relevant to them. “As in human communication, there is evidence that under certain circumstances great apes can also produce and react to ostensive cues as signals of communicative intentions. For example, while eye-­ contact can be a sign of potential threat or attack in the animal kingdom, apes seem to use eye-­ contact also as an expression of their intention to communicate with others” (My emphasizes). Not only are the great apes sensitive to communicative cues as eye contact, but this study reveals the great apes also seem to have a preference for learning through communication. 35  Boesch, C., & Boesch-Achermann, H. (2000). The Chimpanzees of the Taï Forest: Behavioural Ecology and Evolution. Oxford University Press. 36  Visser, I. et al. (2008). Antarctic Peninsula Killer Whales (Orcinus Orca) Hunt Seals and Penguin on Floating Ice. Marine Mammal Science, 24, 225–234. 37  Friedlaender, A. et  al. (2011). Underwater Components of Humpback Whale Bubble-net Feeding Behavior. Behaviour, 148(5–6), 575–602; and Hain, J.H.W et al. (1982). Feeding Behavior of the Humpback Whale, Megaptera Novaeangliae, in the Western North Atlantic. Fishery Bulletin, 80, 259–268. 34

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down crossbills. The male chased the crossbill and the female cut off the escape route.38 All these cases of observed cooperation are learned behavior, and belong to a hunting culture, which is found only in small groups among the respective populations. Also it is worth pointing out that the shared intentions of these animals operate with a focus on short-term effects, and one may doubt that they can co-ordinate cooperative intentions with respect to behavior with no immediate impact on their survival. At this point one may introduce a distinction between shared purposes and joint purposes.39 The characteristic of a joint coordination of thoughts is that the other’s experience co-determines one’s own experience, whereas a shared coordination is purely beneficial for oneself. For example participating in, rather than opting out, of a coordinated hunt may be an advantage for oneself, because it gives a larger share of the prey. In joint coordination part of the reward is that the common dividend gets bigger, regardless of whether or not one gets more for oneself. My immediate reaction to such a distinction is that talk about joint intentions in the sense of common benefits without personal gains make sense only after we have established a linguistic community. Unless, of course, the example under discussion is a case of genetically determined altruism. The joint unifying of intentions is achieved only through socialization once we have established different linguistic norms and rules of behavior by which to live. Consequently, I maintain that without the evolution of a symbolic language, one that is not entirely context-dependent, the extension of the ability to coordinate long-term actions that we find among humans would have been severely limited. Such coordination could not be based on any advanced abstract thinking, until the ability to communicate one’s intentions in terms of abstract thinking has evolved. From a certain moment in time, the evolution of thoughts and the evolution of a symbolic language went into a mutually beneficial feedback loop. A capacity of further abstract thinking selected for a capacity of expressing this thinking in a less context-dependent language, and as a capacity of less context-dependent language evolved, this selected for the evolution of a capacity of thinking in more abstract concepts.  Marzluff, J., & Angell T.(2012). Gifts of the Crow. Free Press, pp. 75–76.  A suggestion made by Peter Harder in a private communication.

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Thus, I hold that the evolution of human language required a continuous adaptation of four basic cognitive features we find in rudimentary form among primates: self-awareness, a theory of other minds, an augmentation of the biological rules of thinking with some conventional rules of language, and a capacity of contemplating the past in order to imagine and improve the future. In contrast to Tomasello, and Harder and Widell, I don’t think that the lack of a symbolic language among non-human animals is due to their lack of cooperation and shared intentions. Natural selection, even without a symbolic language, is sufficient to establish these social features. What is much more important is that a symbolic language, and only a symbolic language, enables the speaker to communicate about things that are not immediately present such as invisible things, past and future things, and possible and necessary events. The less context-dependent a language is, the better it is to convey such abstract thinking. Just think of mathematics, or take a tenseless natural language in comparison to a tensed natural language. Regarding non-human animals, very few empirical studies have disclosed that their thinking is occupied with something that is not immediate in space and time to this thinking. In my view, the evolutionary benefit of self-awareness is its function as a cognitive feedback mechanism such that we can learn without the use of simple induction. It enables us to reflect upon our own thinking and thereby partly complement the inborn rules of thinking with conventional rules of a symbolic language. Similarly, linguistic communication requires not only awareness of one’s own belief but also the comprehension of beliefs of others. Self-awareness helps us, based on our memory, to reflect upon intentions and possible behavioral tactics and strategies. Presumably, during the evolution of hominins an increasing selective pressure emerged to be able to communicate a growing amount of beliefs, feelings and imaginations that transcended space and time. Once the necessary physiological features had evolved, these beliefs and feelings, together with intentions and imaginations, guided our predecessors in devising a symbolic language from the rudiments of coordinating vocal utterances with sensory presentations. This development of a language with intentionally established rules enabled the transition from animals having merely individual knowledge to people who shared the ability to acquire abstract, social knowledge.

6 Self-awareness, Language, and Empirical Knowledge

The naturalist perspective on knowledge and language presented here opposes the idealistic presumption in much of twentieth century philosophy according to which ordinary language determines the transcendental conditions for the possibility of human knowledge. The linguistic turn at the beginning of the last century meant that philosophers assume that language is the constitutive factor of thinking and reasoning. In contrast, as an evolutionary naturalist I regard the categories of perception and cognitive schemas to have evolved as cognitive adaptations to sensory information. Non-linguistic animals have highly sophisticated knowledge of the environment depending on the fitness of their cognitive faculties. However, knowledge of higher animals may be divided between experiential knowledge and empirical knowledge even though empirical knowledge relies on experiential knowledge. The main difference, I would say, is that experiential knowledge is individually acquired, whereas empirical knowledge is socially learned. Apparently, some species like apes and monkeys use their own animal language in the form of gestures, signs and calls to teach their offspring, but the most obvious way they impart knowledge to their offspring is through imitation. One thing that is definitely innate is imitative behavior. The baby monkey learns much of what © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. Faye, The Biological and Social Dimensions of Human Knowledge, https://doi.org/10.1007/978-3-031-39137-8_6

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to do by imitating its parents, or other members of the group. It is clear to see why evolution would have selected such a behavioral tendency. Nevertheless, it must have been a considerably further advantage if animals living in groups were able to coordinate their behavior and to teach their knowledge and feelings to other members of the group not only by imitation but also by understanding overtly expressed signs by which they could communicate their internal mental states. Hence, an evolutionary naturalist holds that human language evolves as a means to communicate our mental states. Indeed, much has changed during the transformation of hominins. Perhaps what mostly marks humans from the great apes is the amount of insight into other minds, the extent of self-awareness, and the ability of verbal communication. Undoubtedly, the great apes (as well as monkeys, elephants, etc.) have some amount of insight into the consciousness of other conspecifics in the sense that they can identify conceptually some of their feelings and thoughts just as they can recognize similar psychological states in themselves. However, a matured self-awareness and a capacity of expressing feelings and thoughts in language seem to be necessary for epistemic commitments and justification with respect to empirical knowledge of humans. Experiential knowledge is not challenged at the same level. This sort of cognition merely requires that an organism is conscious of what happens in and around its own body. The benefit of this capacity does not demand that an organism is aware of its own awareness or aware that conspecifics have the same capacities. It does not presuppose the existence of an intersubjective agreement. Only empirical and theoretical knowledge require that, as we shall argue in what follows. Thus, we can express the task before us by saying it is to give a naturalistic account of the cognitive evolution from experiential to empirical knowledge. The capability of having empirical knowledge is basically language-driven, whereas the capability of having experiential knowledge is basically gene-driven. This transition requires an explanation. I argue that the evolution of language had a huge influence on human knowledge such that much of our experiential knowledge transformed into empirical knowledge. This transformation was made possible by the fact that our resources of pre-linguistic concepts, which structure almost all

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sensory beliefs, were enormously supplemented by linguistically defined concepts structuring non-sensory beliefs. Originally, knowledge about the external and internal world was an individually grown property and not collectively established. Experiential knowledge is primarily information that benefits the individual organism in its struggle for survival. Later, when hominins began to reflect upon their experiential knowledge and exchange their thoughts with others, their understanding became more abstract and theoretical in the attempt to grasp the world beyond the use of immediate sensory categories, and simultaneously the demand for stronger requirements to counter cognitive errors emerged. We need agreement and social commitments only in cases where new beliefs supersede areas of sensations to which we are not solely physiologically adapted. The transition from experiential knowledge to empirical knowledge is also a change from mainly non-propositional knowledge to mainly propositional knowledge. Successful adaptive information-gathering processes shape sensory and embodied knowledge consisting of acquired images and beliefs. Evolutionary pressure has selected these processes not on the basis of epistemic norms but by their function of keeping the proprietor alive. But when evolution gave humans the capacity to communicate by uttering sounds with conventionally established meanings, norms of communication were added to our naturally established expectations regarding the use of language as well as the justification of knowledge claims. The present chapter argues for the following assertions. First, I contend that even though self-awareness is necessary for the evolution of language, the ability to use language correctly is an example of embodied knowledge. Second, I maintain intersubjective agreements and corrections govern the establishment of the linguistic norms that determine how we use language. Third, I hold that the purpose of using language for communication is to share our knowledge with others and thereby engage with others in a cooperative endeavor. Finally, I characterize empirical knowledge as a mixture of sensory and reflective thinking made possible by inductive inference, conscious abstraction from sensations, and a constructive use of language to express new beliefs formed by these reflections. Spoken language evolved as a more efficient tool for communicating our sensory and behavioral thoughts than the gestures and sounds of our

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predecessors. Surely when we began abstracting from the present moment, remembering past experiences and inductively inferring assumptions about future experiences, that was when we really needed language. Thereby, as a side effect, evolution gave us an instrument to articulate new concepts, not directly associated with our immediate sensations of the present moment. These amendments to our experiential concepts enabled humans to acquire knowledge of natural and social phenomena that non-human animals were not able to obtain. The spoken language began its evolution as means of expressing experiential thoughts, but eventually it became “das bildende Organ des Gedanken” to use an old phrase of Wilhelm von Humboldt.

Speaking as Embodied Knowledge The evolution of language adds new dimensions to our ancestral knowledge. Knowledge evolves from resting on a primarily biological basis belonging to individuals to being erected also on a social foundation shared among humans as a public property of society. As a biological property, experiential knowledge comprises an integral part of various sorts of non-propositional and propositional comprehension of our environment. Before the evolution of language, natural selection supplied first primates, and later hominins, with cognitive schemas that organize their beliefs into various modes of comprehension. These schemas of understanding control various sorts of embodied knowledge essential to survival. For instance, such schemas provided us with experiential understanding in which information based on visual, tactile, and kinesthetic sensations blend into a continuous space-time comprehension of the content of our perceptions. Schemas also connect events causally whenever we see that one type of event regularly follows an adjacent type of event. Still others bring sensory images and behavioral information together into imaginative understanding in which we visualize possible experiential situations to guide us in reaching a particular goal or avoiding undesirable outcomes. Likewise, beliefs about feelings and purposes of others require a schematized comprehension that we may call intentional

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understanding. In this case, the relevant schemas allow us to grasp a certain behavior as an expression of intentional driven action. A fifth variant of embodied cognition is instrumental understanding where certain cognitive schemas in humans and some other animals bring experiential knowledge into collaboration in order to handle physical things such as toys, tools, and instruments. Finally, evolution also gave humans linguistic skills consisting of cognitive schemas that organize semantic information such that series of vocal sounds can encode our experiential classification. These schemas make possible linguistic understanding, whenever we have learned to put meaningful sounds together to form words and sentences and to use them to express our thoughts. Though Wittgenstein argued that speaking a language is comparable to playing a game, we need not be conscious about the rules and, in fact, we certainly are not. So following them habitually exhibits a form of embodied knowledge. Inductive learning imprints these so-called rules onto the individual mind. The key to most behavior here, both for the infant learning language and for the species, is imitative behavior. One individual animal makes a particular vocal cry in certain circumstances; the others copy that individual, and so on. Multiply that over thousands of generations and you have a community speaking a language. Thus, linguistic rules are nothing but internalized regular social behavior. The instructions of cognitive schemas make syntactic and semantic regularities possible, but like other forms of embodied understanding, most people are unable to specify the content of these regularities. Linguistic understanding is not something we share with other animals. Nevertheless, the knowledge required to comprehend language is still grounded in our ability to conceptualize our environment, which we have in common with some other non-human creatures, as well as our ability to form reliable beliefs about our own thoughts. First of all speaking a language is a practical skill made available to a linguistic community for a communicative practice in the form of linguistic norms and rules. In and of itself speaking correctly is a kind of embodied knowledge whose function is to communicate our thoughts and feelings to other people. Linguistic understanding requires a certain proportion of an awareness of other minds as well as self-awareness. Unless an animal lives in a social

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group there is no need for alarm calls, and living in social groups seems to select for the evolution of the ability to “read” the minds of others from their posture, behavior, and sounds. With such a capacity, an individual can acquire knowledge of the mood of other individuals. However, this evolution from alarm call to human language also presupposes the existence of a certain amount of self-awareness; i.e., an awareness of one’s own thoughts. Before advanced human languages could evolve, hominins had to be able to recognize, i.e., to individuate, and to identify their own sensations and thoughts. The awareness of our own and other minds seems to explain why the evolution of language became possible. Learning a language requires social understanding. It seems likely that the ontogenetic development of our native language skills mirrors the phylogenetic development of any language. Prior to learning the common use of a language, causal conditioning helps a child to learn to respond with a particular sound whenever it is in a particular belief state. The conditioning sets up a psychological disposition to vocalize the same sort of sounds that the child actually hears produced by its parents in the presence of some other sort of sensations. For instance, the child hears the sound “cow”, while it is having the sensory experience of a cow or a picture of a cow. The cognitive process of conditioning brings about the correlations between a child’s recognition of a  particular type of belief, a cow-belief, and its recognition of a  particular type of sound, the phonetic sound “cow”. Some cognitive mechanism then causally connects these correlations with the social feedback the child receives. This is probably how learning any native language begins, helped along by the infant’s seemingly innate drive to imitate the adults around her or him. The correlation is the result of a natural process of learning by conditioning carried out by innate cognitive mechanisms such as those generating the infant’s natural imitation behavior. However, two important factors are missing before a child can learn a language. The more mature child must be able to recognize that the particular sounds stand for something, that besides its regularity, the correlation conveys a meaning to the sound. Such a recognition demands both the attentiveness of other beings’ intentions in using a particular sound and that of the particular thing in one’s own experience is associated with the use of the sound. In other words, learning a language became possible only after

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hominins developed a capacity of grasping other hominins’ intentions as well as a capacity of grasping their own mental states. The prerequisites for speaking a language, as an example of embodied understanding, lie in human beings’ evolutionary adaptation to the physical and social environment in which they live. However, the conventionality of the rules of language, which is partly a product of our imagination and self-consciousness, also puts humans into a situation where the increase of their empirical knowledge becomes socially possible.

Speaker Meaning Determines Word Meaning In order to understand the evolution of language from the calls of animals to human speech, I shall draw upon Wayne Davis’s expression theory of meaning.1 The theory is associated with Paul Grice in particular and sometimes called intention-based semantics.2 The roots of this theory reach back to Aristotle and John Locke; but the theory itself has been in discredit during most of the twentieth century. However, Davis wants to rehabilitate this old theory for good reasons. As he explains, “The best way to do this, I believe, is to carry out the Gricean program, explaining what it is for words to have meaning in terms of speaker meaning and what it is for a speaker to mean something in terms of intention.”3 Nevertheless, Davis also thinks that the Gricean program is flawed in one important respect. The speaker’s intentions, according to Paul Grice, are audience-oriented in the sense that the meaning associated with the speaker’s expression is an action intending to produce a response in an audience. This makes it a good theory of communication but not a reasonable one for meaning and expression. However Davis believes, correctly I think, that communication should be defined in terms of meaning, sense and reference in terms of expression, and expression in terms of intention. An expression is an intentionally produced indication of one’s  Davis, W.A. (2003). Meaning, Expression, and Thought. Cambridge University Press.  Grice, P, (1989). Studies in the Way of Words. Harvard University Press. The book contains some of his most important papers on meaning first published at the end of the 1960s. 3  Davis, W.A. (2003), p. 1. 1 2

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being in a mental state. Moreover, the mental state in question is a particular kind of mental presentation in the form of an idea or a thought, where an idea is defined by Davis as a thought or a part of a thought. From what we have just said, intention becomes the most central part of Davis’ expression theory of meaning. We may say that an intention is a mental state the function of which is to initiate the act of realizing a certain goal. This requires being aware of the content of one’s thoughts. You cannot intend not to run over the cat on the road, unless you pay attention to the content of your perception and to the content of your wishes of not killing the cat. Similarly, you cannot intend to say that there is a cat on the road if you are not aware of the content of your perception and you desire to make such a statement. Davis rejects parts of the Gricean program because “it led, among other things, to difficulties with linguistic units below the level of the sentence, and to the problematic doctrine that word meaning must be defined in terms of sentence meaning.”4 Indeed, it is impossible to imagine how the evolution of language could get off the ground if words get their meaning from sentences. How could language develop if the meaning of a word was irrelevant to the meaning of the other words in the context in which it is uttered? Only by considering the context in which a word is said can we possibly comprehend what is meant (intended a la Grice) by uttering the word. Already Gottlob Frege opposed the idea that goes back to John Locke that words get their meaning in isolation. Since then there has been an almost unanimously acceptance among philosophers of language that the smallest semantic unity is the sentence. Little did they care that sentences are already complex linguistic structures, which must have evolved from less complex structures. However, my approach to the function of ideas and thoughts in this work is more in the tradition of Locke than Frege. I have indicated that sensory terms get their meaning from the sensory thoughts being associated with them. Let me explain why I think so.  Davis, W.A. (2003), p. 9. A little later, he adds, “Our ability to define word meaning independent of sentence meaning will enable us to account for the compositionality and productivity of meaning. The meaning of a sentence is determined recursively by the conventions pairing word structures with idea structures, and by the basic conventions pairing the words in the sentence with ideas” (p. 10). 4

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First, it is difficult to see how speaking a language can be a form of embodied understanding unless our sensory thoughts determine the meaning of our most basic experiential terms. If you do not know the meaning of at least some sensory terms independently of their function in sentences, it is not clear how one can construct a sentence by giving the sensory terms a function without tacitly knowing their sense already. In order for us to produce a coherent sentence that expresses our intentions, we must have the skills to recognize the grammatical category of each word of the sentence in order to get it right and which allows others to understand our intentions. We must be capable to put words into the correct combination to form a syntactically understandable sentence. Furthermore, if we want to say, “The leaves are green”, it seems to require that we have prior knowledge of the meaning of “leaves” and “green” to be able to pick them from our active vocabulary and combine them to a meaningful statement. How else can we be sure that “leaves” and “green” in combination with “are” express our intentions? According to Frege, the meaning of a sentence is identical with its truth conditions. But knowing what are the truth conditions does not happen automatically, we have to work for this to happen. We must know the meaning of a sentence before we can establish its truth conditions. A sentence acquires its truth conditions when we are able to establish a descriptive convention that correlates a certain combination of words with a certain type of states of affairs in the world.5 Hence, according to this conventionalist view, we must be able to identify independently of each other the meaning of a sentence and the type of situation that would make sentences of this type true. However, the problem with the conventionalist view about truth conditions and meaning is that descriptive conventions may change. Moreover, conventionalism assumes that the establishment of all descriptive correlations between sentences and reality is conventional. In this respect, the conventionalist view is not in agreement with the naturalist approach I defend here because I hold that descriptive conventions cover only non-sensory terms. It is difficult to imagine that linguistic expressions 5  See Austin, J.L. (1950). Truth. Reprinted in G. Pitcher (Ed.), Truth. Prentice-Hall, 18–31. In Faye, J. (2016) Experience and Beyond. Palgrave Macmillan, I have a discussion of the implications of Austin’s theory of truth, pp. 168 ff.

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were not originally evolutionarily selected to vocalize experientially acquired beliefs, images, emotions and feelings. These beliefs, images, emotions and feelings gave sense to those expressions and thereby established their reference. This analysis implies that declarative sentences about sensory and behavioral matters are causally, not conventionally, correlated with experientially accessible states of affairs via our sensations, feelings and impressions. Not until after the correlation and the meaning of such expressions came into existence would it make sense to talk about the conditions under which they are true or not. Their truth conditions depend on the meaning of the words in the sentence, not vice versa Second, the connection between concept and word is inexplicable unless we follow a Lockean approach. I have argued that animals have concepts as soon as they recognize a certain thing or a certain attribute as of a certain type whenever they sense a particular to be like other particulars they have experienced before. Primates (and other animals as well) know their own conspecifics from other animals, they have learned to read each other’s behavior, they distinguish between various types of animals, and attributes, like colors, are separated into distinct categories. Apparently, primates master a rich repertoire of concepts corresponding to the exercising of individual thoughts as soon as they experience what causes the activation of their senses. Their thinking makes use of these thoughts, but before we have a language, it seems necessary that some cognitive mechanisms have to encode each of these possible thoughts into words. Returning to the speaker’s meaning, Davis defines it as follows: “S means that p if and only if S directly expresses the belief that p.”6 It is the speaker’s meaning that defines word meaning. Speaker meaning and word meaning are forms of semantic meaning. In addition, semantic meaning should be distinguished from evidential meaning because semantic meaning depends on intention and intelligent actions, whereas evidential meaning does not. Evidential meaning is the core notion that defines speaker meaning. In Davis’s own words, “we shall eventually define word meaning in terms of speaker meaning, and speaker meaning  Davis, W.A. (2003), p. 12.

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in terms of evidential meaning.”7 However, in my opinion, we should distinguish evidential meaning from conceptual meaning that together determines the speaker’s meaning. When a Diana-monkey sees a leopard, it has a mental presentation of a leopard that indicates the presence of a leopard. This is the evidential meaning. However, before the monkey’s call expresses a belief caused by this mental presentation of a leopard, it must already possess an idea of what a leopard looks like. The call is not about this particular leopard but about any leopard. In other words, the meaning of the monkey’s call (speaker meaning) does not only depend on the mental presentation of a particular leopard (evidential meaning) but also on the conceptual knowledge the monkey has gained by remembering the similarities of this sensory presentation to the presentations caused by other leopards (conceptual meaning). This double origin of speaker meaning allows us to explain how calls, expressions and words connect to the concepts of pre-linguistic animals.

The Rise of Linguistic Conventions It is common among linguists and cognitive scientists to maintain the hypothesis that the uniqueness of verbal language in relation to animal communication lies in its recursive function.8 A sequence of words can be combined into nested hierarchical structures of sentences. One would therefore imagine that if human linguistic representations reflect an original structure of human thought, it implies that human thoughts are different from other primates’ thoughts in virtue of having the capacity of iterating information to form nested beliefs. However, the assumption that recursion is unique to human thought seems to be refuted by the empirical evidence. Using a set of non-verbal tests, Stephen Ferrigno and coworkers show that 50 U.S. preschoolers and 37 adult Tsimane’ villagers from Bolivia, who had no schooling in  Davis, W.A. (2003), p. 20.  A typical example is Noam Chomsky. His main contention is that recursiveness is a linguistic property of all human languages such that the amount of syntactical information that might be expressed in a particular sentence is unlimited, and the number of possible sentences is infinite. 7 8

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math or reading, were able to recognize recursive symbol sequences.9 Surprisingly, however, a similar capacity was found among rhesus monkeys. Although they needed some more training than the humans, two out of three rhesus monkeys were able to display recursive learning and one of the two was able to outperform many of the preschoolers and villagers by constructing novel recursive sequences. These experimental results are so fresh that they lack corroboration by other experiments. Nevertheless, assuming that they are confirmed, these results imply that the last citadel in the defense of the distinctiveness of human thoughts is about to fall. The capacity of recursive thinking is something were share with other primates, as also bonobos, like Kanzi, seem to demonstrate by their ability to combine lexigrams to express their feelings and thoughts. That said, it is also true that, as alarm calls evolved into languages, the ability of communicating beliefs, feelings, and intensions to others improved dramatically. In this process, the evolution of self-awareness and the awareness of others’ mind played a significant role in addition to the automatic coordination of our linguistic behavior. The linguistic coordination is already an important causal factor in establishing a convention on which the caller and the hearer can rely to the mutual benefit of both animals. We may expect that every individual took part in a big imitation game at the dawn of human language, just as the child starts out automatically to imitate his or her parents. Linguistic conventions, as Ruth Millikan argues, “are ‘leader-follower’ conventions. A speaker, the leader, automatically reveals which precedents she is proposing as soon as

 Ferrigno, S., Cheyette,  S.C., Piantadosi, S.T., & Cantlon, J.F. (2020). Recursive Sequence Generation in Monkeys, Children, U.S. adults, and Native Amazonians. Science Advances. Published online June 26, 2020. https://doi.org/10.1126/sciadv.aaz1002. These observations are in agreement with other observations concerning the syntactic understanding of bonobos. “The bonobo decoded the syntactic device of word recursion with higher accuracy than the child; however, the child tended to do better than the bonobo on the conjunctive, a structure that places a greater burden on short-term memory.” Savage-Rumbaugh, E.S. et  al. (1993). Language Comprehension in Ape and Child. (Monographs of the Society for Research in Child Development 58:3–4, Serial No. 233), p. v. 9

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she speaks.”10 But if these imitations of the speaker are to be consistent by carrying the same meaning repeatedly, the sounds of the imitator have to conform to the speaker’s meaning, and in order to achieve this goal, the sounds of the imitator have to be causally coordinated with something more than the repetition of the speaker’s oral behavior. For this to happen, and in order to refer to the same object of belief, the sounds of the imitator have to be causally correlated with the same pre-linguistic sensory thoughts as the ones of the speaker. The occasion for such a coordination occurs only when the leader and the follower are placed in the same experiential context. Whenever it is impossible to correlate phonetic sounds with common sensory thoughts, humans need other ways to establish a convention to coordinate possible thoughts as in those cases where uttered sounds do not refer to something we can see, and about which we have no direct sensory beliefs. Merely the awareness of a particular sound and having ability to learn its possible meaning by inductive inference would produce endless failures in cases where no experiential beliefs are available. Such errors would be significantly minimized in case the ability to correlate an uttered sound with a non-sensory belief includes insight into the speaker’s mind as well as the imitators’ own mind, because thereby the imitators can easily grasp whether their oral behavior is in accord with the speaker’s meaning and uniform with respect to their own internal states. Thus, I suggest that the millennia of evolutionary history have selected in favor of self-awareness as a shortcut to enumerative inductive inferences as a way of learning with respect to our own thoughts such that as animals we can reliably and almost immediately realize our failures and successes. Learning by straight enumerative induction is usually too cumbersome with respect to learning a huge amount of information in a very short time, if this information concerns things we cannot experience.  Millikan, R.G. (2008). The Difference of Some Consequence between Conventions and Rules, Topoi, 27, 87–99, p. 88. Millikan rejects Lewis’s characterization of conventions in the sense that he holds that conventions has to be regularity followed by all members of a group, whereas she, rightly I think, argues that “Speakers and hearers may have quite different sets of linguistic conventions in their repertoires so long there is some overlap” (p. 88). She also notes, in opposition to Lewis, that “leader-follower” conventions survive only if their repetition helps both parts to coordinate successfully their mutual behavior more often than it produces failures. 10

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The reason why language is so effective is, of course, because we can encode thoughts into it; that is, using sentences to express these thoughts (and then linking sentences to spoken and written texts of unlimited scope.) Macaques have only single-word utterances for eagle, snake, and leopard. These words correspond to children’s holophrases such as “food”, “up”, “woof ”, which then adults close to the children complete as part of their own understanding. Single-word phrases are highly context-bound and potentially ambiguous as when the child gets porridge for “food,” but wants ice cream. As the child grows to use multiple-word phrases, the dependency of meaning on context decreases and the definiteness increases. Without sentence-structured languages in which different words have different functions, it would be difficult to speak about the past, future and hypothetical states.11 As the natural capability of thinking among hominins (just by reliving past events) was far more advanced in comparison to their capacity of expressing these thoughts, it is likely that there has been a strong evolutionary pressure to adapt to any improvement of the latter capacity in the form of such a sentential structure. Still, it has been suggested that evolution blocks language: releasing information for non-selfish reasons is loss of personal fitness.12 Perception and other cognitive abilities that solely serve the individual are beneficial to it unless the “establishment costs” are too high. The claim is that language is dysfunctional in the first place, because information delivery by language is altruistic and thus is not an evolutionarily stable strategy. Language can therefore only come into play when there is an environment where evolutionary pressure selects for altruism. The evolution of language requires mutual altruism among the members of a group. However, altruism is not evolutionarily inexplicable; William D.  Hamilton gave an explanation in terms of kin selection. 13 Social behavior, like linguistic altruism, could be favored in two ways. First, there exists a strong genetic kin recognition among hominins (and many  The most complete demonstration of the need of a language with a sentential structure is to be found in Bickerton, D. (1981). Roots of Language. New edition 2016. Language Science Press, pp. 231 ff. 12  Ib Ulbæk, among others, points to this fact in his 1989-thesis Evolution, sprog og kognition. 13  Hamilton, W.D.   (1964). The Genetical Evolution of Social Behaviour, I & II. Journal of Theoretical Biology, 7(1), 1–52. 11

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other animals) in order to avoid interbreeding such that offspring, and other family members, would benefit from altruistic behavior including the conveyance of shared linguistic information. The use of language then is an example of inclusive fitness. Moreover, even without kin ­recognition, linguistic behavior as well as other social behaviors can emerge by kin selection in the demographic conditions of viscous populations. In such cases, animals live together in small groups, which exhibit special proximity and limited dispersal. Typically, participants of such social groups share a recent common origin. A possible way to dismiss this hypothesis would be to deny that kin recognition plays any significant role in the evolution of language. It could be argued that if the early hominin groups were sufficiently related by kinship to develop languages, then the same would apply to the great apes.14 There has to be substantial differences between the great apes and hominins that can explain why language was a huge evolutionary advantage for hominins, and kinship is not one of them. However, evolution is not deterministic like classical physics. A zillion accidental happenings can be bumps in the road that send evolution off in new directions that might not have happened otherwise. A genetic transposition, for example, that might make the development of a larynx possible. Nonetheless, altruism is common among animals that live together in social groups. Undoubtedly, kinship drives communication among these animals. Social insects have astonishing forms of communication that could have evolved only because of kinship relations. So altruism and communication are related to kinship and inclusive fitness. Also there is a difference between the altruistic alarm calls of, say, monkeys or prairie dogs and singing birds. The male’s song aims to attract females and mark territory and can be seen as a classic case of an adaptation enhancing the individual’s fitness. The alarm calls are more ambiguous because they expose the caller to danger, thereby decreasing in individual fitness, but increases the possibility of saving the offspring, thereby ensuring the survival of the genes. That alarm calls can also benefit unrelated individuals is then a non-adaptive consequence that does not reduce the chances of survival sufficiently to remove the overall benefit of alarming. 14

 Ib Ulbæk presents this argument in a private communication.

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At this point, one might add that linguistic communication is very different from all these sorts of animal communication. Human language is conventional, symbolic and not related to specific contexts like alarm calls. Therefore, this difference may be due to a difference between the great apes and hominins in terms of social structure and the possibility of having mutual altruism. As long as we merely consider the social structure of primates as hierarchically organized with an alpha male or a female at the top, it may be difficult to understand how primates as a social group could benefit from the evolution of language. The point is that the social ordering must be such that all members of the society must be more or less equally adept at using a language. So the above objection misses an important point. While kin recognition is presumably both a necessary and sufficient factor in the evolution of altruism, it is a necessary factor only in the evolution of language. Other factors may have played a formative role too. Climate changes have certainly forced our distant predecessors to adjust to new habitats, from deep forest to vast grassland, which might have required not only a restructuring of how they are socially organized but also new cognitive skills that would help them to solve new challenges. In such a changing environment, mutual collaboration may be strengthened by an ability to communicate thoughts and personal knowledge that each individual may already have, like memories, practical experiences, and expectations based on these remembrances. But sharing practical experiences and expectations among a group of conspecifics by the use of language demands an ability to consciously recognize that one has these memories and expectations. What groups of hominins obtained under these changing environmental conditions was self-awareness and the capacity of abstract thinking, which the great apes presumably have to a much lesser degree. In my opinion, the great apes do not have a highly complex language because they lack any developed self-reflection and therefore lack the capacity of abstract thinking that comes with it. The conventionality of language would not be possible without an ability to reflect on one’s own thinking, and consciously to focus one’s thinking on one’s previous thoughts and perhaps correct them with respect to one’s beliefs about the intensions of others. The conventionality of language consists in intentionally establishing a common awareness

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among a potential group of users that an arbitrary sound has a particular linguistic function. The intelligent bonobo, Kanzi, understands many spoken English words and sentences. He also learned to communicate using lexigrams on a keyboard such that he could express his wishes and thoughts. Lexigrams are conventional, of course, but the meaning associated with them is of human origin.15 However, Kanzi would not have been able to learn to understand human language or lexigrams did he not have the cognitive capacity to grasp word-referential relations and syntactic structures. He learned their meaning initially by watching how his mother used the keyboard and later based on his trainer’s approval or disproval. Creating arbitrary lexigrams to encode particular beliefs demands abstract thinking, and there is no reason to believe that Kanzi could have produced such lexigrams himself. Therefore I think it is wrong to assume that our common ancestors were cognitive developed to such an extent that the missing feature of the evolution of language was bipedalism. “The onset of speech is linked to the appearance of fully adapted bipedalism, which necessitated reorientation of the laryngeal tract and made closure of the soft palate possible.”16 Indeed, Kanzi could not have responded to the spoken English sentences or learned to communicate his wishes and thoughts unless he had knowledge of referential purposes of the English words or lexigrams and the individual meaning of both words and lexigrams. Such a knowledge presupposes that he has a fair amount of understanding of what goes on in the world as well as inside his own consciousness. But one should note that his understanding of English sentences and his lexigraphic communication contained no words or lexigrams for abstractions. The spoken English words denote objects and behavior that were all observable, and the lexigrams Kanzi used all refer to visible objects or behavior.17 It is known that zoo-housed chimpanzees and orangutans are able to produce novel vocal signals to get their caregivers’ attention. A new study  Savage-Rumbaugh, E. Sue et al. (1993) is the first extensive description of her and her colleagues’ comparative study of a bonobo’s and a child’s language skills. Both were exposed to the same 660 novel sentences. Many later studies of language skills in bonobos and children confirm these findings. 16  Savage-Rumbaugh, E.S. et al. (1993), pp. v–vi. 17  See Savage-Rumbaugh, E.S. et al. (1993), pp. 112 ff. 15

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shows that gorillas similarly can manufacture a species-atypical sound to seek human attention in the presence of both food and keeper rather than in the presence of either food or the caregiver alone.18 The authors of this study begin their paper by outlining what are supposed to be the similarities and differences between human and non-human primates. “Language is considered a uniquely human feature, though most of its components—such as vocal learning, intentionality, syntax, semantics, and other associated cognitive abilities—varyingly emerge in the communication systems of other animals. Yet despite the mechanical similarities between vocal production and perception in human and non-human primates (hereafter primates) as well as our shared evolutionary history, some of these cognitive features seem to be absent from the communication systems of our closest relatives.”19 For many years, the view in research into animal communication assumed that primate vocalizations were due to innate mechanisms driven by internal states and not adaptable by experience. But the view within the profession is changing. As the authors point out, “New evidence, however, demonstrates otherwise: call structural plasticity, call convergence, turn-taking exchanges, and reinforcement-­based vocal learning during development all suggest that primates may at least be limited or moderate vocal learners. Moreover, research examining audience effect on primate communication suggests that some primates have volitional control on vocal production as well as an awareness of the receiver’s perceptual state, potentially indicating some aspects of theory of mind.”20 All these observations are undoubtedly correct and indicate a certain ability among the great apes to reflect upon their own experiences and behave intentionally on the outcome of their own reasoning. Interestingly, the study found that only half of the eight subjects that were tested produced the novel vocalizations, all females, and three of those were close relatives.

 See Salmi, R., Szczupider, M., & Carrigan, J. (2022). A Novel Attention-getting Vocalization of Zoo-housed Western Gorillas. PLoS ONE, 17(8), e0271871. August 10, 2020. 19  Salmi, R., Szczupider, M.; & J. Carrigan, J. (2022), pp. 1–2. I have omitted from the quotation the references by which the authors substantiate their claims. 20  Salmi, R., Szczupider, M., & Carrigan, J. (2022), p. 2. Also here I have omitted the many references supporting the content of this quotation. 18

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This picture fits into the model of how a linguistic convention arises. A leader produces a novel sound with a specific meaning. Then individuals closest to the leader begin to realize its use and imitate this usage for their own advantage—and so forth. Indeed, the evidence seems to show that such a behavior may take several generations before it is distributed among all members of the entire group.21 Also the study reveals that few other gorillas in different zoos had developed a similar attention call within the known vocal range of this species, and most of those individuals were females. Thus, we must expect primates to manage some forms of abstract thinking in the context of food and keepers concerning unobservable properties like what is going on in the mind of both congeners and humans. Still, non-human primates have only a very limited capacity of self-reflection that is far from comparable to the one that natural selection has installed in modern Homo sapiens. According to my view, the capacity of modern language to express abstract thoughts is the outcome of the co-evolution of both physiological and psychological features of hominins. Linguistic communication works because we consciously know that a speaker normally does not say things accidentally, but that she says what she does because she consciously believes that we understand the meaning of what she says. What we see is probably the outcome of the co-evolution between the increasing complexity of language and a growing amount of both social awareness and individual self-awareness that gave our ancestors the ability to reflect upon their own and the thoughts of others. An increasing insight into other hominins’ minds went hand in hand with an insight into our own. Self-awareness seems necessary for several reasons: first, it had to control both that the articulated sounds expressed those particular beliefs, feelings, and intentions, which an individual wanted to communicate, and second that these beliefs were in accord with his or her sensory impressions. With an increasing imaginative and reflective power, the more human thinking diverged from its sensory origin. Thus, self-­ awareness is needed for the listener to find out what a speaker means when he or she refers to something that neither the listener nor the speaker

21

 Salmi, R., Szczupider, M., & Carrigan, J. (2022), p. 14.

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can perceive. Similarly, the speaker needs it to make sure that what she expresses about non-sensory matters is also what she contemplates. From an evolutionary point of view, the benefit of self-awareness is the ability of quickly correcting and supplementing human thinking such that our cognitive system does not have to wait for the result of enumerative induction to improve our thoughts. It not only helps us to realize what it is that we are thinking about and our mistakes with respect to the use of a language. With a new set of cognitive mechanisms, self-awareness also enables us to determine whether the things we experience are as we believe them to be by comparing different experiences. These new mechanisms allowed us consciously to find out what we do not know by realizing our lack of knowledge and to find a means to remedy it. Furthermore, self-awareness improves an individual’s ability to abstract from experienced similarities and differences, including our experience of others’ intentions, as well as to create abstract concepts, which we could never form based on simple induction. Because the mechanisms behind simple induction working on sensations only take the cognitive system from experiential beliefs to empirical beliefs, we need other cognitive mechanisms for abductions and generalizations that the evolution of self-­ awareness appears to have strengthened. Apparently, self-awareness increases the accuracy and specificity of knowledge and the speed of the learning process. Now, a matured language is normative in the sense that it stipulates rules for which signs and sounds we use to denote particular things. But it is also conventional in the sense that human interactions establish the rules that determine our use of these signs and sounds. So the key question is how we get from empirically established correlations in the use of arbitrary signs and sounds to normative rules of speaking. David Hume, as a naturalist, warned us not to go down the slippery slope known as the naturalist fallacy. Nevertheless, a naturalist must face the gulf between the empirical success of inductively established correlations and a similar success of normative rules. Many norms, although social, have an origin in the adaptive nature of learning a language. Linguistic norms begin the moment one learns to associate particular sounds vocalized by others with what they represent. The speaker of a language learns to use the sounds in a resilient way such

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that they reflect these others’ usage and continue the same associations. The behavior of other people toward things we experience ourselves helps us to establish the connection between our own sensory thoughts, these people’s vocalizations, and the conventional meanings of the sounds. The regularity children meet in the usage of others causally and inductively establishes the correlations between sounds and the beliefs of the speaker. Thus, what start out as merely empirical correlations eventually become rules to the children as they realize that these correlations convey meaning to the sounds in question if, and only if, they are followed and kept intact. Of course, for the child this is not a conscious insight, and most of the linguistic rules will never be consciously manifested, but revealed in our own linguistic behavior as we copy the linguistic behavior of others. Linguistic convention cannot be private, as Wittgenstein made clear. Like other social conventions, they require the participation of a least two individuals. A follower has to learn the regular use of sounds carried out by the leader by imitating the leader’s behavior in the proper experiential circumstances. Although this use of a particular sound by the leader might originally have begun accidentally as only a genetically produced vocalization, it would become a beneficial adaptation for any individual if the production of the sound was not directly determined genetically, but was associated with the sensory belief that was correlated with this behavior. During the evolution of hominins, individuals were gradually adapted to associate the production of certain sounds with their sensory thoughts. Other individuals took note of this use and imitated it. As our self-awareness grew, our ability to imagine and comprehend the thoughts of other people slowly improved. Thus, our social insight both phylogenetically and ontogenetically leaves its original causally induced conditioning behind, and the correlations now begin to function as linguistic rules whose prescriptive function may or may not change as a consequence of intersubjective consent. In the process by which we learn that sounds produced by conspecifics may have a representational function, this social comprehension eventually liberated the correlations from their natural origin. Every generation of human beings attempts to understand each other’s feelings and thinking in relation to that generation’s physical, technological and social environment, and therefore one

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generation after another has improved its ability to express this understanding in the form of new norms and rules. In combination with imagination and reflection, language introduced a new ability to generate abstract thoughts with little or no experiential origin. Before the evolution of language, thoughts of hominins concerned only the conceptualization of information from their senses. Features of modern languages are the conventional use of signs and sounds and the recursive structure of its grammar. Those features enable us to speak about matters that go well beyond our immediate experience and attune our actions according to what we believe to be the reality of our situation. This opens up the possibility for both producing and expressing beliefs about a world of invisible entities and possibilities, regardless of whether these entities are natural or manufactured. Use of the definite article enables us to express our beliefs that what is said exists, even though the belief itself is a product of linguistic rules and our imagination. The evolution of language also allows us to adopt new rules of behavior and thereby to construct new social institutions. Reflecting upon what we see, we may form beliefs about those institutions and other matters transcending the physical world.

 mpirical Knowledge and the Evolution E of Language The transition of individual knowledge into public knowledge is a process that departed from experiential knowledge at the time when our predecessors became able to reflect upon the content of their own (and others’) sensations and could use language to establish a new form of knowledge that we shall call “empirical knowledge.” Empirical knowledge is the knowledge we share with other human beings because of our agreement about the same observation reports in the same or a similar perceptual contexts. However, empirical knowledge contains all the true but non-sensory beliefs we have concerning things’ potential, dispositional, and relational properties in addition to those we have concerning socially defined entities. This form of knowledge includes almost all of our everyday knowledge such as what a book looks like, that

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sugar dissolves in water, that there are five books on my desk right now, that I am married to my wife, and that I need money or a credit card to buy cereals in the supermarket around the corner, etc., etc. I also assume that few other animals have a certain amount of empirical knowledge because they are able to reflect (unconsciously) upon their sensations and behaviorally express their agreement; nevertheless, this ability is not in any way close to the capacity of human beings. Thus, if we say that empirical knowledge rests not only on the ability to classify perceptual objects categorically according to their observable properties, but also, in addition to experiential knowledge, on the abilities to learn about the environment based on associative, relational, and functional classifications, many studies indicate that empirical knowledge is not reserved to humans. Higher animals have empirical knowledge as well.22 What characterizes empirical knowledge, in contrast to experiential knowledge, is in my view that the former, but not the latter, includes a belief about something the classification of which goes beyond what is revealed in the immediate experience. The resulting empirical concept covers the attribution of unobserved or maybe even unobservable properties to the object of that concept. Thomas Zentall and colleagues define associate concept learning as a process that “involves the ability of animals to form categories made up of arbitrary stimuli that are deemed to be equivalent on the basis of their being associated with a common event or outcome.”23 This kind of learning we see when a young vervet monkey picks up an alarm call or when a human associates a new word with an object. Here the acquired association does not rely directly on observable features of the sign or the object, but instead on the observation of the regular circumstances in which another individual uses the sign. This is also the case with more advanced relational concept learning. Whereas perceptual concept learning of objects already requires an ability to recognize similarities and differences between earlier and present sensations of objects, the recognized  Zentall, T.R. et al. (2008). Concept Learning in Animals. Comparative Cognition and Behavioral Reviews, 3, 13–45. https://doi.org/10.3819/ccbr.2008.30002. This paper reviews a number of experimental studies that provide solid evidence for animals’ ability to form different types of concepts that supersede the basic classification of sensations. 23  Zentall, T.R. et al. (2008), p. 14. 22

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similarities or differences need not always be between observable features. This seems to be the case with analogical learning. In such a situation, an animal is learning by unconsciously comparing a set of relations with another set of relations to discover whether they are similar or dissimilar. Although the recognized relations are between observable objects, the comparison of the two sets of relations is not about something that is observable. However, as Zentall and co-workers remark, “At the behavioral level, there is good evidence of the relational capacity in nonhumans; yet, further analyses suggest a possible disparity in process between symbol-sophisticated apes and humans, on the one hand, and other animals, on the other.”24 This observation points to the fact that the evolution of advanced forms of communication, especially human language, opened up new ways of learning concepts, and therefore new ways of acquiring empirical knowledge, ways that are not just a result of a species’ sensory stimuli and innate abilities of categorization but also depend on conscious reflections and abstractions. Indeed, as verbal language developed among our predecessors, their conscious reflective abilities improved, and as their reflective powers were thus enhanced, this evolution nurtured the expansion and advancement of their language. As the development of empirical knowledge progressed into public knowledge because of human self-reflection, the recognition of other minds and the verbal articulation of agreements went hand in hand. Thus empirical knowledge supersedes experiential knowledge as not bounded to the memory of sensory properties alone. Apart from categorization of objects with respect their sensory similarities and differences, which is the first-order abstraction behind sensory concept-based knowledge, empirical concept-based knowledge emerges as the outcome of what we may call second-order abstraction. Often different sorts of visual things elicit the same or different recurrent reactions to other types of visual things, which human thinking then takes as the manifestation of a particular unobservable sort of feature. This form of abstraction assigns what we may call non-sensory dispositions to those visible entities. The distinction between empirical knowledge and experiential knowledge is that empirical knowledge is concerned with sensible entities with some non-sensory properties such as dispositions, whereas experiential  Zentall, T.R. et al. (2008), p. 15.

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knowledge is limited to things whose properties we actually can sense. For instance, imagine that some of our ancestors living in a certain area came across some fruit they had not seen before. They may already have an idea that what they see are fruits, and perhaps they know some fruits are palatable and others are not. We already find this form of knowledge among higher animals according to the tastes these animals associate with various foods. But a taste is a sensory quality that may produce an image and/or a belief as part of our experiential knowledge. However, if some of our ancient forerunners remembered to have heard that someone in the tribe had died by eating an unknown kind of fruit (judged by its appearance), they could share this story with the others and suggest that the fruits they were facing might be these unknown fruits. The tripe could then reach an agreement based in their trust in those who communicated the story that eating this kind of fruit might be dangerous. Hence these hominin’s ability to reflect upon their own memories allowed them to invent a new concept of a non-sensory quality of ‘poisonous’, where the extension of the predicate covers entities that are able to kill people or least make them very sick. The contrasting concept, expressed by the predicate ‘edible’, is satisfied by entities that do no harm to those who eat them. In both cases, the concept of being poisonous or being edible is part of our empirical knowledge concerning a variety of possible foods, snakes, etc. Similarly, we do not see the various seasons. We experience some returning phenomena we associate with a particular season; perhaps such as darkness, low sun, snow, trees without leaves, and feeling cold in the winter. Opposite to winter, summer is hot and sunny, the sun is high in the sky, and trees have green foliage. However, the time between winter and summer is either spring or fall, where birds and animals migrate north or south and leaves bud out or fall from the trees. Indeed, dividing a year into seasons is an abstract construction of the mind. We experience only proxies that act as signs of a particular season. Yet such constructions become part of our empirical knowledge whenever we categorize and name a set of regularly repeating phenomena under the same heading. Considering these scenarios, we may explain how the evolution of verbal language benefitted our ancestors’ capacity for reflection. The benefit of the emergence of language for the development of empirical knowledge seems to take place on several fronts. First, verbal language gave our ancestors the ability to express their sensory beliefs and thinking much

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more effectively than merely through bodily behavior. (Obviously, using sign language requires that you face the person to whom you speak.) Since natural selection shaped humans such that they usually have the same sensations while receiving the same physical stimulation, the sensory awareness experienced by our ancestors was very similar whenever they experienced the same phenomenon. This gave them the ability to coordinate the same verbal expression that was associated with the common experienced phenomenon. The result was that humans could cooperate more effectively, they could teach each other about what the individually had learned, and they could easily communicate this knowledge through the generations. By these means, the individual experiential knowledge of humans was enlarged into public empirical knowledge. Second, inventing new words and phrases expanded the range of the thinking of early humans and helped them to make a clearer classification and more precise conceptualization of dispositions, relations, and regularities. The development of language simplified what otherwise would have been a very complicated train of thoughts, such as ‘there is something about these particular fruits that makes people die from eating them.’ Indeed, this train of thought would already have been too complicated to comprehend without the use of language (just as causing people to die is a dispositional non-sensory property of the fruit.) Language gave human thinking something to work with such that new words, little by little, not only represented human pre-linguistic thinking but also empowered human thought with the power to conquer new epistemic territory. Presumably, the attribution of invisible properties to visible entities would be impossible unless the individual mind could use language in a constructive role to pinpoint its thoughts, because most likely our innate cognitive mechanisms of learning do not automatically drive the formation of these kinds of concepts, as they do with respect to the development of concepts concerning visible things. The development of language moved an important part of human thinking from being image-based and concept-based to becoming language-­based. So when we get to know empirically that this kind of fruit is poisonous—even though this knowledge is the outcome of two forms of mental constructions, a categorical first-order abstraction, a kind of visible fruit, and an attributable second-order abstraction, being

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poisonous—it is because knowledge like this mainly concerns concrete particulars in our environment that we can see, hear, smell, taste, touch, and move around. The abstractions just mentioned departure from the similarities and differences we can experience in the way things look and behave. Hence, our empirical knowledge consists of thousands and thousands of beliefs about invisible features that we automatically associate with things we can experience. Empirical knowledge, which most people share, has accumulated over many generations transmitted by language. Such everyday knowledge does not deal with only the physical environment, but also the social environment as well. Much of our social knowledge about human beings is empirical because it rests on the same sorts of abstractions from what we directly experience.

From Concrete to Abstract Thinking Quite uncontroversially I hold that beliefs are different from thinking. Thinking may involve images, concepts, or a combination of both. Beliefs are mental states having particular thoughts as their  content, whereas thinking, the one based on concepts and not on images, is a mental process whose function it is to deliver conjectures and cognitive solutions to an organism based on its sensory and non-sensory beliefs. This form of thinking brings a creature from one thought to another. Earlier we have seen that the defining feature of sentient beings is their ability to form sensations and to store information of these sense images for later use as templates of non-sensory images in order to learn to recognize the content of present sensations. Thus, I argued that sensory recognition does not require an animal to harbor some non-sensory beliefs. It presupposes the animal has only templates of non-sensory images. However, more flexible and elaborated responses to its environment demand that an animal can form beliefs in a way that parts of its comprehension consist of non-sensory concepts. Such a conceptual identification of actual sensations demands that an organism is able to classify the informational content of its sensations. It is in situations where the mechanisms behind the sensory presentation or

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the conceptual recognition of the sensory content fail to work correctly that the sensory beliefs of a particular organism turn out to be false. In general, such a conceptual recognition fails even though the adaptation of the cognitive mechanisms of all animal species have evolved under the pressure of the environment to the benefit of the reproduction of living organisms. The reason is that the conditions for these mechanics to function optimally is permanently or momentarily put out of action. Natural selection and adaptation make sure that an animal’s manner of presenting the environmental stimuli and of conceptually identifying the informational content of this presentation are reliable processes (given the purpose of sensory presentation and recognition.) Thus, no one should raise eyebrows that naturalists in the overwhelmingly majority of cases would attribute concept-based knowledge even to lower organisms. However, it is not for a philosopher to decide which ones are included and which are not. It depends on empirical experiments to resolve the question when organisms, besides having image-based knowledge, begin to evolve concept-­based knowledge. The empirical evidence is that an organism is able to respond in a particular way to a particular type of objects. Indeed, the supplementing of imaged-based knowledge with concept-­ based knowledge must have been a huge advantage in the cognitive development of animals. The ability to form concepts and acquire beliefs is the first step toward abstract, non-linguistic thinking, since a concept is a first-order abstraction requiring a move of thought from grasping an individual toward grasping a set of individuals. As I talk about thinking beings, I refer to beings whose thinking is concept-based just as much as image-based. Thinking beings, like dogs, cats, monkeys, and crows, are animals that have learned by induction to classify what are for them important visual phenomena in their environment and to think about them in relation to their own actions. They are not merely disposed to have sensory and non-sensory beliefs, apart from their sensory images and non-sensory images, but are also able to relate these mental states to other non-sensory mental states such as desires, expectations, preferences, intentions, and decision-making. In all these cases, the mental content of the animal is not just a result of sensory stimulations. Thinking beings are so adapted that these non-sensory mental states allow them to make decisions for future behavior in situations where perception leaves the organism with more than one alternative for action. Non-sensory mental states

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may consist of remembered sensory beliefs or beliefs generalized from such experiences. However, concept-based thinking presupposes other cognitive attitudes. You need to able to reason whenever more than one option for behavior is available, and an animal capable of thinking should be able to identify these options. In a case of multiple options, it may expect that one of them will more likely happen based on its experiences in the past, it may want one of them to appear due to its preferences, or it may intend one of them to occur assuming that it is within its power to select one of the options. These cognitive attitudes are mental states we find among humans and higher animals. It is rather clear that an organism cannot have any advantage from its desires, expectations, and intentions unless these attitudes at least involve a content that is similar to some present sensory and behavioral thoughts. At some point during evolution, however, these thoughts need not be about any present object. Moreover, they eventually had to consist of empirical concepts by which the organism was capable of understanding disposition, relation, and regularity. I think the reason is that the content of most desires, expectations, and intentions is traceable back to the acquirement of sensory information about visible objects in the past in combination with non-sensory beliefs that this type of object has some invisible property. I may have an empirical belief that there are mountains outside my window, because each time I have looked, I have acquired a sensory belief about the mountains. I may have a desire to visit the mountains, because I believe the trip will be as gorgeous as it was last time. I may have an expectation of catching a salmon from this part of the river, because I have often caught one at this location (and thereby I now have a particular memory about lots of salmon caught in the past), but not always (I now lack a particular non-sensory belief that I always have been able to catch salmon.) This amount of information produces in me a certain expectation that the chance of catching a salmon next time is high. My earlier expectations may diminish to only hopes of catching a salmon, if lately I have received fewer sensory beliefs about salmon I have caught. I also build up some preferences due to earlier successful experiences; I prefer, given my previous experiences, to stand on this side of the river rather than on the other side. Finally, based on my present experience and beliefs about the future, which are inferred from my knowledge about the past, I may work intentionally to actually bring

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about one of several possibilities. Having the capacity of remembering many of my previous sense impressions and having the capacity of distinguishing my behavioral options and my preferences, the present sense impressions allow me one of the most advanced cognitive attitudes ever to evolve. Higher animals have intentions. They can pursue a goal. Some species may only be able to imagine a visible or an otherwise experienced goal toward they are heading; others, including humans, may even be able to imagine an invisible or non-experienced goal. Previous experiences guide all these intentions of attempting to realize specific goals. Desires drive both human and non-human animals. Some desires, like hunger, thirst, and sleep, are genetically determined, whereas others are habits, established through training and learning. My dog, for instance, shows me that it harbors a desire of getting into the backyard by placing itself in front of the backdoor waiting for me to see it. Similarly, it goes to the doorstep and barks whenever it wants to get in. It also shows a desire for a walk by getting up and looking at me when it feels it is the usual time for a walk. In these cases, my dog has a non-sensory belief that doing a specific action leads to fulfilling its desire. Familiar experiences like these examples with my dog show us that many animals have expectations. My dog expects me to behave in a certain way when I become aware of its behavior. But expectations need not be a result solely of training. A hungry chimpanzee may see that an experimenter hides a banana under one of four boxes in another room, but before it can enter that room, the room will be out of its sight for a short moment. Meanwhile, the experimenter moves the banana. When the chimpanzee enters the room and discover that there is no banana under the designated box, it becomes frustrated, making a lot of noise, while it looks under the other boxes to see whether the banana was concealed under one of them. The chimpanzee clearly remembers the episode and expects to find the banana under the right box.25 The example also nicely illustrates how image-based and concept-based thinking blend together in the chimpanzee’s attempt to solve the problem.  Many experiments show that apes do not have the ability to understand false belief. See Tomasello, M. (1913). Why Don’t Apes Understand False Beliefs? In M.R. Banaji and S.A. Gelman (Eds.), Navigating the Social World, University Press. However, I find it in no way strange. Understanding a false belief in others or in oneself requires a high level of self-awareness that chimpanzees or other apes do not have. 25

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The existence of various cognitive attitudes gives us a hint at how we should understand the evolution of animals. The more complex a thinking animal is the more future-oriented is its thinking and behavior. Sensory images, sensory beliefs, and the memory of them are sufficient for keeping an animal alive, but these mental states are unable to help it to improve its behavior with respect to new options or a changing environment. Some sensory beings can learn to optimize their behavior by conceptually recognizing the similarity of the present sensory images with some earlier sensory images and recalling whether the subsequent behavior was successful in the past. Indeed, this process is the work of induction, which is a dominant part of both human reasoning and the thinking of many animals. Selection and adaptation of imagination and intention have improved the survival strategies of thinking beings. The emergence of the ability to imagine counterfactual scenarios in support of predicting the behavioral consequences of people or other creatures is one such survival strategy. Eventually, adaptation features thinking beings with a range of cognitive functions that facilitate forward-directed behavior. In this way, these beings can foresee different possibilities, postpone an immediate reaction for a later one, and lay out tactics and strategies in order to reach an intended goal of desire. Animals may not be motivated by a conscious awareness of their own desire when pursuing a goal, but this is not true only for non-human animals. It is probably also often true for most people, although people, and perhaps some higher animals, can sometimes be conscious of their desires. As genuine self-reflective beings, of all creatures human beings are undoubtedly those whose cognitive functions are structured with the highest focus on the future. Humans have a desire to predict the future and to understand sensory happenings. The evolution of language opened up the possibility for social beliefs and imaginative creations of possibilities about things that stretch far beyond the present and the immediate future. Later we shall turn to scientific knowledge and the challenges this might raise for any naturalist account. Before we get there, we shall discuss how the rise of empirical thinking required the introduction of epistemic standards as part of a communicative practice.

7 Social Knowledge, Agreements, and Testimonies

As language, little by little, emerged as an effective means of communication, knowledge moved from being a purely biological manifestation to becoming a social enterprise as well. The topic of the previous chapter was how our practical knowledge of speaking a language might have evolved, and the conclusion was that empirical knowledge in contrast to experiential knowledge was not possible without the rise of language. In this chapter, we shall look into how norms of empirical knowledge appear as a natural consequence of using language for communicative purposes. A shared language opened up for development in which personal knowledge is embedded in a social discourse to enable the community to come together to work toward a common epistemic goal. This conclusion does not imply that empirical knowledge is something we just invented. Rather my point is that it is a cognitive advantage for humans to work together to find out what the truth is apart from our individual beliefs. We must jointly abide by the rules of the communication to create reliable knowledge—because if we do not, there will be no reliable knowledge to adhere to. Because of our common phylogenetic adaptation, the sensations of humans are alike such that in the same situation we often agree with the same observation reports. Thus, the evolution of human language and the perpetual expansion of empirical knowledge among © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. Faye, The Biological and Social Dimensions of Human Knowledge, https://doi.org/10.1007/978-3-031-39137-8_7

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human beings allowed them to develop a rationale for holding when they personally agree or disagree with other community members concerning these observation reports. The negative wordings are intentional, because in general people often reach consensus about what they believe and hold true based on the wishes of those among whom they live. However, empirical knowledge does not require individual justification but agreement with others’ knowledge, and such an agreement is reached when people are ready to accept the same observation reports. The reason is that empirical knowledge is an extension of experiential knowledge into the public domain, where personal justification does not count because much of this knowledge builds upon general beliefs expressed by non-sensory predicates. Empirical knowledge always extends beyond each individual’s experiential knowledge. Consequently, empirical knowledge and the experiential conditions, which make this knowledge possible, are linguistically based knowledge that we are taught as part of our upbringing as members of a language community. Only if a permanent disagreement prevails between various observers do we need a justificatory procedure to deal with their different views expressed by their observation reports. But no absolute justification exists, only justification relative to intersubjective agreement. Therefore, an intersubjective justification of any observation report depends on a mutual agreement about what counts as justification, about the verbal meaning of the reports, and about how to interpret the suggested evidence in favor of the reports.

From Language to Social Epistemology The traditional philosophical attempts to understand empirical knowledge focus on knowledge as a subjective property of an individual that is describable in terms of some a priori characteristics like justified true beliefs. Moreover, true beliefs are concerned with propositions. Because of their a priori status, these characteristics are considered prescriptive as much as descriptive. Beliefs must be true and justified in order to count as knowledge. All this has changed partly due to some epistemological insights such as Edmund Gettier’s famous counterexamples, as well as

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partly due to some psychological insights that children and mentally handicapped adults possess knowledge although unable to justify their beliefs.1 The abandonment of the justified true belief view of knowledge is also in part due to biological insights that experiential knowledge is a natural phenomenon the main function of which is to benefit both human and non-human individuals in their survival. However, a naturalistic approach to empirical knowledge requires us to understand it not only as a biological phenomenon but also as a social one. An important piece of human knowledge would not exist if we were not social and linguistic beings. As individuals, we are able to learn a language to convey both our ideas and knowledge to others, and through linguistic communication, we coordinate our beliefs with others’ to reach intersubjective agreement. By listening to others’ testimonies, we likewise acquire knowledge about facts we have not witnessed ourselves or have derived from such observations, but which other humans claim to know. For a start, I would not know what various words of a language mean had it not been for more advanced speakers who had been able to teach me about their meaning. Moreover, a great part of empirical knowledge is due to spoken or written testimonies. For instance, I would not know that some people are arrogant, that Alice and Bob are married when they have gone through a social ceremony, that Mount Everest is the highest mountain on Earth, that London is the capital of England, and that there are eight known planets in the solar system, had I not gotten these beliefs from others. All these examples of empirical knowledge claims express propositional knowledge, which human individuals possess in virtue of being language-speaking individuals. Here I shall present a theory of knowledge that considers epistemological problems as flaws in the conditions of successful communication instead of defects in some intrinsic features of justification. Justification is a property that characterize our beliefs only when we express them in language. By expressing our experiential beliefs in a language of declarative sentences, we provide them with an empirical content, and it places us in situations in which others expect us to be able to communicate our beliefs felicitously. In addition to being reliably obtained, of which  Gettier, E. (1963). Is Justified True Belief Knowledge? Analysis, 26, 144–146.

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experiential knowledge is the antecedent source, in order to be true the content of an empirical belief requires that the believer understands the language in which the belief is expressed. Moreover, a belief is truthfully stated only in case the speaker is sincere about her belief. The speaker must, if challenged, hold that the beliefs of others would agree with hers if they were in the same cognitive situation, and she finds herself obliged to act upon it if required. As we have seen, empirical knowledge presupposes the evolution of language to the point that the way we characterize propositions expressing this knowledge depends on if we use language to communicate our thoughts successfully. Finally, I reason that considerations about the felicity conditions of speech acts that deal with assertions about things that are invisible to the speaker as well as the listener reveal the epistemic norms we require for having theoretical knowledge. Usually, we think of the use of language as consisting of three components: syntactical rules that structure our sentences, semantical rules that regulate their meaning, and pragmatic rules that tell us how to use these sentences in an appropriate way to express our thoughts in a given context. I have argued that language has evolved roughly as a means of expressing empirical thoughts and that following the rules for using a language is a sort of practical knowledge we have acquired through socialization. Experiential knowledge is not subject to epistemic rules but entirely determined by innate cognitive mechanisms. We must assume that cognitive schemas that organize our thoughts constraint the structure of our expressions. Therefore, the issue is how the evolution of language takes us from experiential knowledge to empirical knowledge. In my opinion, the explanation lies in using self-awareness in an attempt to understand our cognitive and linguistic practices in relation to our own thinking. What we consider the epistemic rules determining how we ascribe empirical knowledge to ourselves and others reflect the basic conditions for successful communication. Language originally evolved as a means of expressing experiential thoughts, which we automatically share with our fellow human beings in virtue of experiencing the same things. The rise of language partly structured our thoughts in new ways and gave linguistically formulated beliefs

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their propositional content.2 The conventionality of language and its open-ended structures influence the range of human thinking by allowing the creation of new words and the combination of new sentences as an expression of the reflection of our self-awareness. Language enables humans to construct sentences the meaning of which exceeds the language user’s sensory and behavioral beliefs. Self-awareness or self-­ consciousness offers humans an ability to invent abstract matters and to speculate and fantasize about invisible things such as future events and counterfactual situations. Language gives humans the ability to encode beliefs about these things with an overt behavior, which conspecifics can observe and interpret. Therefore, they can coordinate their reflective thoughts and therefore cooperate with respect to things they cannot experience. We should distinguish between three possible set-ups in which early communication took place. We have different speech-act situations in relation to whether: (1) the speaker makes a claim about a visible thing that both he and the listener can see; (2) the speaker makes a claim about a visible thing, which he himself has experienced, but which the listener does not have the opportunity to experience herself; and (3) the speaker makes a claim about things that are (at least in part) invisible to both himself and the listener. The first situation is one upon which I have already touched. In these circumstances, the listener learns how the speaker uses words and sentences, and because both can see what the speaker believes, the listener may either learn the use of novel words or acquire new empirical knowledge or both. However, in these circumstances the listener may also be able to correct the speaker’s use of language or correct the speaker’s belief or both. In situation one, unless the listener is a child, the speaker and the listener are in a position in which they mutually can learn from each other by articulation what they both see. Moreover, they can correct one another in case they believe the other is mistaken without having any other cognitive standards that govern the fitness of their experience. Neither the speaker nor the listener needs any epistemic norms for  For instance, some evidence suggests that the categorization of colors can change while we learn our first language. 2

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approving each other’s knowledge. However, the circumstances change radically, I think, when we turn to the second situation, where the listener has not experienced what the speaker’s assertion is about. In that situation, the listener develops certain expectations about the content of the speaker’s report, because she can no longer rely on her own experience in controlling the truth of what the speaker states. Moreover, eventually the speaker adopts the same set of norms whenever the listener becomes a speaker. The norms become the underlying public rules for speech acts and communication. Self-awareness is awareness of and reflection on not only our thoughts, but also on using language to express these thoughts. The use of language to communicate thoughts follows socially established rules. However, the thoughts expressed by any speaker may concern entities or states of affairs invisible to an audience, but since the audience cannot obtain the content of these thoughts by reliable mechanisms of sensation, people depend on public rules for using language to communicate them. John Austin called these rules for the felicity conditions and divided them into preparatory, sincerity, and essential conditions.3 These are the pragmatic constraints that hold for performing various speech acts. According to Austin, uttering a descriptive sentence is performing a locutionary act in which the speaker maintains that the world is as he or she thinks it is. But if a descriptive sentence should function as an illocutionary act in which the listener understands the utterance as the speaker’s assertion that the world is as described by the sentence, the utterance has to meet some conditions. This is especially true if the sentence intends to describe some abstract or invisible state of affairs that nobody can experience. Among the felicity conditions is the essential condition: the speaker undertakes, by virtue of his or her statement, to guarantee that the statement made is a correct description of what the speaker believes is the facts. By uttering a statement with assertive power, one commits oneself to a number of statements, namely those that logically follow from that statement, and refrains from a number of other statements, namely those that contradict  See Austin, J.L. (1962). How to do Things with Words. Oxford University Press. In this book, he rejects his earlier distinction between constative and performative utterances. Now he considers them all as illocutionary speech acts that use a locution with illocutionary force. 3

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it. In case of one deliberately violates these conditions, one fails to fulfill ones obligation to stand up for the correctness of what is said, and as a consequence one violates the social institution we have created to use our assertions to speak about reality. The social institution of speech acts is the key to understanding human knowledge. Epistemology grows out of speech acts that may pretend to communicate the speaker’s beliefs about facts invisible to the listener. Working with propositional knowledge, epistemology relies on our ability to express our beliefs in statements that define the propositional content of our beliefs. Claiming that a lion is walking away or that there is little water in the pond is a speech act by which the hunter claims to know what he says. The others standing next to the speaker will undoubtedly accept the claim, since they see the same thing. As long as a speaker only utters statements, expressing his or her experiential knowledge, there is little need for socially sanctioned norms to which the speaker must comply in order to be honest about the assertion. Such norms are not essential for communication about experiential beliefs because the speaker and the listener obtain beliefs about common state of affairs; they see the same thing because they possess the same reliable belief-generating mechanisms. Even if the hunter claims that a lion lies behind this mound, or there is fresh water in the direction of these trees, the listener accepts this speech act merely on the basis that if she would bring herself into the same sensory and behavioral situation as the speaker once did, they would witness the same state of affairs. But claiming that there was a lion behind the mound an hour ago is not something any one can witness anymore. Thus, in such a situation we draw on the felicity conditions for speech acts. Today we know that the individual sensory fitness among people is uniform due to the same reliable mechanisms in each of us. However, the evolution of language to communicate thoughts about unobservable happenings such as past or future events, possible occurrences, and invisible objects puts the conditions of communication into a different context. Both the speaker and the listener now realize that reality may not be as asserted. Indeed, many things we know of are observable but actually unobserved when we express our beliefs about them. If I state my conviction that a bouquet of flowers is standing on the table in the room next-door,

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because I just placed it there, my listener does not demand of me that I am otherwise justified in my belief before he or she will ascribe knowledge to me. I may be mistaken in my assertion because someone has removed the vase without my knowledge. It is not among the listener’s expectations that the situation could be different from what I believe, because my belief is the same belief that the listener would have acquired in the same situation. Nature has made perception robust and trustworthy as our main source of knowledge such that little doubt clings to perceptual reports. Therefore, the listener would not require that I must be able to justify that the flowers are still on the table before she ascribes knowledge to me, unless of course, she has sufficient reasons to believe that I am wrong. But the listener would require that my report is true in the sense that my report is in accordance with the content of my reliably acquired sensory and behavioral beliefs. So it still makes sense to hold that I know that there is a bouquet of flowers next door, in spite of the fact that there is a very small chance that someone has removed it just before my claim. Every person in my situation would similarly have been convinced by the same reasons, and everybody else would agree that normally these reasons are sufficient to have knowledge. However, the epistemological consequences of speech act theory is that we may have an obligation to apply different epistemic standards to sensory beliefs and to non-sensory beliefs. Here there may be differences in our expectations before an agreement can be obtained, depending on whether the empirically acquired beliefs are dealing with almost present or long gone state of affairs, especially if someone later could have influenced what originally was the case. Yet, modern communication often concerns invisible things that nobody can experience, but about which reflection has brought us knowledge. In such cases, we face the third speech act situation, where the felicity conditions contain an expectation that the speaker somehow is able to justify what he asserts. Thus, if I say that billions of neutrinos pass through you every second—something no one has seen—the felicity conditions seem to demand that I can justify my belief by either pointing to supporting evidence or supporting testimony. In such a situation, you could not be sure that this is true, since neither you nor I are adapted by natural selection to have experiences of neutrinos. In other words, the felicity

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conditions change unconsciously for the speaker and the listener depending on whether the source of our beliefs is made reliable by nature or only justifiable by reflection. So my suggestion is that while hominin thinking became more and more occupied with abstract problems or invisible things such as what happened in the past or what might cause natural phenomena to happen, social institutions evolved around epistemic communication norms by developing implicit conditions for presenting assertions expressing beliefs about unobservables. The essential commitments one had to subscribe to were truth and justification. To count as an assertion about something invisible, one’s statement has to be true and justified. Since the Greeks, philosophers have intuitively taken these commitments out of their social context and elevated them to the level of essential characteristics of genuine knowledge, as if truth and justification were objective features of knowledge. Though tempting to believe otherwise, truth and justification as norms are social constructs that we have accepted as part of the felicity conditions, in order to enable the reliable use of language for communicating and asserting thoughts about invisibles. Admittedly, the felicity conditions might be social rules of communication, whereas truth has been chosen to be among them, because it is an intersubjective feature of statements. After all, any utterance of a descriptive sentence seems to be automatically true just in case the world is as described by the sentence in spite of the fact that we may be unable to determine its truth-value. According to the correspondence theory of truth, a proposition is true regardless of whether or not we can justify its truth. Such a metaphysical conception of truth is far from what a naturalist would accept.4 A naturalist such as an evolutionary epistemologist would hold that the conventionality of language implies that statements are neither true nor false before we have established a correlation between a certain type of sentences by which we utter these statements and a certain set of non-linguistically determined facts. The way to establish such a truth relation is to make sure that the referring terms actually refer to  Elsewhere, in Faye, J. Experience and Beyond. The Outline of a Darwinian Metaphysics, Palgrave Macmillan, pp. 159–208, I have proposed such a naturalist notion of truth. I refer the reader to this much longer exposition. 4

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something real (and not something we only imagine). We need to fix some empirical criteria to establish the existence of non-empirical referents. If we have no knowledge of such accessible criteria, we cannot decide whether to use a particular sentence to describe the world or just to describe our thinking about the world. Only once we have determined the empirical criteria for asserting a certain type of sentence does it make sense to claim that a particular statement is true or false independently of our ability to justify it. Indeed, in those cases where somebody challenges our statement, we have to appeal to the fulfilment of such empirical criteria in order to maintain that the belief expressed by the statement is justified. The requirement that empirical beliefs have to be true and justified in order to count as knowledge is a socially established commitment. Neither truth nor justification are by themselves mind-independent features of reliably acquired beliefs, much less so is the demand that a reliable belief has to meet these particular socially determined features before it amounts to empirical knowledge. Although truth and justification are neither natural nor objective features of our thoughts, they are not arbitrary but partly a result of reflective contemplations. The concept of truth is a social invention, the function of which is to commit the speaker not to ascertain sentences, he or she does not hold to be true. The listener, on the other hand, expects not only that the speaker is honest about his or her belief, but also is somehow justified in presenting a statement as true. In other words, the listener expects that the speaker knows about what he or she is talking by being able to cite something in support of the truth. Of course, we all know that this is often not the case, just as our trust very much depends on whether or not we believe the speaker has reasons to lie to us. The major part of human knowledge is empirical, which means that our sensory and behavioral knowledge we are able to express in language today have increased our individual cognitive fitness. Therefore, I have proposed that the model of communication from which we have abstracted the concept of truth builds on the intersubjective relationship between reports about our experiential beliefs and the informational content of our sensory experience. What might have happened was that when contemplating non-sensory beliefs people have reached the

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conclusion that these beliefs had to fulfill the same relationship as the one between reports about sensory beliefs and the biologically determined content of our sensory experience, because without reasons we do not doubt that things are as our sense experience shows us they are. For instance, our senses show that distant trees are smaller than near ones, but virtually no one believes that because we learn as babies that we see things in perspective. It is an indisputable part of our empirical knowledge that visual sensations present the world to us in a three-dimensional perspective. Another indisputable part of our empirical knowledge is that the colors of things remain the same in the dark. Therefore, as part of their ontogenetic maturity, all people learn to regard empirical reality as something that is not always entirely consistent with what a particular episodic sensory experience may lead us to believe. The same relationship must hold for empirical beliefs if these have to be true, but the problem is that the some of the content of such beliefs refers to something that we do not or cannot experience. The outcome of such considerations leads us into traditional epistemology: in order for empirical beliefs to count as knowledge they have to be true and empirically justified—an a priori demand that applies to theoretical beliefs as well, since empirical beliefs are sometimes mistaken.

Perlocutionary Effects and Social Knowledge Observation reports are speech acts openly uttered. If not openly uttered, they are considered as linguistically formulated thoughts. A report concerning our experience is the same as making a statement in which we describe our experiential beliefs in an empirical language. We thereby directly commit ourselves to the truth of what we are saying. However, as long as knowledge consists of only experiential information, which an organism is able to have because of its adaptations, what an organism believes is irrelevant to any societal approval of its beliefs. But if, in addition, an organism is a language user, and some of its observational beliefs are expressed in terms of sensory as well as non-sensory predicates, the use of these predicates in the observation reports is subject to social control. Often the audience will be able to observe the same state of affairs

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and may agree with the speaker’s report; or if the report is concerning a past observation, they will trust the report, unless they have reasons to believe otherwise. Thus, the conditions of satisfaction for a speech act such as the assertion of an observation report are not only that it is (supposedly) true, but also that the speaker sincerely believes the content of her own assertion. The speaker is expected to be sincere about her assertion, even though it may be that what she states is false.5 If she does not agree with what she herself says, she is lying. Nevertheless, as long as her assertion is intended to have only illocutionary force, her beliefs do not yet express public knowledge. She might want to assert her own conviction without claiming that she knows what she asserts. She may for instance say, “This man is a thief ” or “This woman is pregnant” but does not intend to express other than her own opinion. Of course, she may also intend with her assertions to say, “I know it regardless of what my interlocutor thinks.” But if her beliefs are asserted as more than mere opinions, she must want to be trusted to be saying something truthfully. Her intension must be that the interlocutor understands the meaning of her statements in order for him to ascribe knowledge to her. He will do this only if he also accepts that he himself should believe what she asserts. In other word, she should intend to express something that produces consent in the interlocutor and not dissent. Her speech acts must have perlocutionary effects, which she can intentionally strengthen with a knowledge operator such as “I know that …” in front of a statement expressing her thought. As far as the interlocutor agrees with what the speaker states, he will not challenge her beliefs and be willing to ascribe knowledge to her. Sharing the same language in which both people can report their observations and having faculties that are the results of the same cognitive adaptations, most people will therefore normally agree about singular reports about their sensory experiences. From such a shared experiential basis, social knowledge emerges through linguistic interactions and conceptual developments in which reports about the numerous observations of many individual people come to play a role in forming public beliefs. What were originally personal experiences made by our predecessors have  See, for instance, Austin, J.L. (1962), p. 41.

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transformed into the social knowledge we learn either through our upbringing or later by our interacting with other people. Almost none of us doubts that most of our knowledge we have acquired as social beliefs are true. Of course, those people who teach us what we should believe wish us to start to believe what they say is true, i.e. they want their utterances to have perlocutionary effects. As long as the speakers or the public media have authority, and we consider them honest in their communication, their utterances have such effects and we do not challenge their messages. We get to know that things are as the speakers or the media assert without being able to justify the content of these assertions. In fact, we do not need to be able to present evidence for our beliefs in order for them to have the status of knowledge. All we have to do is to agree tacitly with what we are learning. All shared knowledge exists because of a common agreement about the truth of our beliefs. People are in general altruistic and trust others if they know them well as trustworthy, or believe they know them as such, or provide them with an authority they do not have themselves. So in most contexts in which people report what they know, we do not challenge their assertions, because we have no rational grounds to disagree with their acclaimed truth. When we disagree with another person, we may do it for a number of reasons. Either we cannot observe what that particular person reports observing, or we possess observable evidence that contradicts the alleged observation. We may also doubt that this particular speaker, although usually honest, is well informed about the subject about which we raise dissent. In some cases, we may directly know that what the speaker asserts goes against common knowledge. However, most distrust is not based on rational grounds, but on emotional ones. Whatever the reason or the emotion is, we are no longer in agreement with the speaker. If we are in disagreement, we put ourselves into a new epistemic situation, assuming we want to continue a further conversation with the speaker (and vice versa). Indeed, we may attempt to persuade the speaker, but this action would only show that we have a different belief than the speaker, not that we know something that the speaker does not know. Therefore, we must show that our opinions are more reliably established than the opinions of the other party, hoping that the other party can be influenced by reasoning and is being straightforward. First, we must

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attempt to find common ground from which we can gain evidence that confirms the truth of one or the other’s opinions, or second, we may appeal to what experts agree upon or what common public opinion holds. Only when we meet disagreement in what to believe, or meet rejection of our reasons for holding a belief, do we have to justify our own belief.

Objection: Agreement is Not the Same as Truth It seems too easy to concoct examples that show that truth cannot be the same as agreement even after two persons have been able to justify their beliefs publically by citing reliable methods. Assume Mr. Smith and Mrs. Jones act as independent witnesses in a trial where Mr. Brown is accused of being a thief. Both have seen Mr. Brown fleeing the shop after the robbery, and both are able to point to Mr. Brown in a lineup, because Mr. Smith knows Mr. Brown since they went to school together and Mrs. Jones was once married to Mr. Brown. But unbeknownst to both and to Mr. Brown, the latter has an identical twin who was adopted by another family just after his birth. Let us therefore assume that it was this twin brother Mr. Smith and Mrs. Jones saw running from the crime scene, but they agree that it was Mr. Brown. So not even agreement based on reliable methods gives us truth. There is no reason to dispute that truth is not identical to agreement, not even justified agreement. A group of people sharing the same belief may be as wrong as any single person can be. My point is that truth becomes a feature of propositional knowledge because the concept of truth originates as a standard of communication in order to establish an intersubjective goal for the agreement between the interlocutors. Agreement, even when justified, does not imply infallibility. But we cannot ascribe truth to a statement for no reason. In the example above the truth in the story is constructed from my or any other third person’s point of view. I have determined what counts as the truth relation in the story. In reality, nobody has the ability to judge the truth relation between proposition and reality with respect to a God’s eye view. When people have decided what this relation should be, we may then judge that the

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relation is not satisfied in this or that particular case.6 Everyone can only recognize this retrospectively as we reject someone’s assertion (which I did by making up the story). As long as everyone seems to agree about a particular belief, we have little motivation for refraining from ascribing truth to this belief. Today, it is common to talk about fake news, alternative facts, and conspiracy theories, because of social media. One way of distancing oneself from these social phenomena is to define “facts” as perspective-­ independent. Facts are objective, they do not depend on whether we believe them or not. But how do we determine who possesses perspective-­ independent beliefs, i.e. the content of which does not depend on the subject’s perspective? The immediate response would be to argue that those beliefs, which are or can be justified by adequate evidence, are true and therefore perspective independent. The problem is that justification and justificatory evidence very much rely on interpretations and that the act of interpretation always happens from a certain standpoint determined by a particular conceptual framework. This argument leads very easily to epistemic relativism. Therefore, one might conclude that one knowledge claim is as true as any others’ claim of knowledge, whether or not they agree. However, evolutionary naturalist does not necessarily imply relativism with respect to social epistemology. A way forward theoretically speaking is to introduce a principle of impartiality in which a third party who shares none of the disputed beliefs to judge which of the acclaimed evidence is most reliable. For instance, when President Donald Trump and all his proselytes challenged the U.S. presidential election in 2020, they went to court and an impartial judge had to decide the cogency of evidence in favor of the complainants and in favor of the official results. Although the Supreme Court of the United States ruled the case groundless (after many lower counts did the same), neither Donald Trump nor his dedicated supporters accepted these verdicts by a third party. In the minds of his audience, Trump’s political objectives were more appealing than the alleged facts of  In Experience and Beyond (2016) I argue that truth is a construction to the effect that there exists a descriptive correlation between a certain type of statement and a certain type of facts due to our observational ability to identify both independently of each other. See Faye, J. (2016), sec. 5.5. 6

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the matter due to their identification with what they imagined to be his political agenda. We may say that Trump’s speeches attempted to establish an emotional and an epistemic bonding between the speaker and the interlocutor, which excluded impartiality or made it very difficult to achieve. The American rhetorician, Kenneth Burke, has argued that such identification with this political rhetoric takes place along three dimensions of agreement: in terms of meaning by unconsciously aligning one’s symbol-­ system with the symbol-system of others, in terms of purpose by isolating a common opponent, and in terms of intention by applying sympatric symbols that predispose the audience to the rhetoric.7 These three forms of agreement induced by the former president’s speech acts make the audience believe what he asserts, even though the available evidence indicates much of this is not true. The perlocutionary effect of the various speech acts is the same regardless of whether the agreement is reached by reason or by identification with the speaker and his goals. The difference between the two cases is that in the first case the achieved agreement, if the previous circumstances were in a state of doubt or disagreement, occurs based on an impartial evaluation of which evidence is most reliable, whereas empathetic persuasion brings forward the second case of agreement.

Nothing But the Truth Central to the internalist approach to epistemology is the premise that propositional knowledge, i.e. knowing that such and such is the case, consists of beliefs whose truth must be justified by appropriate evidence. Everything that justifies a belief p, which S holds at time t, is the evidential states X, Y, Z, which S is in at time t. In other words, a belief p is justified by other beliefs X, Y, Z that act as evidence for p to epistemic subject S. For X, Y, Z to justify p, there must be a relation between these assumptions in the form of “fittingness”. This fittingness relation can be either  See, Burke, K. (1950). A Rhetoric of Motives. University of California Press, pp. 19–27, and 35–37.

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inferential or non-inferential. A similar justificatory requirement must be at work in the case of a naturalist approach, because nobody wants to say that what he considers to be misinformation can count as knowledge. However, internalist epistemology may subscribe to some further commitments, which Michael Williams formulates as four principles:8 • No Free Lunch Principle. Every epistemic justification must be a personal justification; it does not automatically flow to us, it must be earned through epistemically satisfactory behavior. • Priority Principle. It is never epistemically responsible to believe a proposition as true when one’s reasons for believing it to be true are less than adequate. • Evidentialism. Pieces of evidence are reasons consisting of propositions that count in favor of the truth of the believed propositions. • Possession Principle. For a person’s beliefs to be adequately justified, it is not sufficient that there is merely adequate evidence for it. The person who has a belief must himself believe (and make appropriate use of ) the evidence which makes the believed proposition likely to be true. Williams himself wants to uphold a conceptual relation between knowledge and justification in a less severe form in case one accepts what Brandon calls the Default and Challenge Model.9 This model allows us to deny that some of these commitments have to be satisfied in case no known interlocutor challenges someone’s beliefs. As long as I agree with your opinions, I have no reason to contest your beliefs and you are not required to defend yourself. However, this option is totally based on pragmatic grounds. Justification is still considered to be a defining part of what it means to have knowledge, and the person who is epistemically

 Williams, M. (2001). Problems of Knowledge: A Critical Introduction to Epistemology. Oxford University Press. Ch. 13. 9  See Brandon, R. (1994). Making It Explicit. Harvard University Press, and Brandon, R. (1995). Knowledge and the Social Articulation of the Space of Reason. Philosophy and Phenomenological Research, 55, 895–908. Brandon’s distinction owes much to the discussion found in Austin, J.L. (1961) Other Minds. In his Philosophical Papers. Oxford University Press. 8

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responsible must be able and prepared to provide adequate evidence for her assertion—if so asked. Of course, an externalist, like an evolutionary naturalist, rejects all four commitments tout court. His view is that there is no conceptual link between knowledge and justification. The demand that justification be built into the concept of knowledge is nothing but an attempt to meet the epistemological anxiety about skepticism. In contrast to the internalist, the evolutionary naturalist does not fear skepticism, thinking that skepticism is a real option only if there is a neutral place from which one can question the possibility of knowledge. But since the skeptic presupposes the conceptual framework of knowledge, which she is challenging, philosophical skepticism should not be taken seriously. Nevertheless, although justification is not a part of the naturalist’s concept of knowledge, it is part of the communicative practice as a general standard of solving disagreements that must be met in case one wants to keep the communication going. If our beliefs concern empirical matters, and some people either doubt what we report—or they would like to understand why we assert what we do—we must be able to justify our assertions in one way or the other. Only in order to reestablish agreements among the interlocutors is a justification needed. In recent epistemology, some philosophers, especially Alvin Goldman, advocated reliabilism as a position that avoids problems with evidentialism and allows a subject to have knowledge without necessarily being able to present evidence in its defense.10 However, the philosophical definition of reliabilism focuses usually on justification of beliefs that are either true or false. Besides propositional knowledge, we also have non-­ propositional knowledge such as different forms of experiential knowledge, whose appearance depends on the reliability of the adapted cognitive mechanisms that lead to this sort of knowledge. So let us for a moment leave ‘beliefs’ and ‘truth’ out of the discussion and talk just about the informational content of mental states. We may then say that a cognitive state M of an organism is a result of a reliable process if, and only if, the  A general theme in much of Goldman’s work around epistemology and social epistemology is Goldman’s exposition of reliability according to which knowledge merely requires to be acquired by a reliable method. See, for instance, Goldberg, A. (1986). Epistemology and Cognition. Harvard University Press, p. 51. 10

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mechanism that produces the informational content of M is successfully adapted to inform an organism about its environment and works properly. A reliable process or mechanism is one that with a high probability produces a cognitive state that consists of information about the world in any way that enhances the organism’s survival and biological fitness. Thus defined, reliability is not measured in terms of truth but in terms of adaptive success. Consequently, sensory and behavioral processes are normally reliable because their function is a result of biological adaptation. Likewise, storing and retrieving processes are usually reliable for the same reasons. Sensations are mental presentations, and if they present the environment, as they are adapted to do, they are reliable. If the production of a belief based on these sensations happens in accord with the adaption of the belief-forming mechanisms, then the content of the belief is reliable. The belief caused by such a mental presentation is not justifiable unless one is able to reflect upon the belief, which only humans can do to the extent of being aware of what one believes. The ascription of truth to beliefs goes well beyond their original function of providing an organism with an attitude toward the informational content of its experiences. Thus, I shall say, that sensory beliefs are reliable because the information, which conveys these beliefs, has been processed by mechanisms that have been naturally selected because they help the animal to survive and reproduce its kind, and the acquired information may in fact be beneficial for their survival. Unreliable beliefs, however, consist of information that has been processed by the same mechanism but where the acquired information is too sparse and therefore may decrease the animal’s prospect of survival. Since almost all of our sensory beliefs are reliable, no justification of them is required, and in those rare cases where such beliefs might turn out to be unreliable, they are corrected by other sensory beliefs. Animals may correct their sensory beliefs without having the ability consciously to compare them with evidence. This happens due to the qualitative changes in their sense impressions, and most of the time we may correct our misperceptions due to the same causes and not by consciously comparing them with evidence. At a distance, and in a foggy weather, I may see a cow lying in the field but close up I realize that it is a trunk. The change of belief does not happen in virtue of any rational justification, but

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because, given my changing sense impressions, my belief in the trunk, in contrast to my belief in the cow, continues to be stable over a longer period. A stable sensory belief automatically replaces an unstable sensory belief concerning the same object. However, no philosophers who have discussed truth and justification have done it in vain. They have failed with respect to identifying the epistemic situations to which the concept of justification apply. Having the capacity of imagination, we learn to reflect upon how things happen in the world and how our own thinking relates to the world. Moreover, we are also adapted to express these reflections in language. Thus, the combination of these two abilities enables us to develop very abstract or idealized ideas, which may or may not have their origin in an interpretation of experiential beliefs. These ideas may concern invisible or abstract entities, which we believe explain or describe visible and concrete entities. The epistemic problem with beliefs about invisible or abstract entities is of course that these entities are a product of human imagination and free reflection even though they are inductively anchored in what we know about the world through our senses. The content of the abstract beliefs, in contrast to experiential beliefs, is therefore only partly determined by mechanisms that are adapted to provide us with reliable information. As part of the social practice of ascribing knowledge to others, we have developed some standards of communication such as truth and empirical justification that have to be met if others should consider our opinions to be genuine knowledge. The notion of truth has evolved from language users agreeing about how to correlate different types of sentences with different types of observable states of affairs. Hence, truth can only function as a standard of communication as long as the members of a community are able to verify that in fact an appropriate correlation exists between particular claims and the things they assert. Beliefs agreed upon among the interlocutors are considered true as long as the agreement implicitly exists; beliefs about which they disagree require empirical justification to regain agreements. Indeed, not all disagreement between interlocutors need be over truth. Our propositional attitude is often “probable, but not known,” or of course they may disagree over the strength of the proposed justification. It is also

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possible to agree on the proposition, but hold it for different reasons, i.e. different justifications. Nevertheless, truth and empirical justification are socially evolved standards of communication, which constrain and tame free speculations, and to which we are committed in case we want others to accept our beliefs concerning knowledge of invisible and abstract entities.

Social Knowledge and Testimony Much of our common knowledge comes from the testimony of others, because they have witnessed something that we have not, or they have learned something that we have not. When we are young, these informants may be our parents or our teachers, but as we grow older, they may include acquaintances, friends, experts, or others whom we have no reason to mistrust. Hearing or reading what other people have to say about what they are knowledgeable about is an important source of human knowledge. Such testimonies are in a modern society just as significant a cause of knowledge as any personal perception of external or internal states of affairs. A testimony is impossible without coordination of communication and can be defined as a linguistic statement, or another form of communication, that intends to state a fact or pass on information. Whether we believe a testimony or not depends on several things. If the testimony agrees with our presumptions or our background knowledge, it has a much higher chance of acceptance. Likewise, if a person stating a testimony has a high status for persons in our ethos, like our parents, friends, or experts, the testimony will have a high probability of passing unquestioned until someone might challenge it. Already the great naturalist, David Hume, acknowledged that testimony is a source of knowledge, but he also believed that its trustworthiness had to be justified by empirical evidence and inductive inference. As he claimed, “The reason why we place any credit in witnesses and historians, is not derived from any connexion, which we perceive a priori, between testimony and reality, but because we are accustomed to find a conformity between

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them.”11 Hume’s claim has been interpreted as a kind of reduction, and C.A.J. Coady, known for his ground breaking work on testimony, directly calls it Hume’s Reductionist Thesis.12 According to Coady’s interpretation, Hume says that the testimonies require empirical justification to make sure that they are reliable in the sense that we can experience a regularity between a testimony and the fact which this testimony reports. However, Coady wishes to contest the Reductionist Thesis by putting forward two objections. First, the experience Hume talks about may refer to that of individual observers, but in this case, the claim would be false. Through individual observation of another person A and the way the world is, no one can obtain sufficient evidence to be able to prove that since in the past there has been a reliable connection between A’s reports and the way the world is, then A’s reports in the future will be truthful. In many cases, we have never proved that the world is in the way that A’s testimony tells us, but this we may still trust. Second, the experience Hume talks about may refer to one of a community of observers such that the recipient of the testimony assumes that others’ observation reports are true. In this case, Coady rightly thinks that the claim involves an infinite regress, because other people’s observation reports are also testimonies whose justification presupposes still others’ observation and so on. As an alternative theory, after a lengthy discussion of the relationship between testimony and meaning, Coady posits that there is an a priori connection between statements expressing testimony and the world to which these statements relate (thereby making those statements true or false). The argument is the following: If we do not know the meaning of a statement, then we can also not determine whether the statement conveys a testimony. The a priori connection is shown precisely by the fact that we cannot use experience (as if it had been an a posteriori statement) to show that such a connection does not exist. Therefore, Coady’s claim is that we cannot understand what a testimony is unless we do  Hume, D. (1777/1966). An Enquiry Concerning Human Understanding. Second Edition by L.A. Selby-Bigge. The Clarendon Press, p. 113. 12  Coady, C.A.J. (1973). Testimony and Observation. American Philosophical Quaterly, 10, 149–55. Reprinted in S. Bernecker & F. Dretske (Eds.), Knowledge: Readings in Contemporary Epistemology. Oxford University Press, 537–546, p. 538. 11

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understand that a testimony in and of itself is reliable evidence of what the world is like. In other words, it is part of our concept of testimony that it, by its meaning as a sort of a speech act, indicates what is true about the world. A testimony has the power to be an independent source of justification in agreement with empirical observation itself. So there is real social irreducible knowledge. How can a naturalist make sense of testimonies without denying testimonies a specific justificatory role? The first step is to acknowledge that testimonies do not directly express how the world is but what a person who makes a statement believes about the world (assuming he is not deliberately lying.) A person’s empirical beliefs may stem from others’ testimony, but all their empirical beliefs are in the end directly or indirectly attached to sensory experiences. Even if the person is honest in his or her reporting, the statement could still be false. And if it is false, some other reporting based on more reliable experiential evidence must contradict the testimony. Moreover, in contrast to Coady, I think it is reasonable to say that, through experience, we learn that testimonies are attributed an independent justificatory role and that, through experience, we also learn whenever we should not trust an alleged testimony. However, we do not justify an alleged testimony by direct comparison with relevant evidence. Rather we consider a testimony to be justified as a source of knowledge if someone to whom we ascribe a great deal of authority states it, because we have learned that we often agree with that authoritative person and we think that he or she has no reason to be dishonest. In my opinion, Hume was more sophisticated in his view than the normal interpretation of him allows. For instance, he apparently admitted that in many social circumstances we take testimony to have an independent justificatory role or to express knowledge directly. Which circumstances we are talking about depends very much on the discursive situation. This is what Hume says: Were not the memory tenacious to a certain degree, had not men commonly an inclination to truth and a principle of probity; were they not sensible to shame, when detected in a falsehood: Were not these, I say, discovered by experience to be qualities, inherent in human nature, we

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should never repose the least confidence in human testimony. A man ­delirious, or noted for falsehood and villainy, has no manner of authority with us.13

In other words, Hume argued that every one of us has discovered that most people are trustworthy most of the time and for that reason alone, we are ready to rely on the statements of other people as reliable testimonies and consider them to express knowledge or to be a source of justification of our own beliefs. He also explains why each of us has learned that most people are trustworthy most of the time. The truthfulness is due to human nature: it is part of our psychology to be mostly honest when we speak with other people. However, the truth is that Hume’s naturalistic defence of testimony as a source of knowledge is questionable for one important reasons. The “us” in the quotation above refers to straightforward educated British gentlemen, not to the great mass of humanity who not always care one wit about honesty. Time after time politics proves that very many people will believe testimony from individuals who are both dishonest and villainous, because these people emotionally want to believe those individuals. Hume can hardly be taken as the rule for humanity at large, no matter how correct his philosophy might be. Apparently, there is nothing in Hume’s view that would have excluded him from subscribing to Tyler Burge’s claim that “a person is entitled to accept as true something that is presented as true and that is intelligible to him, unless there are stronger reasons not to do so.”14 Again, this statement seems to assume that people believe what they do for evidential reasons; whereas the fact is that people often believe what they do for emotional reasons and that evidence and rational argument are persuasive only to that minority who are called philosophers or scientists. The explanation is that testimony about social matter concerns entities that are linguistically constructed and that the empirical beliefs we have about these entities rest very little on experiential evidence. Whether an election is stolen is not something anybody can see by his or her own eyes. So all  Hume, D. (1777/1966), p. 112.  Burge, T. (1993). Content Preservation. Philosophical Review, 102, 457–488, p. 457.

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those people who emotionally want it to be true think it is true when someone whom they already admire says so. That puts restrictions on testimony as a source of knowledge. For a naturalist the attribution of entitlements to any person is not based on a priori insight into how testimony is connected to the world, but is based on empirical knowledge learned by observing people’s behavior and their use of language. The entitlement follows from how language has been adapted to express human beliefs and desires and our natural habit of trusting other humans in order to survive. Then, of course, it is true that communication would be impossible unless the overwhelming majority of people speak the truth most of the time. However, this is a contingent fact that depends on the fact that language evolved as a means of expressing our beliefs and wishes in order to be able to share them with others. But regardless of whether or not we are taking about linguistically constructed social facts, we are not entitled to accept as true any testimony given by a person whom we trust unless it can be traced back to common evidence based on experiential knowledge. Summing up, I hold that every normal human being is taught by experience what other human beings are like, and how they use language for different purposes. This is essential knowledge for the individual’s survival in a society. Therefore, social knowledge is no less a natural phenomenon than our knowledge of the physical world in spite of the fact that social knowledge, in contrast, is highly culturally relative and applies to one group of people, but not necessarily to another. Higher animals living in social groups need to trust each other in that group more often than not. A vervet monkey’s alarm call functions as a testimony. Young monkeys learn what such a call means and older monkeys are entitled by practical success to accept it as reliable, until, as we have seen, they discover that the caller is unreliable because he or she wants to benefit from his or her misleading the group. The learning process in virtue of achieving practical successes establishes what we might call a natural habit. A natural habit is a regular behavior or a set of behaviors that is learned, because by learning it, normally an organism and its offspring will survive more effectively in their environment. The conclusion we may draw from the fact that alarm calls act as testimonies among monkeys—because they have a meaning (they are not

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merely sound signals), and this meaning is learned by each new generation—is that the relation between the call and a predator is not known a priori. Coady’s argument against Hume operates with the wrong idea that individual animals and humans need to observe the relation between a testimony and the world repeatedly in order to have confidence that the message and the messenger are reliable. Natural selection and adaptation secure that higher animals living in complex groups do so for collaboration—a collaboration that depends on the ability to trust as much as the ability to exercise strength. And if you genetically are equipped with the ability of trusting those to whom you are emotionally and socially bonded, you need not observe their behavior repeatedly in the past before you greet their testimony with confidence.

Knowledge Beyond Empirical Beliefs Apart from experiential and empirical beliefs, modern human beings also have theoretical beliefs. Where empirical beliefs concern properties of observable things, properties that are not immediately visible such as dispositions and regularities in the succession of visible things, theoretical beliefs are about entities that are not directly observable. The liberating function of language is that it enables us to think about matters we can only imagine, and to construct and organize our thinking of the physical world around us in new ways. It gives us concepts of understanding the world we have not had before. The evolution of language furnishes human beings with further capacities of believing and understanding that depend on the rise of self-reflection and social commitments. However, the basic function of language still emerged from reporting and communicating experiential beliefs. This claim explains why traditional epistemology as a normative enterprise has thought of human knowledge in terms of justified true beliefs. But many of our beliefs go beyond our sensory and behavioral experiences in virtue of being part of our social, scientific, and religious understanding of the world. And we know from experience that the invisible objects to which we refer in these beliefs may not actually be as they are believed to be. Consequently, we need some measure by which we can judge whether unobservable things are as believed.

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However, there is linguistically no difference between expressing a belief concerning visible or invisible matters. Philosophers have had no difficulties conceiving the felicity conditions governing speech acts expressing beliefs about experiential things and then extend them to speech acts concerning beliefs about unobservable things in order for these beliefs to amount to knowledge. Traditionally, philosophers have made such an extension in order to treat all versions of knowledge uniformly, hoping that they could meet various skeptical arguments. Explicating sensory knowledge in terms of justified true belief was a reasonable undertaking, until science learned about fitness, adaptation, and natural election. But is it still a maneuver that the naturalist must explain, and if so, how can the naturalist explain it? From a naturalist standpoint, an experiential belief is reliably acquired if the sensory content of this belief is reliably obtained, precisely because those mechanisms that process this kind of information are adapted to functioning such that the information increases the individual’s fitness. Thus, an organism reliably obtains an experiential belief if this belief increases the probability of the belief–acquiring organism’s survival (or its progeny). Furthermore, an experiential belief is true only if this belief is reliably obtained in this manner and only if at some point in human history we have correlated the same kind of beliefs with a certain type of expression such that we could report our belief in a regular manner. So the naturalist explains the social origin of the concept of truth as a linguistic notion we have derived from intersubjective communication on what it means to state something really is as it is believed to be, in contrast to stating that something is as it is not believed to be. The reliably obtained beliefs are, then, those beliefs we appeal to whenever we want to fix the empirical criteria for securing a reference for statements that truthfully express our beliefs about non-perceptual things. The justification of a particular belief concerning invisible things consists of nothing more than the common assent by the community as a whole. No single individual can have justified true belief in isolation. The common assent concerning invisible things amounts to a mutual agreement about how to understand the observational evidence that everyone in the community holds to be true. We appeal thereby to various forms of social understanding such that what someone believes agrees with

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others’ beliefs of similar sorts. A belief concerning invisible things is justified if, and only if, it agrees with similar beliefs of others and these shared beliefs rest on some experiential beliefs that everyone holds to be true. A prompt reaction to this proposal would be to object that people at some point have agreed on various invisible things, which have since been shown not to exist. Think of demons, witches and other trolls. When people could gather around a belief in these things, they mutually agreed, but they were not justified in the truth of their belief. This is true, but on my account, these people were justified in their belief even though we agree today that things like demons and witches do not exist. This lack of truth is retrospectively due to our common denial. The evidence they interpreted as signs of demons and witches nowadays we understand otherwise. So justification in terms of agreement among experts or scientists is possible only because all their beliefs about invisibles are products of our capacity of using language for descriptions, and the intentional use of descriptive assertions is to refer to something the sentences presumably represent. Language offers a means of defining concepts of things we cannot see and its open structure generates understanding, which, on the one hand, reflects some cognitive mechanisms of self-awareness, and, on the other hand, expresses some common ways of understanding. Cognitive schemas determine the linguistic skills we need to perform valid inferences, and our self-correcting awareness produces a reflective understanding that is manifested in how language is used. Therefore, in human history people sometimes change their shared view about invisible things by coming to an agreement that the evidence that previously justified one’s speaking about a specific kind of invisible thing (because at that time  everyone agreed about the interpretation of this evidence) should now be taken as evidence for speaking about another kind of thing. Various speech acts convey different sorts of reflective understanding. For instance, apart from descriptions speech acts give us the possibility of raising questions and posing answers. In my view, the purpose of an explanation is to provide the explainee with understanding of the explicandum, although not necessarily with knowledge. Offering explanations show our ability to answer questions, and this capacity draws on our ability to connect a particular belief intentionally with other beliefs.

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Explanation consists of consciously relating the expression of an unaccounted belief with a body of beliefs the assertion of which allegedly has explanatory force. The same holds, mutatis mutandis, for other sorts of reflective understanding such as interpretative, theoretical, and metaphysical comprehension. Each of them involves a body of organized beliefs that allows the holder of such a body of beliefs to involve him- or herself in different forms of language use. Given that theoretical beliefs go beyond human experiences, in order for theoretical beliefs to achieve the status of knowledge, it is a reasonable epistemic requirement that these beliefs about invisible things require special attention different from our beliefs about visible things. Beliefs about invisible states of affairs are not directly formed by the cognitive mechanisms that have been adapted by natural selection to yield sensory information. In contrast, our sensory knowledge consisting of experiential beliefs is the product of these cognitive mechanisms. Our empirical beliefs are somewhere in between experiential and theoretical beliefs. Language not only enables us to define the content of empirically justified beliefs, but language also defines what satisfies those predicates the extension of which exceeds what we can directly see with the naked eye. The content of people’s empirical beliefs thereby supersedes the content of their experiential beliefs. Therefore, in order to establish and exchange their beliefs as social knowledge, language use requires people to accept some commitments of communication such as achieving agreement among the participants about the truth of their empirical beliefs. However, science is the primary source of theoretical beliefs about invisible entities, although religion have produced quite a few, and in terms of sheer numbers of believers, these entities have probably been believed in more often than those of science. But unlike scientific beliefs, religious as well as political beliefs are maintained for emotional reasons rather than evidential ones. In the next chapter, we shall investigate how science as a social enterprise fits into the epistemological framework of evolutionary naturalism.

8 Science and its Epistemic Limits

Many people consider science and technology to be the highest attainments of human thinking. The fact that humans have been able to gain systematic insight into nature shows how far superior our ability to acquire knowledge is in comparison to the abilities of our closest relatives. For some people this even demonstrates that the power of our intellectual aptitude is no longer limited to knowledge of visible objects but includes an ability to have knowledge of invisible entities and abstract objects as well. According to these people, human language and mathematical skills have liberated our social thinking from its evolutionary origins such that science, as the most conspicuous example of social achievement, constructs mathematically formulated theories about things far beyond our senses that reveal the structures of the world in and of itself.1  An example is Ladyman, J., & Ross, D. (2007). Every Thing Must Go, Oxford University Press, where one finds the following statement: “As collective constructions, the institutional filters of science need not mirror or just be extensions of individual cognitive capacities and organizing heuristics. They have shown themselves to have a truth-tracking power—partly thanks to mathematics—that bootstraps the process of scientific learning beyond the capacities of individual minds. Furthermore, the limitations on the sorts of heuristics we must use for doing special sciences arise not from limitations of the kinds of minds we have, but from the irreducibly asymmetric nature of the local spacetime in which all our measurements must be taken” (p. 300). 1

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The previous chapter argued that the intersubjective goal of impartial agreements among people about their empirical beliefs was to reach a common acceptance of these beliefs as true. With respect to theoretical beliefs this seems to indicate that if people imagine this or that invisible entity and they agree that all empirical evidence supports the existence of such an entity, they are justified in believing in the existence of that entity and that the theoretical representation of it is a true description of that entity. Therefore, if scientists in general come to an understanding of realism about scientific theories, we seem to have overwhelming reasons to maintain that scientific theories, which we consider as true or approximately true, are assertions of our theoretical knowledge. But without some constraints on what we can know based on scientific theories, one may come to believe that “the fundamental ontology of the world consists of a vector in Hilbert space evolving according to the Schrödinger equation.”2 In this chapter, I shall look into science as the generator of theoretical knowledge of the empirical world. Not only has science been able to describe our physical environment in terms of mathematics, or so it seems, but technological advancement has also enabled scientists to penetrate deep into the nature of matter and disclose things we cannot see with the naked eye. From the standpoint of evolutionary naturalism, one may wonder how this is possible. I maintain that it is possible. Thus, I argue that scientists have theoretical and practical knowledge about the existence of invisible but observable entities, but reject that scientific theories by themselves express such knowledge. My starting point is human evolution and the cognitive restrictions I believe our adaptations have imposed on our ability to know what we cannot experience. Since experience is not limited to discrete visual sensations but also includes bodily sensations, our own behavior and its technological extension are just as much a part of our ability to attain knowledge as visual perception. Therefore, I think we have knowledge of invisible physical objects such as atoms because of our practical interactions with them, but we have no knowledge of abstract objects like numbers or universals. Consequently, I reject the position that  The quotation is from Carroll, S.M. (2021). Reality as a Vector in Hilbert Space https://arxiv.org/ pdf/2103.09780v1.pdf 2

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theoretical knowledge includes knowledge of abstract entities. Scientific theories do not express our knowledge of nature but, I will argue, set up a vocabulary, and define the linguistic rules for how it should be used to speak about our experimental observations. In contrast to scientific realism, I hold that just as the evolution of the cognitive capacities of our brain has determined the scope of our everyday experiences, human adaptation to the environment also controls the biological space for scientific thinking. Nonetheless, the science community and the philosophy of science community often ignore the fact that the adaptation of our cognitive faculties to what exerted a selective pressure on our predecessors may narrow the possible range of human knowledge. Since the influence of logical positivism has dwindled, most scientists and philosophers of science have operated on the basis of the assumption that our best scientific theories represent the world and that such theories understood as true or approximately true literally express our knowledge about reality. Only few contemporary philosophers have expressed their doubts concerning this approach to science.3 Here I shall argue that representationalism is implausible given that the natural

 Indeed, the classical example of the opposition to representationalism in the modern era is not van Fraassen, B.C. (1980). The Scientific Image. Clarendon Press, as one might have thought, because he still holds that scientific theories are either true or false, even though we are epistemically unable to establish their truth-value. Another anti-realist Wray, K.B. (2018). Resisting Scientific Realism, Cambridge University Press, concedes the empirical success of science but is skeptical “about our alleged knowledge of the unobservable entities that are posited to account for the phenomena,” p. 204. However, people like Cartwright, N. (1983). How the Laws of Physics Lie. Oxford University Press, and Hacking. I. (1983). Intervening and Representing, Cambridge University Press, consider themselves as entity realists, although they have partly rejected representationalism concerning theories. A recent defend of anti-representationalism is Rowbottom, D.P. (2019). The Instrument of Science. Scientific Anti-realism Revitalised. Routledge. In his book, Rowbottom argues convincingly that the goal of constructing a theory is not to provide scientists with a theory with high verisimilitude. Instead, a theory supplies them with eminent predictive power and with an understanding of the phenomena. Similarly, Plotnitsky, A. (2021). Reality Without Realism, Springer, offers a view according to which the interaction of the measuring instruments and the quantum objects produces the quantum phenomena such that “the ultimate constitution of reality responsible for them is placed beyond representation or even conception, thus making this reality a reality without realism.” (p. ix). In contrast, Johansson, L.-G. (2021). Empiricism and Philosophy of Physics. Synthese Library 434, Springer Nature—although he expresses the same non-representational attitude to the laws of nature as I defend in this chapter—also subscribes to the collapse postulate as if superposition of the wave function represents a real physical state. I personally think this does not fare well with his empiricist position. 3

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selection of our cognitive capacities has designed them to understand what we can observe, not what we cannot observe. Consequently, I hold that scientific theories are in general neither true nor false and therefore do not express either how the world is or our knowledge of it. Instead, we should consider scientific theories as consisting of a vocabulary and explicit rules for using this vocabulary by which scientists can express their beliefs and speak about their observations with reference to visible or invisible entities in an interpretive model.4 The situation in science is not much different from the one in everyday life. A natural language consists of a vocabulary and many implicit or explicit rules for using this language. The main difference is that in science scientists (sometimes) explicitly state these rules, because they have themselves made them, but in everyday life, we need linguists to unravel those rules. It is, I argue, only when scientists make concrete assertions about empirical phenomena that it makes sense to ascribe a truth-value to such utterances. Of course, we meet several forms of practical and theoretical knowledge in the sciences, but the quantitative laws of scientific theories do not express any of them. The practical knowledge we meet in science is comprehensive but easy to overlook. It ranges from knowledge concerning how to manipulate various formalisms and how to apply these formalisms to an interpretive model in order to describe a particular object of study, to knowledge about how experiments function and how to act such that the instruments yield an experimental result that is acceptable to the community of specialists in that scientific discipline. It also includes the capacity to speak the relevant language of a particular science properly and to determine what is relevant in a given context. All these scientific abilities are skills that scientists learn by training just as those skills people acquire when they learn ordinary forms of craftsmanship. The  For a long time I have advocated the view that the basic laws of science that express relations between physical quantities are nothing but explicit linguistic rules or definitions that prescribe how we should describe physical objects in a model in order to tell how and why these entities behave as they do. See Faye, J. (2002/2018) Rethinking Science. An Introduction to the Unity of Science. Routledge, Ch. 8; Faye, J. (2014). The Nature of Science Thinking. Interpretation, Explanation and Understanding, Palgrave Macmillan, Ch. 4; and Faye, J. (2016). Experience and Beyond. The Outline of a Darwinian Metaphysics. Palgrave Macmillan, Ch. 4.7. 4

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theoretical language is only part of science, just as a language is part of a culture, but a culture is much more than a language. Scientists then acquire theoretical knowledge by performing those skills in connection with their assumptions concerning the objects of study, assumptions about ruling principles, mechanisms, and the nature of the entity.

 hat Are We Adapted to Know, and What W Are We Adapted to Understand? Generally, science uses two cognitive methods in order to gain insight into nature and human beings. One is the inductive-hypothetical method that empiricists roughly consider the foundation of all scientific practice, and the other is the hypothetical-deductive method that rationalists usually praise. Throughout history, there has been a tug of war between these two camps. Nowadays, there are those who believe that theory construction happens “bottom-up” from physically observed regularities, but many others believe in a ”top-down” approach in which physical theories are mathematical constructions based on certain abstract principles. I suggest that science uses both methods, but that the inductive-­hypothetical method delivers empirical and theoretical knowledge, whereas the hypothetical-­deductive method generates explanatory hypotheses. Indeed, how we verbally explicate these methods is the result of conscious reflection on our inherited cognitive practices of reasoning between the process of observing, educated guessing, hypothesizing, and observing again. Before constructing any explanatory hypothesis concerning our observations, we have to make an inductive abstraction of concepts by which we grasp these observations.5 In order for such a construction of new concepts to make sense, they must rely on the experience-based concepts we already have. However, starting from above with a mathematical formulation of a hypothesis one needs a physical interpretation, and if such an interpretation should not be vacuous as a theoretical  I very much agree with Johansson, L.-G. (2021), p. 4. He and I have for a long time agreed that scientific laws are either implicit or explicit definitions, although we disagree with respect to their truth content. These issues will be dealt with later. 5

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explanation, it has to be such that some observational consequences can be deduced from this formulation, given prescribed initial conditions. Sensory or experiential knowledge is the most basic form of knowledge upon which empirical and theoretical knowledge have developed and upon which their justification rests. However, science has discovered that organisms, including human beings, gain knowledge in no other way than through their senses. Therefore, I shall argue that we may consider observational instruments as a prolongation of our sensory modalities and experimental data as empirical information about indirectly observable entities. As a result, I hold that theoretical knowledge is nothing but empirical information concerning the properties of visible or invisible, but instrumentally observable, entities, as this information is understood in the terms of a scientific theory. On the one hand, our ability to abstract and make inductive inferences helps us to obtain empirical knowledge from experiential knowledge. On the other hand, our ability to reflect on our empirical knowledge and invent new concepts concerning things that are not directly visible, as a qualified response to such contemplations, may provide us with theoretical knowledge. However, I shall also argue that this sort of theoretical knowledge is distinct from scientific understanding. I maintain, as previously argued, that understanding is a cognitive organization of beliefs or sensory information. This means, if my view is correct, that animals have understanding in the form of concepts and in the form of expectations even though they have no language. Of course, human understanding improved immensely with the evolution of a verbal language, but understanding is evolutionarily older than language. Language enables us to formulate new beliefs based on experiential information such that our empirical knowledge transcends what we came to know from the senses directly. But language also facilitated our imagination of entities that people could not see and allowed them on some occasions to agree about the existence of such invisible entities. So when human beings developed mathematics, they gained a new language in terms of which they could ascribe to such invisible entities quantitative properties and numerical relations with a precision never seen before. However, I would like to add that just as human experiential knowledge as a consequence of the evolution of language expanded into

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empirical and theoretical knowledge so has language helped humans to formulate aims and intentions such that its repertoire of experiential knowledge has increased with performative and operational understanding. I shall define performative knowledge as the acquired ability to engage in proper actions with the intention of realizing empirically formulated aims, while operational knowledge is the learned ability to accomplish actions that involve instruments with the intention of realizing some theoretically defined aims.6 The evolution of empirical knowledge has influenced the development of performative knowledge which in and by itself has had an impact on the evolution of empirical knowledge. Similarly, operational understanding presupposes both theoretical knowledge and performative knowledge, which again involves behavioral and actional knowledge. We cannot understand empirical and theoretical knowledge separated from performative and operational knowledge. These versions of knowledge are dynamically interdependent but analytically distinct. Now, inductive inference seems to be the main cognitive process behind the construction of any form of concept-based knowledge that is formed on external sensations and bodily movements. Inductive inference automatically occurs whenever an animal unconsciously develops a conceptual understanding of parts of its environment. The animal’s ability to compare earlier sensations with later ones is a precondition for such an understanding. As long as we consider an animal’s sensory beliefs, it seems that the conceptual identification that makes such a belief possible could not occur unless the animal already possessed the relevant concept. Forming such a concept is often attributed to a process of abstraction from particular sensations, but I hold that the process of abstracting is nothing but the mental process corresponding to an ampliative inference like induction or abduction. Sensory concepts are the outcome of simple enumerative induction that constantly operates on our sensations as we 6  In his book, Chang, H. (2022), Realism for Realistic People, Cambridge University Press, Chang argues that science should focus on operational knowledge and scientific practice just as much as propositional knowledge in order to grasp theoretical concepts and their developments. I very much agree. However, I also think we can explain the reason for that by the origin of human cognition. Furthermore, the way I categorize these things, performative and operational knowledge are specific forms of practical knowledge.

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learn to master novel concepts due to the unconscious cognitive mechanism of induction. Remembering similarities and dissimilarities of a series of particular sensations may generate in both human and non-­ human animals an understanding that the recollected sensations have noticeable similarities in common, such that these sensations are classified as a recognizable type. There can be no sensory concepts without simple induction. Most empiricists probably think that Hume’s critical analysis of induction established once and for all that inductive inferences cannot be proved to be universally valid. Any attempt to validate induction will somehow appeal to something we already believe true on the basis of induction or appeal to dogmatically postulated general principles or would involve an endless justificatory regress. So how can it be true that the acquisition of knowledge as a biological phenomenon has advanced based on inductive inferences in spite of the problem of induction? Perhaps, John Norton has suggested some of the answer: “In a material theory …, inductive inferences are warranted by facts. A simple example illustrates this central idea. We can infer inductively from the evidence that some samples of the element Bismuth melt at 271 °C to the universal conclusion that all samples melt so. The warrant is a fact about chemical elements”. But he also points out that “According to that theory all inductive inferences are warranted by facts. Since these facts are contingent, there are no universal warrants. No system of inductive logic holds universally; each holds only in the limited domain in which the warranting facts are true.”7 Of course, warranted facts are indeed inductively justified facts, which again are justified by further inductive inferences and other warranted facts. However, Norton disputes that this means that the material theory of induction falls victim to a regress objection either diachronically or synchronically. I propose that induction needs no justification in general. An organism’s capacity of making inductive inferences prevents its species from extinction. Not even in science does a factual statement need any inductive justification as long as members of the community agree with the  Norton, J.D. (2014). A Material Dissolution of the Problem of Induction. Synthese, 191, 671–690, p. 673 and p. 674. 7

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statement. Norton observes that the justification of serious inductive inferences in science becomes stronger and stronger the more we can appeal to our knowledge of already established scientific facts. But this holds only in case scientists face disagreement. In a situation of mutual disagreement, scientists may want to justify their own assertions by an appeal to what the community takes to be true. The same holds for our everyday knowledge, which is a result of cognitive engagement with the world. Of course, any ampliative inference involves a risk, but it is always local in the sense of not casting doubt upon our entire body of knowledge, and the risk becomes less the larger this body is. We should also recall that the failure of inductive inferences to be deductively valid is something we have realized after we have formalized inductive and deductive inferences. In practice, people use inductive inferences such that if they realize that their induction went wrong, such an awareness happened only against a background of inductively well-established knowledge. Even in science, various forms of induction play a major role in formulating hypothesis and theory building to which scientists may appeal in their criticism of other inductively established assumptions.8 As an evolutionary naturalist, I hold that the neuro-cognitive mechanisms behind inductive inferences, of which we certainly are not aware, and we therefore need not be conscious of making, establishes the capability of making inductive inferences as an innate ability. As an innate capacity of obtaining beliefs, it does not make sense to claim that inductive inferences should be justified as a rule. In general, justification does not make sense, because the physiological mechanisms behind induction are the automatic results of cognitive adaptation in non-human animals. These mechanics are a fitting cognitive means to acquire sensory knowledge of the environment that our forebears phylogenetically inherited. In nature, inductive inferences are essential parts of an animal’s cognitive machinery of learning, by which it creates sensory concepts and reaches sensory knowledge of events in its surroundings. However, there is arguably a difference between sensory knowledge and empirical knowledge  In a recent book, Slobodan Perović (2021), From Data to Quanta, Niels Bohr’s vision of Physics, Chicago University Press, argues that Bohr in his work on understanding the atom used various forms of induction based on his knowledge of the experiential practices of formulating various hypotheses about the atom and to construct quantum theory.

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here. A child needs to experience a hot stove only once to realize that the experience is painful. No inductive generalization is required because the strong feeling of unpleasantness does not require reflective considerations as long it is remembered. But empirical knowledge does. Induction provides some animals with useful empirical beliefs, but induction also provides these animals with information, if their empirical beliefs are not workable. (The revision of empirical beliefs demands more than one observation to convince any inductive agent.) Inductive inferences rule the whole process of acquiring empirical knowledge in an individual organism from the newborn to what remains of its life. The use of induction to understand particular specimens is in need of justification in common life and in science only if other members of the community call such an inference into question. Hence, I shall propose a distinction between non-reflective inductive thinking and reflective inductive thinking. The first form happens automatically outside any conscious attention, the second form happens guided by such an attention. Non-reflective inductive thinking works on sensations and delivers sensory concepts and sensory knowledge. It partly extends sensory beliefs beyond what the organism observed here and now. It thereby helps an organism to conceptualize parts of its environment and helps this animal to form beliefs about what it actually experiences. Non-reflective inductive thinking does not carry an animal’s knowledge any further than what it is capable of observing, because such an inference operates not by conscious awareness. Instead, it functions resting on the same neurological mechanisms by which many animals obtain concept-based sensory knowledge. As we have also observed, higher non-human animals possess not only sensory knowledge, but to a certain degree, they possess empirical knowledge as well. To the extent that non-human animals possess empirical knowledge, they must be able to develop beliefs that do not entirely rest on direct sensations. This requires a rudimentary capacity of reflection that gives an animal the ability to imagine what itself, or other animals, are doing that is beneficially or non-beneficially to itself. It would be impossible to teach chimpanzees and bonobos’ sign language if they were not able to reflect upon their own or others’ behavior and observation. (Indeed, this capacity does not require that they can pay attention to their own

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reflections.) The fact that behavioral signs of the great apes are meaningful is a mental property associated with these signs, which orphans learn to understand in connection with seeing these visual signs. Moreover, the great apes also obtain empirical knowledge by displaying the ability to make analogical inferences. Thus, evolution has provided at least the great apes with a capacity of thinking beyond what their sensations directly reveal. Also reports about various species of corvids, jays, and magpies, and other mammals such as elephants, dolphins, and orcas, indicate that they are capable of analogous thinking just like the great apes. Therefore, these, and probably several other animals, possess a certain amount of empirical knowledge. Indeed, any concept formation in animals presupposes some cognitive mechanisms that allow them to exercise relational and analogical thinking by comparing actual sense impressions with memories of sensations experienced earlier. So my conclusion is that inductive inferences occur in the acquisition of all versions of knowledge and that only in those cases in which humans reflectively  make different inductive inferences about the same topic, or challenge an inductive conclusion, does it make sense to demand evidential justification.

 he Introduction of Invisible T But Observable Objects What is it like to be a bat? We do not know by experience, as Thomas Nagel pointed out, although we may speculate.9 I raise this question not because I believe Nagel is correct in his suggestion that it shows that sensory experience is not explainable. I think not. I pose the question because it illustrates quite well that biological evolution has selected the manifest world of human beings very differently from that of bats, which we as humans therefore cannot know anything about because we have no access to the consciousness of a bat in order to know it directly. Here I use the phrase “the manifest world” to refer to how the world appears via its senses to a human or to a non-human animal. Human beings and bats have adapted in different ways to their environments. None of their  Nagel, T (1974). What Is It Like to Be a Bat? The Philosophical Review, 83(4), 435–450.

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different ways of experiencing is closer to a correct presentation of the environment. These manifest images are just presentations that are well adapted in the sense that they help individuals to survive. A manifest image presents the world as it appears to a particular species. Many realists think that the image of the world provided by natural science has moved beyond the manifest image and provides us with knowledge of how nature really is. The image or images science puts together stem from scientists’ ability to explore nature in the terms of concepts that stand for unobservable entities. According to these realists, the images science develops in this manner provide us with theoretical representations of the real world, and it is in virtue of such an alleged reality that we may explain what is observable within the manifest image. For my part, I join those antirealists who view theories as conceptual frameworks that enable us to understand observations and experiments. The purpose of theories is not to offer a true or approximately true representation of the world but to give us a means to speak about our observations and to conduct experiments in an intelligent manner. From an evolutionary standpoint, theoretical knowledge as much as empirical knowledge has a practical function of bringing consecutive observations together. It helps to understand that if one observes this phenomenon, then one can expect to observe that other phenomenon, or if one makes that kind of experiment, this will probably happen, or if one uses this mathematical tool to predict the behavior of a particular phenomenon, one can anticipate that kind of result. The challenge antirealists have to address is that if we should not give our best scientific theories a literal interpretation and thereby claim that they present at least some of our knowledge of the world, it seems inexplicable why scientists postulate the existence of invisible entities as part of the scientific image. The answer is as simple as it is complex. Observable entities may be invisible. Visibility depends on our sensory physiology, whereas observability can make use of technological means of extending those senses into domains that we humans have not been adapted to sense. What is invisible, like dark matter and dark energy, may eventually be made observable by technological means, but until then the existence of these unobservables is hypothetical. Thus, I contend that true beliefs in the existence of concrete invisible but observable entities such as atoms

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or black holes are not a result of theoretical conjectures but of instrumental observation even though such “observations” require a great deal of theoretical assumptions in order to interpret the data as observations of atoms or black holes. Speculations about atoms have a long history, but not until modern chemistry with Lavoisier appeared in the late eighteenth century did the concept gain an explanatory function in the description of chemical processes. In 1789, when Antoine Lavoisier formulated the law of mass conservation during chemical reactions, and in 1799, when Joseph Louis Proust formulated the law of constant proportions, the speculations about these invisible elements gained solid empirical evidence. Lavoisier found that the mass of the substances formed by a chemical reaction has the same mass as the substances that were present before the reaction. Thus, there seemed to be a constant over change that ensures the preservation of mass during the chemical processes. However, this quantitative relation was not the only thing thus discovered. Chemists had also discovered that there were basic chemical elements of which the chemical compounds were composed. Then Proust proposed that any chemical compound contains the basic chemical elements in a constant mass ratio that is characteristic of just such a compound. The first to put forward a truly modern theory of atoms was the British chemist, John Dalton. Faced with the outcome of a series of experimental studies of gases, he concluded that the basic elements consist of tiny particles—atoms that could not be created, divided, or destroyed during the chemical process. Each chemical element consists of the same atoms; different elements consist of different atoms, which are distinguishable from each other by their relative weight. The atoms of each element combine with the atoms of other elements to create chemical compounds. So what changes during a chemical reaction is the composition of the compound made of atoms. Hence, chemists had provided the scientific world with a theoretical hypothesis that all matter consists of atoms. Nevertheless, chemists and philosophers still harbored doubts about the existence of atoms until the beginning of the twentieth century.10 The concept might be just a heuristic device of thought that help us to predict and explain  See Gardner, M.A. (1979). Realism and Instrumentalism in 19th-century Atomism. Philosophy of Science, 46, 1–34.

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why so many chemical phenomena behaved in an invariably manner, but there was not yet any direct evidence for the existence of these atoms. Thus, it was not until chemists and physicists were able to observe via instruments the causal effects of the behavior of atoms and make experiments on and with them that doubts about their existence vanished.11 Also black holes are invisible although considerations about their existence go back to the eighteenth century speculations that gravitation of stellar objects might be so huge that light corpuscles could not slip away from their source. John Mitchell was the first to suggest such a possibility in 1784 in accordance with Newton’s theory of gravitation, and he ingeniously suggested that a way to detect them was to observe such black stars as companions in binary systems with optically visible stars. A few years later Pierre-Simon Laplace stumbled on the same idea. The possibility of black holes is also a theoretical prediction of the general theory of relativity according to which a supermassive object may form an event horizon beyond which no light can escape. However, it is only in recent times that technology has given us an observational proof of their existence. For some time stellar motions at the center of galaxies have implied the presence of black holes. And over the past six years gravitational waves have been detected, which can be explained according to general relativity theory as resulting from the merger of two back holes. Another phenomenon, which implies their existence, is the discovery of their gravitational lensing effects. However, in 2019 astronomers were able to construct a false-color image of a super-massive black hole at the core of a gigantic galaxy, M87. The construction of this image rested on radio wave data collected by a large array of radio telescopes and a powerful amount of theoretical assumptions. Nevertheless, the transformation of the radio signals into visual information shows the cresent-shaped emission ring around the “shadow” of the black hole’s event horizon. Again, we see the same kind of empirical evidence for their beliefs in black holes that scientists appealed to a hundred years earlier in their defense of their beliefs in the existence of atoms. The results of many very  In Nancy Cartwright (1983), pp. 82–84, she adduces Jean Baptiste Perrin’s justification of the existence of atoms and molecules based on the determination of Avogadro number in as many as thirteen different but independent experiments. 11

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different sorts of experiments confirm the existence of black holes in the sense that scientists agreed that the existence of black holes provides us with the only physically possible, or at least with the most plausible, understanding of many different phenomena. After a period of time during which they were hypothetical entities suggested by theoretical speculations, over a longer period of time during which scientists came to believe in their existence based on an interpretation of the behavior of visible entities, in this contemporary era both atoms and black holes have finally moved from being hypothetical invisible entities to becoming observable. Therefore, I hold that whenever we specify the identity conditions of an invisible entity, these conditions determine the use of the name for this entity. However, if the identity conditions include predicates concerning observable properties that count as good evidence for observing this entity, and this evidence is actually collected, the entity changes its epistemic status from being considered hypothetical to being considered real. As long as understanding the observable data for their existence prosed representational problems, physicists could not agree that their beliefs were true.12 These hypothetical beliefs rose from a tentative interpretation of these data. Nowadays, however, the interpretative period is finished. No doubts exist with respect to the data concerning the existence of these two types of objects. The observational data do not indicate a representational problem anymore—rather the empirical evidence we have for their existence becomes part of the meaning of being an atom or a black hole. Not only are all present data consistent with physicists’ beliefs in the existence of these entities, but physicists also use those beliefs to explain and predict new phenomena. The beliefs in atoms and black holes are now part of physicists’ fundamental comprehension of the physical world. Nonetheless, one might object that there is a huge difference between seeing a house with one’s own eyes and observing atoms and black holes. The house provides me with a sense impression of it, but neither atoms nor black holes produce any sense impression in me. So how can I suggest  In Faye, J, (2014) I argue that we should understand any interpretation as a hypothesis that attempts to solve a representational problem. 12

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that we can observe invisible things? However, I think this objection does not hold water. A lot of empirical knowledge we have is due to induction. I know what my house looks like, though this knowledge does not rest on any actual sense impressions. I also know how to get home from the university. Likewise, I know at the university that my house is still there when I return home. However, a pedantic opponent might respond you may believe it, but you cannot know it, because you could be wrong. Indeed, I may suffer from amnesia, or someone might have blown up my house, but I contend that such hypothetical possibilities do not downgrade my knowledge to mere beliefs. The possibility of p being false is not in conflict with claiming that I know p, according to the “standard” definition of knowing that p. Only its actual falsity is. As long I have strong inductive support of my beliefs, and no empirical evidence against it, I am for all practical reasons obliged to say that I know what I believe. Similarly, I maintain that the same hold with respect to physicists’ beliefs in atoms or black holes. Today physicists know that there are atoms and black holes and that they behave in this or that way. A series of inductive inferences based on mutually independent empirical data supports their beliefs that there are atoms and black holes, just as no empirical evidence is in conflict with such beliefs. So when a physicist is facing a digital picture of a particular atom or a particular black hole, her belief that the picture is the result of observing one of these things is in principle no different from her belief that a picture of her fiancée is a picture of that person. In both cases, you can elaborate on all these counterfactual and hypothetical possibilities about a scenario that these pictures show something else. But such speculations are irrelevant to a naturalist understanding of humans’ ability to instrumentally observe concrete invisible entities. The problem is, of course, that human beings have not evolved to experience invisible objects, because these are not part of our experiential world. The physical environment has not yielded any selective pressure on human beings to develop a biological capacity to gather information about very small objects or things very far away. Those parts of an organism’s physical environment, which are irrelevant for its survival and reproduction, will stay invisible for that very organism because it does not need this extra information. Nevertheless, some might argue that our

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beliefs in the existence of invisible objects seem to be the result of reification of our ideas and thoughts. In my opinion, this holds only for so-­ called abstract objects.13 These alleged entities do not exist; they are merely mental constructions. Even if they do exist as abstract objects they would be causally inert and not located in space and time, and we could not have developed any faculty by which we could know them. The use of mathematics does not require that the mathematical symbols refer to abstract objects just as the use of language does not necessitate that general terms refer to real universals. The situation is quite different when we consider invisible entities that have causal powers and are located in space and time. However, let me add that an evolutionary naturalist could in principle be agnostic about the existence of abstract objects and/or universals. He only has to say that we cannot know whether they exist or not. He might argue that what exists is quite independent of our cognitive faculties. Evolutionary naturalists are realists concerning visible and perhaps even observable but invisible entities. I admit that it seems outrageous to claim that abstract objects do not exist, because we are not capable of knowing their existence. Nevertheless, I also think that if the evolutionary naturalist can explain why our capacity of inventing abstract concepts is a great benefit for us and has been for our predecessors, we have no legitimate grounds to assume that there exist abstract entities corresponding to these abstract concepts. I will develop such an explanation in some of the remaining parts of this chapter. Invisible entities are, as the name says, not accessible to the naked eye because they are either too small, too transparent, too massive, too far away, or do not reflect light. However, this does not exclude the possibility that they are accessible in other ways. Elsewhere, I have argued, in contrast to Bas van Fraassen’s view, why I think instrumental observation provides us with information about the existence of concrete but invisible objects.14 So-called unobservable entities are invisible to the naked eye but observable by instruments that engineers and technicians have 13 14

 See Faye, J. (2016).  Faye, J. (2016), Chap. 3.

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designed to transform and amplify different physical effects into something that is visible. I also very much agree with Ian Hacking’s claim that if you can use an invisible entity to manipulate other entities, it must be real.15 Physical interaction and manipulation are the ultimate grounds for agreement about what exists or not. Behavioral engagement, not passive sensation, is the procedure by which we establish the existence of visual things. Nobody has ever been in an interaction with centaurs or ghostly appearances; therefore, we agree that there are no centaurs or ghosts. Hence, we know by experience that apparitions, mirages and hallucinations are not real because we are not able to interact physically with these alleged appearances. Although we are not adapted to see invisible things, we believe by analogy that we are justified in thinking of phenomena that we cannot observe without technological means to be manifestations of real things as long as we can intervene in their course of appearances. Moreover, scientists have a functional understanding of instruments and instrumental readings, which implies that the design of an instrument is to give them data about some invisible object that is distinguished from the apparatus itself, although this something eludes the human eye. Or to put it in another way: the experimentalists’ understanding of the purpose of using instruments consists of a firm belief, and not only an expectation, that proper instrumental readings reveal something about objects that exist independently of the apparatus itself. A basic element in our comprehension of nature, which is a product of the cognitive adaptation of our mental faculties, is the grasp of the changes of visible phenomena caused by other visible phenomena. The ability to experience regularity and order among visible things is just as much part of our evolutionary adaptations as the ability to sense each particular sensory thing itself. We automatically apply our cognitive schemas of causation even when we experience changes whose cause we cannot experience with the naked eye. Since evolution has ingrained a grasp of causation in our understanding of nature, we simply cannot make sense of what happens around us unless we comprehend visible phenomena, which we cannot causally explain in virtue of other visible phenomena, as changes that are caused by invisible entities. Before modern  Hacking, I. (1983).

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science arose, such an appeal was to the cause of non-natural or supernatural creatures like gods, spirits or deities, but the emergence of modern science made this kind of understanding irrelevant. After the empirical discovery of atoms, scientists and technicians have been able to use their knowledge of the causal properties of molecules, atoms and subatomic particles in numerous ways in their creation of many new pharmaceuticals, chemicals, and different materials as well as use this knowledge to construct instruments, computers, electronics, atomic reactors and, unfortunately, atomic bombs. In my earlier works, I have defended a naturalist, or some will call it non-realist, semantics of common names and general terms that I have named the criterial theory.16 The basis of this semantics is the common observation that we learn mass terms and common names by ostension or by descriptions that contain terms enabling us to identify the named object by empirical means. The theory applies to common names standing for natural entities that are either visible or invisible. It builds upon two assumptions. First, it accepts, in agreement with Kripke’s causal theory of reference, that there exists a causal relationship between the proper use of a common name and the bearer of that name.17 Second, those observable features we use to identify a particular entity as a particular kind of entity are those that establish a causal relation between the bearer and the use of the name. The bearer’s observable properties that I characterized as its sortal properties eventually establish themselves as the defining empirical criteria for identifying the entity to which the name refers. The empirical criteria become part of the natural meaning of a common name.18 Common names do not refer to universals, nor to any essential properties. On the contrary, they refer to any entity whose identity conditions satisfy some definitional empirical criteria. So it is part of what we understand by the natural meaning of a common name that observing the relevant properties provides us with good experiential 16  The earliest presentation of this view is Faye (2002). Rethinking Science, pp. 72–78. See also Faye, Jan (2016) Experience and Beyond, pp. 140–142, and pp. 191–193. 17  Kripke, S. (1972). Naming and Necessity. In D. Davidson and G. Harmann (eds.) Semantics of Natural Languages. Reidel. 18  Metaphysically speaking: if one believes that objects are nothing but bundles of properties, it would make sense to say that a natural name refers to such a bundle of observable properties.

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(sensory and behavioral) evidence that the corresponding name correctly applies to this object. Indeed, such empirical criteria are defeasible, and therefore the reference is changeable. Thus, if we evoke this theory to understand the reference of the names of invisible things, we can say that the meaning of terms like “atoms” and “black holes” includes some empirical criteria of identity. In the proper experimental situations, these objects reveal specific observable properties that scientists regard as good empirical evidence for their existence and that this evidence becomes part of the meaning of their names. This semantic view seems close to Darrell Rowbottom’s position when he argues “for a moderate form of semantic instrumentalism. It involves a denial of semantic realism in so far as this pertains to talk of unobservable properties, but not unobservable objects provided that these are defined in terms of observable properties or by analogy with observables.”19 I take this to mean that hidden variables, for instance, may characterize unobservable objects as long as these variables are analogous to observables like position and momentum. (Of course, strictly speaking, the only observable in physics is space and time loci; all other observables rely on position measurements.) Indeed, this gives us a possibility of envisaging what is going on in quantum mechanics although we cannot observe such non-classical states. However, as Rowbottom notes, a reason for not attributing invisible entities observable properties is that if one agrees with Bohr that the classical state defining concepts do not refer to the properties of quantum objects directly, but that the use of these concepts is intelligible only in relations to experimental arrangements that are complementary to one another.20 This view excludes hidden variables. It is very intelligible from an evolutionary perspective that we are unable to characterize unobservable properties of invisible entities, and that we  Rowbottom, D.P. (2019), p. 31. Certainly, Rowbottom is not alone with this observation, but in contrast to many other philosophers, he takes Bohr’s interpretation seriously as a supporting example of his own cognitive instrumentalism. 20  Rowbottom, D.P. (2019), p. 34. Bohr’s interpretation of quantum mechanics speaks to the fact that the notion of causation exists as an adaptive schema of understanding that has evolved to grasp the behavior of things we can experience. Although Bohr realized that the so-called classical concepts are indispensable for our understanding quantum phenomenon, he also realized that their application had to be restricted. This restriction, I will argue, is a result of the fact that we are not biologically adapted to understand quantum phenomena. 19

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ascribe observable properties, or properties in analogy to observables, to invisible things only when we have good evidence to do so. Electrons and other atomic or subatomic particles may not have a definite position nor a definite momentum unless they interact with a particularly designed experimental apparatus. It makes no sense, according to Bohr, to assign any of these two observable properties to a free particle because according to Heisenberg’s indeterminacy relation these properties cannot be ascribed both at once. Similarly, whether observed electrons can be described as particles or waves also depends on the experimental context. Nevertheless, whenever we are able to ascribe these attributes to an electron, we are still able to ascribe these properties to the electron only as an observed phenomenon about which we know something that allows us to predict something else. In addition, electrons also possess observable features in the sense that they carry proper mass, spin, and electric charge independently of the experimental situation. We identify electrons by those sortal  properties, although mass, spin, and energy are not sufficient for their individuation. This requires a situation where we have experimental contact with something that can be attributed such sortal properties. Hence, science knows something definite about electrons as invisible but observable entities. The message behind Bohr’s interpretation is that we need make use of the so-called classical concepts (those concepts introduced by classical physics) whenever we want to describe invisible objects like electrons as individuals, even though these concepts refer to the invisible objects only in the context of the phenomena in which they are observed. In other words, we are able to attribute, say, momentum or position only in cases where we are able to make a particular experimental individuation of the object in question. Because the so-called classical concepts are adapted to grasp our physical experiences of macroscopic objects, experiences that according to a naturalist consist of an elaborated extension of our sensory impressions, they are, although contingent, the adapted ones we must use if we want to unambiguously express the experimental results and convey these results to other human beings. This brings us to concepts like superposition and entanglement that have no analog in classical mechanics. Moreover, superposition and entanglement are not observable features of a quantum system and therefore we cannot individuate any alleged thing in these quantum states. For instance, with respect to superposition, it is only in connection with the

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experimental individuation that we can ascribe observed properties such as momentum or position to an electron. In quantum mechanics, according to Bohr, positon, momentum, time, energy, and spin direction are experiment-dependent properties.21 Furthermore, a quantum system in a singlet state is in an entangled state such that its constituents cannot be ascribed individual states independently of the states ascribed to the other constituents of the system. In other words, but in more technical terms, an entangled system is defined by quantum mechanics as one in which its quantum state cannot be factorized as a product of the quantum states of the individual constituents. We also know that if we measure a pair of electrons, A and B, in a singlet state we will observe one electron with spin up and the another with spin down because of the anti-correlation of their spin components independently of the direction in which either will be measured. However, if we attempt to measure the spin components of the two electrons in different directions, the measured spin values will not correlate. Assume we measure A’s spin in its x-direction, and B’s spin in its y-direction, and then again measure A’s spin in its y-direction. In this case, A’s spin and B’s spin in the y-direction will no longer be anti-correlated, because the pair is no longer in a singlet state. The first set of measurements separated A and B by making them individual objects, which can be interpreted such that the spin direction of an electron does not exist before an instrumental observation. As a fermion, an electron is defined as having a spin value of one-half. Thus, spin together with proper mass and charge are the observable properties that identify an electron, and thereby determine the empirical criteria that define the reference of the common name ‘electron’. Thus, our theoretical knowledge concerning electrons is that we know what the observable properties are by which we identify an electron. These sortal  properties are epistemically necessary for our ability to recognize something as an electron. Although they are empirically discovered, we would not be able to identify an electron if we imagine a situation in which an electron did not possess those properties.  In (2019) I distinguish between extrinsic and relational properties, claiming that relational properties such as higher than, older than, or later than are not causally grounded, whereas extrinsic properties are due to a causal interaction between two systems. Thus, I say that these relational properties are extrinsic. 21

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However, since electrons are invisible entities these observable properties only help us to individuate electrons whenever we measure them. In other words, since we cannot see electrons and thereby observe any individual boundaries to other objects, the only manner in which we can individuate them is to have an experimental physical contact with something that meets the empirical criteria of being electrons. Whether an electron has a spin up or spin down is not an intrinsic property of an electron but an extrinsic one. But definite extrinsic properties characterize only individuals. So an electron has a definite value of a spin direction, just like it has a definite momentum or a definite position, only in those situations where we can ascribe such properties to an individual particle. In an entangled quantum state, without any instrumental observation, there are no separated individuals. As a result, we may conclude that we can have empirical knowledge of extrinsic properties in quantum mechanics only in those cases where a specific measurement enables us to individuate the observed entity based on which we attribute a definite value. Invisible objects are real, because they are observable, whereas abstract objects are not. The latter are merely constructed abstract ideas to which no objects correspond. We have no knowledge of abstract objects as mind-independent entities, because we have no empirical criteria that make it possible to identify them. Any attempt to establish other criteria, such as set theoretical criteria for the identity of numbers, fails because these criteria are themselves abstract. These criteria are themselves mental constructions. Nevertheless, this does not exclude the possibility that the mind might generate abstract concepts in terms of linguistic definitions. However, every concept, which is not just a constructed abstract idea, is also an “abstraction” by the mind, but drawn from observed particulars. In such cases, the abstraction determined the intension of a term expressing the concept in question, whereas the extension of the term expressing this concept is the set of all things that satisfy this intension. Thus, the empirical criteria obtained by abstraction provide us with the rules by which the term for a concept is used correctly according to its intension. In fact, it would seem impossible to recognize any regularities at all unless you can abstract what is common to the repetition of the regularities. Successive cases are not identical in every respect, but only in certain respects; so we have to be able to abstract from the particularities of each

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case and consider only that which is common. But the construction of abstract ideas has helped us to apprehend sensory regularities and to understand how visible things behave over time as they do, even though no objects match such ideas. The use of epicycles in astronomy is just one historical example. The concept of entanglement is another. We can observe the anti-correlation of, say, the same spin direction of electrons in a singlet state, and we can observe no such correlation in different spindirections. Therefore, the wave function of a pair of electrons is not a factorable product of the wave function of the two components. The concept of entanglement is abstract in the sense that it is a mathematical representation of the possible outcomes of a conglomerate of various incompatible measurements all at once, which is physically impossible in the microdomain and so cannot refer to a concrete real thing. In contemporary physics, concepts like ‘state space’, ‘phase space’, ‘configuration space’ and ‘Hilbert space’ are such abstract ideas. The same is also true for concepts like ‘superposition’, ‘wave function collapse’, and ‘virtual particle’. These concepts do not refer to anything that is detectable by experiments. They are constructions, useful in various ways for physicists’ calculations and in their understanding of the phenomena. Names expressing these concepts are not referential in the sense that no empirical criteria determine their use. Such names are defined not in relation to any observable properties but to an abstract description of their intended functional meaning. Abstract ideas help us to understand how to calculate and predict the behavior of natural as well as social phenomena; they do not give us knowledge about the world beyond our sensory experiences to which our sense organs are not adapted.

 hy Scientific Theories Do Not Express de W re Knowledge Realists about scientific theories believe that these theories represent physical reality. Probably, they all agree with Jarrett Leplin that (1) our best scientific theories are true or approximately true, and (2) the central terms of our best theories genuinely refer to some objective entities,

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properties, or states of affairs.22 Similarly, Carl Hoefer characterizes scientific realism as, “the family of philosophical views that assert that we have strong reasons to believe in the truth or approximate truth of much of the content of our current scientific theories.”23 Scientific realists not only think that scientific theories are true or approximately true; they also hold that theories posit the existence of those entities over which they range. Three other quotations illustrate this quite well. The first is by Grover Maxwell who maintains that: “well-confirmed theories are conjunctions of well confirmed, genuine statements and … the entities to which they refer in all probability exist.”24 The second is due to Richard Boyd: “By ‘scientific realism’ philosophers ordinarily mean the doctrine that non-observational terms in scientific theories should typically be interpreted as putative referring expressions.”25 The third one stems from Stathis Psillos who writes, “insofar as scientific theories are well confirmed, it is rational to believe in the existence of the entities they posit.”26 A case supporting such claims might be the appearance of black holes in classical Newtonian gravitational theory or black holes in Einstein’s general relativity theory. However, nobody will claim that Newton’s classical mechanics posits the existence of pendulums or planetary systems. So why would it posit the existence of black holes? I shall return to this question below. However, what people have in mind when talking about scientific theories is rather unclear, especially if we agree that a science is much more than its theories. Most philosophers and scientists undoubtedly think that a physical theory consists of a set of mathematical formulated propositions such that these formulas, which scientists hold to be true, are the laws of the theory. Hence, realists regard physical theories as expressing our de re knowledge in terms of these laws as necessarily true. The  Leplin, J.t (1984). Scientific Realism. University of California Press, p. 1.  Hoefer, C. (2020). Scientific Realism without the Quantum. In S. French and J. Saatsi (eds.), Scientific Realism and the Quantum, 19–34. Oxford University Press. 24  Maxwell, G. (1962). The Ontological Status of Theoretical Entities. In H. Feigl and G. Maxwell (eds.), Minnesota Studies in the Philosophy of Science Vol. III, 3–27. University of Minnesota Press, p. 18. 25   Boyd, R. (1980). Scientific Realism and Naturalistic Epistemology. PSA 1980, Vol. 2, 613–662, p. 613. 26  Psillos, S. (1999). Scientific Realism: How Science Tracks Truth. Routledge, p. 70. 22 23

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characterization of law statements as expressing our modal knowledge of nature is something both empiricists and epistemic naturalists would like to avoid. In his defense of constructive empiricism, Bas van Fraassen argues that laws as de re propositions are unnecessary, and Ronald Giere opts for a position in which we can do without laws.27 I agree to the extent that scientists do not need laws to be true in order to use them for describing and predicting the behavior of observable phenomena. One thing seems certain: if it turns out that theories are neither true nor approximately true in a realist sense, they cannot express knowledge about the objects they allegedly posit. Arguments that have been given in support of realism include the no-miracles argument and the explanation argument. If a scientific theory does not suggest the existence of those objects it supposedly describes, then the no-miracles argument is unsound because scientific success cannot be equivalent to referential success. The fact is that no theoretical law of nature posits the existence of any objects. For instance, quantum mechanics is used to speak about the empirical findings of microscopic objects, but it can also be used to describe macroscopic objects, although nobody attempts to do so for practical reasons because the effects of the quantization of energy are insignificant. The second argument is that a theory needs to be true in order to have explanatory power. Thus, if a theory is true, then it has explanatory power; but apparently, the realist also claims that if a statement is an explanation, then by definition it must be true. Against this assertion stands the observation that we appeal to all kind of theories, i.e., religious, philosophical, political or social theories, to explain what we intend to explain as long as we believe they give us the wanted insight. We take them to be useful because explanations, rightly or wrongly, provide us with an understanding of how things hang together, and a theory offers a language in terms of which we are able to speak about the observable world around us.28  van Fraassen, B.C. (1989). Laws and Symmetry. Clarendon Press; and Giere, R.N. (1999). Science without Laws. Chicago University Press. 28  For a further discussion of explanation as discursive act of communication, see Faye, J. (2014). Here I defend a pragmatic-rhetorical theory of explanation. This theory is closely associated with the cognitive evolution of humans presented here since it characterizes explanations as perlocutionary speech acts. My claim is that understanding consists of the organization of beliefs or information and that a speech act functions as an explanation because it relates some unintelligible belief, information or observation to a set of intelligible beliefs such that what is explained also becomes intelligible. 27

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Therefore, I propose that (i) theories are neither true nor false, just as (ii) no central term of a theory refers in and by itself. Indeed, these claims need some qualifications. Lars-Göran Johansson distinguishes between three types of laws: (1) those that in an epistemological sense are fundamental laws, which introduce new concepts as the result of inductive formulation of regularities; (2) those that are derived laws; and (3) those that are explicit definitions.29 The first kind, the basic laws, functions as implicit definitions and are said to have empirical content. This kind of law stems from inductive inferences based on observational reports that do not include theorydependent predicates. In the formulation of classical mechanics, John Wallis, among others, observed that the velocity in the collision of elastic bodies before and after the event was constant, and the resulting constant of using different bodies was then defined by Isaac Newton as a quantity of matter, which he named the mass of the body. Movement is something we immediately experience, and ‘velocity’ became an empirical notion as soon as human beings arrived at the idea of defining movement by two other experiential notions ‘time’ and ‘length.’ Thus, the observation of velocity constants with different bodies and the induction based on these observations together yield a new concept the ‘conservation of momentum.’ The term “force” was then introduced as a term equivalent to the term “the change of momentum.” This is how Newton got to his three so-called laws of motion. However, this empirical motivation for introducing unobservable predicates like “mass” and “force” into the vocabulary of mechanics does not make Newton’s three laws true. Rather the reasoning behind these observations constitutes an epistemic procedure to make certain that the language presented by the theory is empirically relevant by being defined in terms of predicates of observables. The defining rules are applicable in describing empirical phenomena such as collisions and changes of the velocity of physical bodies. Contrary to the scientific realist, I shall hold that no theory, as a set of laws, posits the existence of black holes or any other entity. Scientists introduce theoretical entities into a science by constructing an interpretive model from the experimental knowledge they have of the entities in question. They think of these entities such that their properties can be 29

 Johansson, L.-G. (2021), Ch. 10. I refer the reader to his insightful discussion.

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described in terms of a theory’s predicates. The basic equations of any numerical theory are implicit or explicit definitions of how the various predicates that we use to describe a physical system can be expressed in terms of other predicates. Physical descriptions are always linguistic acts the intention of which is to represent a real object in an interpretive model. Thus, theories function as linguistic rules for how we may legitimately speak about the quantitative properties of physical systems. From this point of view, Newton’s second law does not state a causal relationship between a force and the acceleration of a body with a certain mass. Instead, the equation defines what it means to be a “force.” Hence, theories are adequate for scientists’ descriptive and explanatory aims, but they do not express our knowledge of nature. Knowing a theory is to know how to use a technical vocabulary to speak satisfactorily about a particular area of experience. Had Alain Aspects and the experiments of others shown that Bell’s inequalities were not violated, this would have shown that quantum mechanics is inadequate for predicting the outcome of those experiments, although it has proven adequate in predicting the results of numerous other experiments. The suggestion that black holes may exist is not derived from any theory but from applying either the Newtonian or the Einsteinian theory of gravitation to the construction of an interpretive model in which the mass of a body is assumed to be sufficiently large that no corpuscle of light can escape. A reason for such a claim is that neither of the two theories of gravitation involves any suggestions about the nature of light particles. The physicists have to introduce them together with a hypothetical celestial body into an interpretive model as idealized objects of study, such that either of the two theories can describe the behavior of the light particles in relation to this body. A more general reason is that the equations of Newton’s theory and Einstein’s theory consist of relationships between only those predicates that physicists may use to characterize the entities they want to depict as idealized objects in an interpretive model. By constructing such models physicists, or other scientists, produce their predictions and explanations. Theories deliver the conceptual framework by which scientists construct their interpretive models allowing them to understand specific entities in terms of this framework, and the

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explanatory hypothesis they derive from such a construction enables them to make predictions. Also consider quantum mechanics. Physicists use it to calculate the observation of the properties of many kinds of subatomic particles, which were not yet discovered when the theory first came to light. For instance, quantum mechanics does not posit neutrinos or predict their existence. Instead, neutrinos were hypothetical particles suggested by Wolfgang Pauli in 1930 in order to explain why the emission of electrons in beta-­ radiation does not violate the principle of energy conservation. Not until 1957 was the first case of neutrino detected, although indirectly. In fact, when Heisenberg presented matrix mechanics in 1925, only two subatomic particles were known, the electron and the proton, which were experimentally detected without relying on any particular theory, even before the presentation of Bohr’s semi-classical model. Scientists and philosophers alike use the term models alongside the term theories. Nonetheless, they frequently do not make a clear distinction but use them interchangeably. In modern philosophical literature, there are at least two ways to think of models. One goes back to Patrick Suppes’ model theoretical approach to theories, according to which a model is a semantic but partial interpretation of a scientific theory, where a theory consists of a set of models or interpretations.30 This approach has been at the center of the semantic understanding of theories in contrast to the syntactic approach of the logical positivists. Mary Hesse, I think, typifies the other approach. This view on models prefers to see them as idealized representations of the real world, not in virtue of any alleged correspondence or isomorphism between model and reality, but in virtue of analogy. Such a representation can be weak or strong, it all depends on the amount of evidence provided by the different analogous domains.31 My own view about theories, which I call the linguistic view, is as follows: a physical theory consists of a vocabulary of interpreted numerical  Suppes, P. (1960). A Comparison of the Meaning and Uses of Models in Mathematics and the Empirical Sciences. Synthese, 12, 207–301. 31  Hesse, M. (1963). Models and Analogies in Science, Sheed and Ward. See also Hesse, M. (2000). Models and Analogies. In W.H. Newton-Smith (ed.), A Companion to the Philosophy of Science. Blackwell Publisher, 299–307. Here she also criticizes the semantic concept of scientific theories. 30

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predicates and a set of rules concerning how these predicates are defined in relation to one another. This view is not new. Already Ernst Mach and Henri Poincaré had similar ideas. What we can observe is motion and change of motion. Thus, Poincaré stated, considering Newton’s so-called laws of motion, “it is by definition that force is equal to the product of the mass and the acceleration”; which no future experiment can disprove.32 He then immediately recognized that the third law follows as a logical consequence of the second. However, Poincaré then claimed that neither the second nor the third law is strictly true. But, as Johansson points out, this is a confusion.33 In my mind, such a confusion arises if one doesn’t make a clear distinction between a theory as a system of definitions or linguistic rules and a theory as a model that is constructed such that it is an idealized representation of some target system. Thus, in contrast to theories, we have models.34 A model is an idealized representation of an object or a system of objects that can be described using the predicates of a particular theory. In a model, the theoretical vocabulary of observable predicates is brought into play by being used to characterize those entities that the model is intended to represent.35 In addition, these representations—although today they may have become the standard way of representing a certain kind of entities—were originally the production of a conscious interpretation. I therefore call them  Poincaré, H. (1905). Science and Hypothesis. Dover Publication, p. 104. After Poincaré and Mach characterized Newton’s laws as definitions, several philosophers like Stephen Toulmin, Norwood R. Hanson, Thomas Kuhn, Brian Ellis and Ronald Gieri have argued that Newton’s laws are, or sometimes act as, implicit definitions. 33  Johansson, L.-G. (2021), p. 32, although favoring the same view, points to some inconsistencies in Poincaré’s expositions. 34  In my opinion, models and theories are embedded in a scientific discipline that also contains metaphysical presumptions, theoretical assumptions like conservation principles, scientific values and knowledge of a scientific practice within a certain field. 35  Today, it seems clear that a model representing a certain target system does not represent only because of an isomorphism between the model and the target system. What is much more important is the human intention behind constructing the model in a particular way, and what use the scientist wants to make of it. See, for instance Friggs, R. (2002). Models and Representation. Why Structures are not Enough. Measurement in Physics and Economics Project Discussion Paper Series, DP MEAS 25/02, London School of Economics; and Giere, R.N. (2004). How Models Are Used to Represent Reality. Philosophy of Science, 71: 742–752, p. 743. Usually, the aim of using models is to provide scientists with predictions and explanations, but sometimes it happens at the expense of the lack of understanding. A classic example is Bohr’s model of the hydrogen atom where the discontinuous transition from one orbit to another is unimaginable. 32

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interpretive models by which scientists may generate explanatory hypotheses. A representation can be mathematical, linguistic or physical, depending on the sorts of elements that supposedly do the representation. What the model represents can be all kinds of phenomena that are of interest to science. And the degree to which this interpretive model represents its intended target is determined by how idealized the model is with respect to the system it is intended to represent. A theory gives the scientist the conceptual comprehension of how to construct an interpretive model such that the object or the system is described in terms of a set of predicates offered by the particular theory that the model is constructed to interpret. The function of scientific theories is to deliver a set of predicates and some rules for using these predicates such that these rules determine how the scientists should describe its target systems in order to represent those entities adequately in a model. An interpretive model’s adequacy is measured with respect to how precise it delivers predictions. However, the guidelines of a theory do not do the work alone. Constructing an interpretive model also requires the interpretation of experimental data concerning initial conditions and other information about the objects represented in the model and the observable effects of their behavior. Such information may be in the form of empirical knowledge concerning the causal behavior that characterizes the target object. After scientists have used all this information to construct their interpretive model, they can use it to predict certain results and compare them with new observations. The construction of an interpretive model is successful only when the inductive process of reasoning combines empirical data and theoretical suggestions. Often this happens in analogy with models of already well-understood phenomena. From the various models, if they fail to be successful, the process of induction may gradually result in a new model or an entirely new theory. Science does not reject a model because it is false, but because of an agreement that it is inadequate for its intended purpose of representing the target or explaining observational data. Historical examples are the inadequacy of Aristotelian physics in describing the heliocentric model that led to Newton’s mechanics, and the predictive deficiency of Bohr’s atomic model before Heisenberg, based on these failings, developed his matrix mechanics.

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Besides the process of constructing interpretive models (and more rarely theories,) the scientific enterprise also consists of the practice of formulating hypotheses concerning how various experimental designs would operate to produce the desired results, the process of constructing and running these experimental devices, interpreting data, and explaining experimental results. As Rowbottom aptly says, “science is legitimately concerned with problem solving, and directly trying to grasp how phenomena interrelate, rather than merely testing theories. Moreover, it is not passive. We often want to know how to intervene in order to affect what happens; i.e., to predict the effects of our possible actions (as well as to identify new possible actions).”36 Effectively carrying out these intentions requires practical more than theoretical knowledge. By doing science, scientists acquire practical as much as theoretical knowledge. However, practical knowledge not only involves physical laboratory skills, but also includes the developed ability to construct interpretive models and to manipulate mathematical formulations in order to derive predictions. In the same way, theoretical knowledge not only consists of knowing how to interpret mathematical signs in physical terms, but also requires knowing how to connect them to empirical data and knowing what to expect about invisible entities based on observation and experimental results. Therefore, the evolutionary naturalist easily agrees with pragmatists that, for instance, “quantum theory should not be thought to offer a description or representation of physical reality: in particular, to ascribe a quantum state is not to describe physical reality. … [Likewise, pragmatists] deny that this makes the theory in any way subjective. It is objective not because it faithfully mirrors the physical world, but because every individual’s use of the theory is subject to objective standards supported by the common knowledge and goals of the scientific community.”37 According to the evolutionary naturalist, the theory of quantum mechanics provides us with a language and the rules of this language (including the Born rule), which, together with ordinary language, empower us with  Rowbottom, D.P. (2019), p. 23.  Healey, R.(2022). “Quantum-Bayesian and Pragmatist Views of Quantum Theory.” In Edward N. Zalta (ed.) Stanford Encyclopedia of Philosophy. (Spring 2022 Edition). URL = 36 37

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standards of communication. Using this language allows physicists to express a mutual agreement about the physical world as it appears to us—through experimental manipulation of entities that exist independent of us. However, it takes us far beyond the scope of this book to discuss a naturalist interpretation of quantum mechanics in any detail.

Mathematics and Empirical Knowledge Advanced sciences such as physics use mathematics to construct and describe idealized objects in an interpretive model that lets the practitioners speak about experimental data and human observations. However, it is worthwhile to remind ourselves that mathematics consists of a series of formal signs connected by some syntactic rules. In each area of physical research, scientists have to interpret these signs such that they become empirically meaningful. The only way scientists can ascribe semantics to a mathematical formalism is to carry out an empirically meaningful interpretation of the mathematical signs by using ordinary language supplemented with a specific terminology, as Bohr argued, because ordinary language already has a semantics that is adapted to express our common experiences. Hence, this implies that we can communicate only what makes sense to say within the use of ordinary language. The above observation requires that we address at least two queries. First, if human beings understand mathematics only in relation to an empirical interpretation, why do we use mathematics in the first place? Second, the use of mathematics seems possible only because we understand the reference of mathematical signs. In other words, if mathematical statements are neither true nor false, how can we explain the definition of deduction as a truth-preserving inference? I shall discuss these two objections in consecutive order. The response to the first question is that science needs mathematics to express scientists’ thoughts as a supplement to ordinary language, because humans experience spatially and temporally distinct objects and sense properties not only qualitatively but also in degrees of these qualities. For instance, we can assign an individual name to concrete objects just as we can assign a number to the same object. The assignment of numbers

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enables us to identify and count, something that higher animals manage to do in a small degree. The last number assigned to a set of concrete objects would also characterize the cardinality of the set itself. Similarly, one stone feels heavier than another, one person is taller than another, and one moves faster than another, etc. Hence, we originally learned to assign numbers through the experience of the separation of concrete objects, and numbers were later used to gauge the experienced differences of degrees in attributing properties to these object. Therefore, mathematics is the language that human beings have developed to handle numbers—first natural numbers and eventually other kinds of numbers—as a measure of objects or properties. This assertion leads to the second point of inquiry. Recently, Lars-­ Göran Johansson has argued that the suggestion that mathematical statements are not truth-apt “undermines the idea that use of mathematical identities in logical inferences is justified by being truth-preserving. For if we conceive an equation as a mere string of linguistic signs lacking truth-­ value, it cannot do its job of preserving truth in a deductive argument, hence this approach undermines the entire idea of valid deduction.”38 Apart from this argument, Johansson also adds that he cannot see why an existential quantifier in mathematics should mean something different from what it does in ordinary language. Although he is a nominalist, he still sees numbers as existing abstract individuals. Let us address the latter issue first. Of course, an expression like “there is …” does not mean something differently in ordinary language and mathematics. When I say “there is … “, or “X exists”, I express my belief, and beliefs, as is too familiar, may be false. The history of human beings shows that people, individually and collectively, have believed many things, which most, if not all, we do not believe today. It is correct that Quine told us which part of a theory we should believe to represent something, namely ”—a theory is committed to those and only those entities to which the bound variables of the theory must be capable of referring in order that the affirmations

 Johansson, L.-G. (2021), p. 54.

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made in the theory be true.”39 But as a naturalist, Quine was also very much aware of the fact that scientists operate with general terms and abstract concepts like universals, which, as a nominalist, he did not accept. In order to show that these concepts do not designate entities we should accept, he introduced his method of paraphrasing that logically eliminates the predicate variables in a theory so that they do not refer to kinds or universals. However, since Quine held that numbers were indispensable for mathematical science, and his method of paraphrasing did not exclude numbers, he believed in mathematical objects as abstract particulars.40 Science as a conceptual system produces many cognitive successes but so do various forms of religion. The difference here is that a naturalist, like Quine, believes the success of science relies on referential success of its mathematical terms, whereas he would probably hold that this claim is more doubtful when it touches religion. Here paraphrasing cannot get rid of an abstract individual notion such as there is a God. However, an evolutionary naturalist might argue that people may have invented a notion of God for explanatory purposes, but they cannot have any knowledge of such an entity, because they could not have been selected to know something which they have no possibility of seeing, touching, hearing, smelling or which has no other perceptual effects on us. The same holds for numbers considered as abstract individuals. Moreover, as noticed before: why should the empirical sciences, in order to be successful, need expressions of numbers where the signs simultaneously refer both to concrete physical objects, their quantitative properties, and to abstract individuals? Hence, as an evolutionary naturalist I maintain that Quine’s criterion of existence is insufficient. Ontology is not determined by logic alone. The reason we think that anything exists independently of us is due to physical manipulations and interactions. Elsewhere I have argued that number terms are names by which we label concrete objects as we engage  Quine, W.V.O. (1953.) From a Logical Point of View, Harvard University Press, pp. 13–14. It seems that Quine did not distinguish between objects and entities. However, one may argue that only objects are the subject of the quantification because they have determinate identity conditions. 40  See also Putnam, H. (1972). Philosophy of Logic. Georg Allen and Unwin Ltd., pp. 53 ff. 39

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in a mental operation of identification, individuation, and counting.41 Human beings and some other higher animals are adapted such that we not only can count but also directly see how many objects there are forming a small set. Thus, right from the beginning of human development as language users, number terms figured in ordinary language. The potential infinite series of numbers is a later construction due to human imagination of what the implication of counting means if we consistently follow the already learned rules of counting. Apparently, mathematics emerged as an independent language only when philosophers began expanding the series of natural numbers as they contemplated whether or not visible lines and drawn figures could be divided, and naming the result of what they imagined with new number expressions. These people used their visual skills, physical actions, imagination, and induction to generalize the concept of natural numbers into concepts of rational, real numbers, etc. It is true that deduction is a truth-preserving inference and therefore the premises must be capable of having truth-value. However, this shows neither that these statements are in fact true in the sense that they represent (correspond with) something in the world, nor that they refer to some abstract individuals. Even if the conclusion is a true statement, because it expresses some observational facts, we cannot validly infer that the premises must be similarly true. However, assuming that I am correct in claiming that the laws of a theory are at least implicit definitions of the predicates involved, these statements are assumed to be true as stipulated, i.e. true by convention. They are not factually or contingently true. Hence, Johansson’s argument is not as strong as it might seem. Of course, we must understand the rules of mathematics before we can use them correctly. However, this understanding consists only of our familiarity with the syntactical rules by which we can manipulate the mathematical signs. We do not need to know whether these signs stand for anything independently of our imaginative power in order to have mathematical understanding.42 Mathematical signs first become symbols  Faye, J. (2019), sec. 10.2.  Perhaps the lack of semantics explains why so many people have difficulties learning mathematics. No sensory cues help them to understand the content of mathematical signs and therefore no sensory cues to grasp the syntactical rules. 41 42

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by getting a semantic content when we are able to know to what extent a formal system represents some reality. Here evolutionary naturalism argues that the way we are adapted by natural selection sets up epistemic limits to what we can know in this regard. In contrast to van Fraassen, I hold that we can know that mathematical signs stand for real entities in an interpretive model if these entities are accessible to the naked eye or if we can manipulate them instrumentally due to their observational properties. What we cannot know are those cases where a mathematical sign is also claimed to represent an abstract object, since science has never discovered that a human being, or any other organism, can gain knowledge in any other way than through its senses. So even if abstract entities might exist independently of the human mind, which I deny, they are by definition not something we are able to know.43 I stated above that the ability to invent abstract concepts is beneficial for those organisms that have acquired this capacity. In fact, it has proven to be valuable for the individual cognition as well for enabling social group behavior. We may distinguish between two forms of abstraction depending on whether an organism’s cognitive mechanisms automatically generate concepts from sensations, or our reflection produces them from thoughts and language alone. The first example of abstraction is when an organism is able to recognize a particular visible object as of a certain type. That organism has a concept concerning a group of concrete particulars without having acquired an ability to grasp a universal ante re or in rebus. The cognitive mechanism of abstraction helps the organism to experience what is important for its survival in its environment. By experiencing concrete objects as sorts and numbers, and not only as individual  particulars, the processing of the amount of information that a complex organism receives from the environment can happen much  In a private communication, Lars-Göran Johansson suggests that it is reasonable to say that abstract entities are human constructions and we can know our own constructions. Knowing an object is to know its identity conditions, and we know what it is and can give various descriptions of it. I have one problem with such a suggestion. It implies that the identity conditions are mind-­ dependent such that abstract objects are not platonic objects. However, concepts in themselves are not objects. All human (and non-human) concepts are constructions of the mind, but they are not objects but modes of thought; i.e., modes of mental presentation. Like other modes of thoughts, they can become intentional objects of the reflective mind. Indeed, in those cases you may say that in order to identify them as such you associate them with their identity conditions. 43

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more swiftly. It has no problem responding to individuals, it has not previously seen. Therefore, such an organism is able to react more quickly to dangers that threaten its life. Likewise, it also permits an organism to identify its sorts of prey or other kinds of food. The ability to abstract concepts from sensations of particulars is also helpful, whenever animals evolve into socially organized beings. The development of a linguistic and a mathematical syntax depends on behavioral interaction between groups of individuals. The socialization of higher animals living in groups occurs while learning the various types of behaviors that mark the hierarchy, the cohesion, and the interaction between the members of the group. It is not sufficient to learn a particular behavior as an act of an individual; it has to be able to recognize this behavior as the same behavior when performed by another individual. Thus, socialization among both human and non-human animals is cognitively possible—given the slow processing rate of the nervous system— because the ability to categorize their sense impressions enables them to react quickly and effectively to their sensations. As I have suggested above, language probably originated when survival in a changing environment demanded a closer collaboration than is found among the great apes living in a stable environment. The capability of communicating verbally turned out to be a huge advantage for cooperative actions and strategies. As hominins evolved into Homo sapiens, our ancestors used language to express new ideas and concepts that enabled them to define and establish new social categories. Via a verbal communication, they were able to construct rules and a legal system and thereby established the first civilization. I suggest that a significant feature of a civilization is that a person has the legal or moral right to the ownership of certain property. However, ownership is a constructed abstract notion. It is not abstracted from any visible features of a piece of land, a tool, or a shelter. Possession does not determine ownership, since a property can be taken by force, be stolen, be borrowed, etc., even though the one who possesses it does not own it. Concepts like ownership, responsibility, justice, and right or wrong are social constructions. Such constructions consist of verbally defined concepts aided by human reflections. They do not result from cognitive abstraction based on observational features of concrete phenomena. Instead, they are the verbal products of human imagination and

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inventions. That they are linguistic creations does not imply, however, that abstract concepts like those mentioned above are arbitrary. A mutual process of reflection and practice has demonstrated the usefulness of these concepts by regulating people’s behavior in ways that suit social stability. Abstract concepts within the social sphere do have a purpose to the extent that they regulate human behavior such that much of human social interactions become explainable and predictable. As long as these concepts fulfill their social aims, there is a strong tendency to hold on to them in order to maintain social order. Eventually such concepts become ingrained as social norms, and the descriptions of how to uphold them become the social rules that are followed. Mature science required creating similar abstract concepts. Both with regard to how science may describe its objects of investigation in order to gain theoretical knowledge of them, including knowledge of the society itself, and with regard to how science operates in order to gain empirical knowledge, these abstract concepts establish rules that scientists accept as part of their scientific understanding of the world. In other words, by using abstract concepts we can mentally organize and understand our empirical knowledge, in spite of the fact that their use does not commit us to knowledge of abstract entities. An example taken from philosophy illustrates this point. The concepts of necessity, possibility, probability, and contingency are abstract modal notions that characterize the way we conceive of something that relates to something else and what we are claiming when we express a statement. Evolutionary naturalists would have no problems with such notions as long as they express something about our beliefs and not what we factually know. Organisms of all species must be able to find connections and structures in what they experience, since that allows them to understand present experiences in relation to earlier ones and, due to this understanding, to anticipate what might happen next. However, because members of Homo sapiens are the language users we are, we have gone to the extreme and described our understanding in terms of logical relations. Many philosophers and scientists have automatically read these logical relations into nature as objective necessities, objective possibilities, and objective propensities, or have regarded them as parts of an abstract realm of reality. However, these people owe us a biological explanation of how Homo sapiens became

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adapted so that such philosophical doctrines exemplify knowledge. In contrast, the evolutionary naturalist has to explain why people are in such a need of reification of abstract concepts in order to make statements using these modal notions. These remarks bring us to the end and a recapitulation of this Chapter. Science produces practical as well as theoretical knowledge. However, the constraints that human evolution puts on theoretical knowledge are more severe than what scientific realists hold. Scientific theories do not describe the world, as it appears to us. Models describe (or represent) but only in an idealized fashion. Scientific theories offer a language by which we can speak about observed phenomena. Using this theoretical language, scientists are able to construct interpretive models by describing the envisioned object in terms of the defined predicates of the theory. Knowledge of such models enables us to speak about what we may or may not observe. But this does not imply that we have no knowledge of the constructed entities, as long as their existence has observable effects. What we are excluded from knowing is objects that have no observable effects, like purportedly abstract objects. Without any physical manifestations, it is impossible to comprehend how human cognitive capacities could have evolved such that they were adapted to these alleged abstract objects, since these alleged entities could not have exercised any selective pressure on the survival of our predecessors.

9 Epistemic Values from a Naturalistic Perspective

Undoubtedly, human beings have a long history of understanding what they could see in terms of what they couldn’t see. As our predecessors evolved into social beings and eventually attaining the ability to use language, we got the means to share beliefs about invisible entities. If people were unable to explain unusual events as caused by familiar events, they resorted to speculation about imperceptible causes. Very early on humans showed a strong need to understand events around them even if they had to invent unseen entities and events to explain those they saw. Although science is born of this same psychological need, social norms eventually demanded that one’s beliefs about both visible and invisible phenomena should reflect established intersubjective and systematic agreement. Presumably, the social coordination of opinions among many individuals concerning what we could not directly experience led to the rise of science and an extended understanding of nature. The values leading to successful agreements are what we consider today as epistemic values for claiming knowledge. I began this book by saying that knowledge and understanding are different cognitive phenomena in the sense that understanding is not a version of knowledge but an organization of beliefs and knowledge. Thinking is what produces understanding regardless of whether our thinking is conscious or unconscious. If conscious, then explanations, © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. Faye, The Biological and Social Dimensions of Human Knowledge, https://doi.org/10.1007/978-3-031-39137-8_9

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inferences, and interpretations in terms of abstract concepts play the major role in creating relationships of understanding that help bring order among our beliefs, regardless of their truth. However, sensory and practical comprehension consisting of reliable information about connections in our environment and our behavioral relations to them are generally obtained unconsciously. Of course, among non-human animals these structuring relations characterize nearly all their understanding without any epistemic values being involved. However, with a common language it became required to share norms for attributing knowledge and reflection-­based understanding to each other in order to keep cognitive coherence among members of the community. This holds even more so for science. Thus, in contrast to knowing, understanding is a question of how an organism organizes its beliefs conceptually, inferentially, and causally, independently of their truth. Scientific theories provide the conceptual and linguistic frameworks for expressing our understanding of the surrounding world and ourselves. They help us to grasp how things hang together as scientists construct interpretive models of idealized objects such that these can be described in the vocabulary of the relevant theories. This understanding is then expressed as predictions and explanations. Where empirical and theoretical knowledge are inductively justified by observation, I maintain we should separate understanding from the epistemic goals associated with truth and evidence. The individual’s understanding comes with coherence among one’s beliefs, and a shared understanding establishes itself when people can exchange explanations and interpretations. The function of explanation and interpretation is to provide us with understanding, but explanations and interpretations may be false and still provide a coherent understanding. Therefore, both explanation and interpretation are speech acts having the purpose of allowing the explainer and explainee to communicate efficiently together. Important notions for describing science, such as representations, interpretations, and explanations, all involve context, intention, meaning, reference, and understanding. Years of debate among philosophers of science ought to have taught us that scientific practices hinge on shared and individual interests, depending on the topic of investigation. A naturalistic description of the epistemology of science that attempts to leave

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intentions, meanings, and interests out of the picture would commonly be judged inadequate in today’s philosophy of science. Only by including intentions and meanings in our discussion can we give an account of the norms of explanation and understanding within a naturalistic framework. A naturalistic approach to explanation and understanding should not exclude normativity because the norms of rationality are engaged in reflective thinking about what one takes to be the purpose of science, and it may vary among scientists. In this final Chapter, I am not concerned with the epistemic values of knowledge, but with those of understanding. First, I outline a naturalist explication of understanding. Next, I distinguish between explanation and understanding and then differentiate our immediate grasp of the world from reflection-based understanding. Finally, I show how this kind of understanding leads us intentionally to form norms of scientific understanding.

The Evolution of Understanding Once they could communicate using an oral language, our ancestors acquired new capabilities for understanding, but also socially installed norms for what such a kind of understanding required. The sign language humans had inherited along with the great apes was invaluable for this transition. They learned a lot from other individuals by watching their behavior. With linguistic communication, human beings could learn from others by hearing about their beliefs, descriptions, interpretations and explanations, just as they could also communicate their own. As a new medium of communication, oral language introduced into the biological sphere a highly abstract level of understanding and an effective way of sharing it among individuals, but before individual interpretations and explanations were publicly acceptable they had to meet certain epistemic criteria. Consequently, due to this conceptual advancement language and mathematics gave humans a grasp of the world vastly better than any animal’s. Language also improved because it enabled us intentionally to define norms that collectively increase our comprehension of the world. All forms of understanding are ways of organizing our beliefs, or more

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fundamentally of organizing information. Reflection-based understanding is best expressed in terms of beliefs, because that is how we phrase epistemic questions, and beliefs are expressed in terms of propositions. However, when discussing understanding involving only images and bodily behavior I will refer to “information.” Before a verbal language evolved among hominins, they were surely able to understand much of the experiential world around them. Consequently, we should be able to account for understanding without referring to any acts of explanation or interpretation, which belong only to linguistic communication. Animals can neither verbally explain nor interpret anything; yet, they are not without environmental understanding, which we partly share with them. That non-verbal kind of understanding is attributable to cognitive schemas operating according to cognitive mechanisms that splice together sensory and behavioral information with experiential beliefs into an organized network of causal and inferential structures. Thus, we should distinguish between various forms or “levels” of understanding, where evolution built reflection-based forms on a foundation of experience-based ones. The basic form of experiential understanding  is behavioral understanding, embodied structured  information obtained by individual organisms, but not having the cognitive status of organized beliefs. This embodied form of understanding later evolved, along with the rise of actional knowledge, to become the source of practical understanding of human beings. Embodied understanding consists of the ability to coordinate a regular series of movements with specific patterns of behavioral effects, for example an animal getting around its territory. A person just behaviorally  driving her car or just behaviorally  speaking a language are other examples. Embodied understanding allows one to foresee the physical effects of one’s own behavior. Another form of experiential understanding, sensory understanding, comes from connecting various sensory images or sensory beliefs. The expectation or anticipation of seeing something after actually experiencing something else is an example of this form of understanding. Typically, experiential understanding emerges from a cognitive organization of sensory and behavioral information and sensory beliefs in order to navigate safely in a particular environment such that it enables an animal to foresee the effects of other animals’ actions. The third form is

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empirical understanding, a mental state in which, for instance, one understands the causes of others’ actions. Finally, theoretical understanding in its most basic form is a mental state in which one understands the causes of physical effects, including the cause of one’s own actions. The evolution of language has especially improved this form of understanding by giving us the ability to think abstractly. In other words, theoretical understanding began to arise with the awareness of causal regularities.1 In its most advanced form, theoretical understanding involves beliefs about unseen causes expressed in terms of either philosophical, religious, scientific, social, or cultural theories. Indeed, these four forms of understanding replicate both phylogenetic and ontogenetic developments. In contrast to experiencebased forms of embodied and sensory understanding, both empirical and theoretical understanding are reflection-based.2 The upshot is that understanding comes in degrees, and our understanding may be useful, but not necessarily true or false. Of course, we can have true or false beliefs about our understanding. Human understanding creates a psychological map in which inferential or explanatory relations connect sensory and non-sensory beliefs. Like topographical maps in which roads connect cities, psychological maps represent more or less accurately what they are intended to represent. You may understand something although some of your beliefs are false or the relations between your true beliefs are not as you assume. However, those who do not share your understanding may hold that you misunderstand the matter, because they believe your beliefs are false or you connect them in the wrong way. There are therefore good reasons to distinguish between knowledge and understanding. As the architecture of, say, a set of beliefs, understanding consists of relations among these beliefs, structured by  I owe the specification of these four levels of causal understanding to Gärdenfors, P. (2003). How Homo became sapiens. On the evolution of thinking. Oxford: Oxford University Press, pp. 41–42, although he is not responsible for my use of them as exemplification of different forms of cognition. However, Gärdenfors hesitates to ascribe animals the ability to understand the cause of physical effects. But see my discussion in Faye, J. (2017). Are Causal Laws a Relic of Bygone Age? Axiomathes, 24(6), 653–666. 2  In Faye, J. (2014). The Nature of Scientific Thinking. On Interpretation, Explanation and Understanding. Palgrave-Macmillan, I distinguish between embodied and reflective understanding and divide them into several subcategories. Here I attempt to follow the exposition given earlier of the various forms of knowledge. But the fact is that these various distinctions are a philosopher’s constructions based on how they may be identified in evolution. In practice, the various forms of understanding are intermingled in humans and are not clearly separable from one another. 1

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cognitive mechanisms according to various natural cognitive schemas. These inherited schemas are blue prints for how the brain processes sensory and behavioral information. Therefore, cognitive mechanisms determine both the form and the manner of our reasoning. When the mind began reflecting upon its own thinking, such considerations gave rise to the logical or explanatory principles we consciously use in building up a body of beliefs concerning invisibles. As an organization of a body of beliefs, empirical and theoretical understanding—by introducing consciously established norms—may be more or less correct. The organization is correct if the beliefs, involved in the understanding, obey some self-imposed norms that we—who may belong to different cognitive and social communities—hold are required in this context to have understanding. Consequently, the scientific practice contains two sorts of norms of understanding. Some we have abstracted by reflection from inherited ways of reasoning, and others we have added to our practices to improve them. A simple illustration would be the use of induction. There is no doubt that induction is the most important cognitive mechanism by which we accumulate knowledge and understanding. Induction based on sensory information and remembered experiences sets up visual or conceptual models of our environment to help us form our expectations. Induction is the mechanism by which we learn about the uniformity of our environment and, therefore, as the basic machinery it forms human understanding. Eventually, by contemplation on our own thinking practices, we come to understand induction as a principle of reasoning. Most likely this development was closely associated with the evolution of human language. But with the rise of science, and probably even before, we also realized that inductive reasoning may sometimes lead us astray, especially if we wish to formulate general or universal claims about the objects of induction. Hence, scientists have improved conscious inductive inferences by inventing new epistemic values, ranging from simple requirements such as variation in collecting data, controllability of data, and precision in observation and description to far more advanced requirements associated with statistical inferences like the binominal distribution of collected data, uncertainty estimates, and standard deviations.

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No naturalist intends to deny that the sciences add their own explicit norms for understanding to those principles that already implicitly exist in our inherited cognitive practices. Nor need the naturalist reduce them to innate principles. But the naturalist will insist that such norms are justified only with respect to their usefulness in achieving assumptions that can withstand further empirical scrutiny. They are justified based on how effective they are in guiding us to cognitive success, including scientific understanding.

A Naturalist Approach What is the cognitive function of understanding? Does understanding have a function distinct from knowledge? These are the questions a naturalist must answer. The need for knowledge evolved to enable us to navigate in our environment. To be distinct from knowledge, understanding must play another or additional role. This role seems to be the ability to put beliefs together in order to form expectations of what is going to happen, and adjust our behavior according to such anticipations. Understanding is the mental capacity that links past knowledge with future goals. Knowledge and understanding are often treated as equivalent.3 But when we realize that experiential knowledge, if concept-based, consists of beliefs about the present, and that empirical knowledge is a generalization of experiential knowledge that includes beliefs about the past and about invisible dispositions, an organism must be able to cognitively bring these different sorts of beliefs together with those that arose due to the satisfaction of its expectations. My suggestion is that this capacity is empirical understanding. As I argued in The Nature of Scientific Thinking, in evolutionary terms understanding is the conceptual grasp of sensory information or the cognitive organization of sensory and non-sensory beliefs.4 This has a number of implications. First, animals possess non-verbal understanding in  See, for instance, Grimm, S.R. (2014). Understanding as Knowledge of Causes. In A. Fairweather (Ed.), Virtue Epistemology Naturalized: Bridges between Virtue Epistemology and Philosophy of Science, 329–345. Springer. 4  Faye, J. 2014. 3

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the form of behavioral and sensory comprehension, and higher animals may  even have empirical understanding and perhaps some theoretical insight. Second, human comprehension includes various forms of understanding such as behavioral, sensory, empirical, and theoretical understanding, which are definitely not isolated into different cognitive compartments, but are often interdependent. Third, ‘truth’ and ‘falsity’ do not characterize understanding but only those beliefs thus organized. Fourth, not only the diverse forms of explanation but also the diverse forms of interpretation provide us with understanding. Explanations as well as interpretations help us consciously to organize and structure our body of beliefs. Fifth, the cognitive organization of beliefs causes our psychological sense of understanding. Considering these consequences, I shall argue that the non-reflection-based forms of understanding determined by various cognitive schemas set the purely evolutionary standards of cognition because of their contribution to an organism’s survival. As previously stated, a cognitive schema is a particular cognitive mechanism that through its adaptive fitness structures thinking and understanding such that much of the previously acquired behavioral information or sensory beliefs become beneficial for the organism in its interactions with the world to which it is adapted. These cognitive schemas have evolved in response to our sensations in order to augment our bodily interactions with our environment. They have an epigenetic origin and constrain the form of our thinking. Because they have evolved by means of natural selection, they determine our understanding by determining the way we think. However, our thinking is not constrained only by them. Our thinking also operates within the scope of these schemas in accord with certain neuronal mechanisms, which evolved in a way that enhances the benefit of the available information any organism receives. These regulating mechanisms process incoming information to enable our thinking to become successful. The regulating mechanisms assure attaining consistency, coherence, relevancy, informative reliability, and inference-aptness among our beliefs. These cognitive features make it all the more likely that our thinking will reach a robust understanding. Thus, I take our habits of thinking to be generically inherited dispositions to process information such that we think in a manner that makes

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our behavior successful. Our cognitive faculties, which evolved according to their fitness, both form and regulate our thinking in a way serving our survival and reproduction. Since we have only the neuronal mechanisms evolution has given us, when our thinking is successful with respect to our behavior, the working of these mechanisms sets the cognitive standards by which we grasp the effectiveness of human thinking. Thus, as part of a naturalist approach to norms of understanding, I shall make a distinction between cognitive standards and epistemic values. The cognitive standards of understanding are determined by inherited mechanisms that regulate our thinking, and therefore determine our cognitive practices as we become conscious of it. Humans have partly unravelled these cognitive standards by reflecting consciously on the cognitive success of their own thinking. In contrast, epistemic values of understanding are idealized requirements on which a community has intentionally agreed in order to improve the cognitive success of reflection-based thinking. Cognitive standards are abstracted from the natural manner of reasoning, whereas epistemic values have their roots in deliberate reflection. Epistemic values have been socially stipulated, elaborated, and idealized to improve and justify our understanding. As human beings eventually became able to attain reflection-based comprehension and verbal communication, the need for conscious interpretations and understanding verbal requests for explanations became pressing. However, obviously both personal and common interests guide interpretations and explanations. Hence, our response to these requests is shaped by our particular purpose confined to a context of supportive theories, background presumptions, and our empirical knowledge. The context influences the criteria of reflection-based comprehension one holds. The question is not whether the sciences, as part of a social enterprise, follow the standards of successful understanding inherited from our ancestors, but whether they establish more reflection-based values for proper understanding. I argue that the sciences do institute such values. But first we shall discuss the cognitive standards more closely.

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The Cognitive Standards As natural phenomena, neither embodied nor sensory understanding are formed according to certain epistemic values. Only when natural selection gave our human ancestors during their cognitive evolution the ability to become aware of their own thoughts were they able to reflect upon their own cognitive practices. At some point in recent history, people began to realize which features made understanding successful at achieving useful empirical insights and which made it unsuccessful. The result of these reflections was a characterization of the most fruitful ones, which could then improve other areas of thinking. Until then, because it produced practical accomplishments, successful understanding rested solely on whether the results of this activity were beneficial for the individual’s survival or its progeny. The turn from adapted successes navigating in a hostile environment to the recognition of cognitive criteria for successful thinking appeared when we became aware that not all (logically) possible ways of experience-based reasoning improved our thinking. Therefore, first we should describe the features we find in our habits of thinking. How did evolution adapt our ancestral thinking to become effective and successful? Which regulating conditions do we find buried beneath our cognitive practices and which, once implicitly or explicitly acknowledged, become standards for our reflection-based understanding? Posing these questions assumes that cognitive schemas have evolved such that they structure the normal person’s conceptual comprehension of the world. These cognitive schemas determine how an organism puts its conceptual comprehension together. They consist of patterns of space-­ time, causation, identity-difference, substance-property, token-type distinction, part-whole relationship, inferential relationships, and other forms of connecting beliefs, all structuring and coordinating our experience and thinking in a consistent, coherent, and relevant way. Thus, I assume that this cognitive machinery regulates the conditions for how we understand the world, bringing our beliefs together into an intelligible order, and in patterns from which the reflective mind can abstract the standards of its own thinking.

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In order to work in favor of an organism’s survival and reproduction, the conceptual manifestation of its individual beliefs must not only be structured by these patterns, but also they must be assembled in a particular order such that they help the organism to reach its goals. Thus, successful forms of understanding coordinate beliefs such that they increase the chances for these beliefs to be useful in guiding successful actions. Indeed, a successful action is one that leads to the desired goal. In all such cases, consistency, coherence, relevance, and completeness are the natural features that set the standards for cognitive success, since inconsistent, incoherent, irrelevant, or incomplete understanding is usually counterproductive to reach productive empirical assumptions and successful actions. Actions following from inconsistent singular beliefs very seldom achieve their intended goal. Inconsistent beliefs generally directly block any form of (successful) action. Moreover, inconsistent beliefs cannot be coherently connected to one another. Without coherence our understanding becomes reduced and cannot be used to navigate effectively in a complex environment or society requiring cognitive coordination of many distinct beliefs. Different beliefs related to one another also have to be mutually relevant. For instance, if some beliefs are connected by some form of inference, that form not only must be valid or reliable; but also the beliefs must be topically relevant in that they concern the same semantic or ontological categories. Invalid or unreliable inferences may connect beliefs that logically do not fit together. The opposite holds for valid or reliable inferences. False premises making categorical errors can validly imply true conclusions. Finally, we also want our understanding to be complete. Too many lacunae in a person’s system of beliefs lessen its effectiveness in guiding actions. Indeed, no person has all his or her beliefs organized in one single system. We harbor many different systems of beliefs, among which very little, if any, connection exists. A person may understand the consequences of the American Constitution as well as the theory of natural selection without any conceptual relationship between them. Such a relationship is not necessary for a federal judge who is interested in biological evolution. Much of what we believe is expressed in terms of different conceptual systems. There may be also internal inconsistency, incoherence, or

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irrelevance among beliefs expressed within a single conceptual system. Such flaws do not necessarily make us unable to act successfully or communicate in a rational and meaningful manner. That depends on how crucial or central these shortcomings are for one’s overall understanding. A singular belief that does not accommodate into the general system of our background assumptions, beliefs, and knowledge, need not be devastating for our general acumen. Insight and comprehension always come in degrees and therefore influence our ability to act proportionally. I propose that people eventually became conscious of when their thinking was successful and when it was unsuccessful, and which features characterized their successful thinking in contrast to the unsuccessful ones. People called “philosophers” began to wonder about why they explained reality the way they did, and what made them prefer (and perhaps improve) one explanation over another. But prior to naturalistic epistemology, it was not recognized that these features, which they elevated to standards for successful thinking, were a result of evolution by natural selection and cognitive adaptation. Therefore, we must confront two sets of questions: one group is about what establishes a successful way of understanding the world around us; the other group is about how we can consciously improve our understanding. For instance, philosophers pondered about human cognition, and realized that understanding consists in relating events to causal powers, intentions, or supernatural forces. They also reflected upon methods of reasoning like induction, deduction, and inference to the best explanation to reach further understanding. The appeals to intentions and causal connections were merely conceptual expressions of natural habits of thinking determined by some inherited cognitive schemas. These natural patterns of thinking characterize most animals to some degree and give them a tacit understanding of their environment. The inherited reasoning patterns in the cognitive schemas constrain the conditions of experiential learning and understanding. Cognitive schemas and regulative conditions are general in the sense that they are part of our biological heritage that any normal mind must follow and cannot avoid. Since no reflective considerations can overrule these schemas or dispense with obeying them, they both enable and constrain our thinking. They form the biological limits and possibilities of cognition.

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But when it comes to reflection-based thinking itself, and the science which arose from it, the human mind also attempts to explain occurrences in human experience that go beyond it. We attempt to explain what we experience by things we do not experience. This means that we begin to explain the visible by something that is invisible. This also generates consciously formulated requirements for rational understanding supplementing those we already have obtained by our biological adaptation. Most intentionally established norms are no longer general but as epistemic values they are contextual. They depend on the explanandum and our shared or individual interests in what we want to understand. Thus, such norms rely on human invention. Given the particular purpose of our reasoning, the most successful ways of thinking also set the norms determining how we should regard particular claims to knowledge and understanding. Thus, in these cases, the particular “ought” behind our thinking is determined by the aim of our thinking in a particular context of epistemic problems. To sum up: the cognitive standards of understanding, abstracted from our habits of thinking as we reflect upon our own cognitive practices, concern everyone since these standards reflect the coordinating features of our inherited cognitive schemas of thinking. However, since epistemic values are socially constructed, they are context-dependent, and therefore local. For instance, cognitive structures of our understanding determine that we perceive events as the effect of intentional acts or the causal efficacy of some physical powers. However, it is a socially established norm in today’s science that we disallow supernatural powers or God’s intentions as causes that give us scientific understanding. Epistemic values of understanding are not an innate part of our thinking. They are created because of intentions and social agreements, but as institutionalized values, they may still guide how people think. Just recall inductive reasoning, inference to the best explanation, or statistical thinking in science. These forms of reasoning obey both evolutionarily established standards of thinking and conventionally established context-dependent values. As we shall see, such socially imposed context-dependent values make successful understanding possible.

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Reflection-based Understanding Epistemic values of understanding arose with reflection-based thinking. Before humans could reflect on their experience, thinking, and action, there was no need for any normative commitments. All human thinking about the environment was carried out, almost as it is in non-human animals, in accord with some selectively adapted habits. Even when our ancestors gained the ability to talk about their own sensations, thinking, and behavior, they did this without consciously relying on cognitive standards or epistemic values. The important step in this development came when humans began contemplating their thinking about things existing beyond their immediate experience. Early in this cognitive evolution, things were explained and understood in terms of anima, regardless of whether they were animals, trees, plants, crops, water, stones, rivers, mountains, etc. It seems doubtful that such speculative projections required any specific norms of thinking and understanding. The situation completely changed when the Greeks began to reflect upon how to systematize mathematics and to justify naturalistic claims with empirical evidence. Aristotle developed a method of scientific understanding and delineated four forms of explanation. All this happened because he (and other philosophers) began to contemplate possible rules of human thinking and discovered some cognitive standards for bringing beliefs together. Later, the Arabic philosopher and scientist,  Ibn  al-Haytham, better known as Alhazen, as the outcome of his study of light, seems to have compiled and expanded on earlier reflections on an experimental methodology. He explained how he thought we could understand not only light, but every physical phenomena. Thus, I claim that only when we began a systematic and theory-guided investigation into nature was there any need for establishing certain methodological norms for how to understand nature correctly. Advanced reflection-based thinking requires using linguistically defined concepts to express non-sensory beliefs and therefore takes place in the context of human communication. Conscious acts of interpretations and explanations help us to organize those beliefs we acquire through investigation and public discourse. Their function is to connect

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what we already understand with what we previously did not understand. We may generate such explanations and interpretations ourselves, since in learning to participate in communication we have learned how to put questions and produce answers to ourselves. More often, however, explanations given by others inform us about the relationship between empirical facts or between empirical facts and theoretical assumptions. Explanation and interpretation offer understanding; but both explanation and interpretation also presuppose a certain amount of understanding. We could not produce explanations unless we already had a robust understanding of what it requires to give an explanation, what would count as an explanation given the state of ignorance, and what is required for an explanation to be successful as determined by whether or not the explanation is accepted by those being addressed. Explanation and interpretation are creations of human psychology, constructed in interpersonal communication, and based upon our sensory experience and ability to transform the material world by hand and technology. Hence, interpretation and explanation must be understood as cultural phenomena. These are phenomena we produce in response to our or others’ request for understanding, because we can participate in a social discourse of raising questions and giving answers. Our common ability to raise questions and to address them whenever we confront an epistemic problem provides us with reflection-based understanding. Therefore, I hold, that explanation and interpretation are best described as speech acts that offer different kinds of reflection-based understanding. In reflection-based understanding, different organizing mechanisms relate disparate beliefs to one another such that the connections fit our naturally evolved thinking patterns. So when we interpret or explain something outside the range of our immediate experience, we still use some of the cognitive schemas of understanding depending on what we particularly want to understand. Broadly speaking, reflection-based understanding consists of a web of complex relationships that incorporate a belief into a conceptual framework such that holding this belief is meaningful for the person involved. We may indeed form additional beliefs about the relations among such beliefs. In that case, we have what I call second-order reflective understanding.

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I disagree with those philosophers who assume understanding is a particular form of knowledge, e.g., causal knowledge.5 Indeed, we do have such knowledge, and we may certainly distinguish factual from conceptual understanding. Nevertheless, the distinction makes no difference. Truth is not a criterion for applying the concept of understanding (as it is to the concept of knowledge) and therefore not a condition for factual understanding either. Knowledge of factual matters may well give us understanding, but that does not make the factual understanding true. Understanding is a second-order cognitive ability that consists of a structural linking of first-order beliefs (information), regardless of whether these are acquired through the senses or through reason. It makes sense to speak of “truth” in connection with these first-order beliefs if their semantic content reflects what they are supposed to concern. By contrast, understanding itself has no propositional content. Instead, it makes sense to speak of correct or adequate understanding, if our beliefs are appropriately connected with our background assumptions. But, again, we may form beliefs about our understanding and therefore statements expressing those beliefs. This holds even more so in relation to theoretical understanding, where the organization happens according to some form of explanatory relationship. In science, for instance, explanations make use of representational devices like theories, models, diagrams, etc. I therefore agree with Henk de Regt and Victor Gijsbers who also reject what they call “the veridicality condition on understanding” namely “the claim that only representational devices that satisfy a criterion of representational veridicality can grant understanding.”6 However, one doesn’t even have to look into the history of science to find theories or models that are successful in explaining the phenomena in question albeit not ‘true.’ Many examples of representational devices current in science rest on contradictory representational conceptions but are very successful in their predictions. When I was studying physics, we were a group of students given the problem of an experiment concerning the collective movements in the  See, for instance, Grimm, S.R. (2014).  De Regt, H., & Gijsbers, V. (2016). “How false theories can yield genuine understanding”. In S. Grimm, C. Baumberger, & S. Ammon (Eds.), Explaining Understanding: New Perspectives from Epistemology and Philosophy of Science. London: Routledge. 5 6

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atomic nucleus of Hafnium. Before performing the experiment, we were taught two different interpretive models to calculate the various movements in the nucleus. The drop model represents the nucleus as a flexible water drop. Allegedly, this model would give us a precise treatment of phenomena concerning vibration and rotation of the nucleus. The other, the shell model, constructs the nucleus like an onion with the nucleons placed in different layers. This model helped us to describe how a single nucleon moves with respect to some of the other nucleons. Our textbook instructed us to use different models to represent Hafnium depending of what kind of problem we wanted to solve. 7 The structures of the two models are incompatible, because they build on different principles of construction. It makes no sense to argue that one is ‘true’ and the other not. Nonetheless, both models gave us insight into how to explain the results we received when bombarding the target system. However, de Regt and Gijsbers argue another condition is necessary for understanding: “We propose the effectiveness condition on understanding. This is the claim that understanding can only be gained from applications of representational devices that are, for a subject S in a context C, scientifically effective; where scientific effectiveness is the tendency to produce useful scientific outcomes of certain kinds.”8 In my opinion, this improves on de Regt’s earlier characterization of understanding as skills.9 Now, the focus is on how the scientist’s representation shows us that he or she understood the observed data and whether this understanding meets certain reasonable demands. However, I believe de Regt and Gijsbers miss the cognitive aspects of understanding. A scientific representation is a linguistic and mathematical expression of scientists’ understanding. Insight, connections, and comprehension are in our thinking and may give rise to effective representations. This understanding need not always be effective. As long as we are talking about scientific understanding, I agree that successful understanding has among other things to

7  See, for instance, Halliday, D. (1957). Introductory Nuclear Physics. Wiley & Sons; or Krane, K. (1987). Introductory Nuclear Physics. Wiley & Sons. 8  De Regt, H., & Gijsbers, V. (2016), p. 51. 9  For a criticism of identifying understand with skills, see Faye, J. (2014), pp. 34–37.

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be effective. But I would still claim that unsuccessful scientific understanding is, in fact, understanding, too. Referring back to an earlier work of de Regt and Dennis Dieks,10 de Regt and Gijsbers express a revised opinion: According to this theory, a phenomenon P is understood scientifically if and only if there is an explanation of P that is based on an intelligible theory T and that conforms to the basic epistemic values of empirical adequacy and internal consistency. A theory T is intelligible for a scientist S if, in one or more of its representations, it has qualities that facilitate its use by S. Intelligibility, then, is not an intrinsic property of a theory, but a contextual property that depends on, among other things, the skills of the scientist.11

De Regt and Gijsbers do not want to appeal to empirical adequacy or internal consistency. Instead, their central notion is the effectiveness of a representational device. However, by replacing epistemic values of empirical adequacy and consistency with effectiveness, they seem to ignore the difference between understanding and this understanding being effective. This is a mistake: de Regt and Gijsbers define scientific understanding such that effectiveness as evidence for successful explanation becomes a necessary component to characterize understanding. Of course, explanations in terms of a scientific theory may provide scientific understanding, but they also presuppose some basic or general form of understanding. Skillfully or effectively applying a representation requires understanding particular applicability conditions. An explanation is nothing but a specific way of communicating one’s understanding of the explicandum to somebody who has no understanding or understands the explicandum differently. (Or who accepts different standards.) A person ignorant of a certain state of affairs may ask different types of questions depending on his or her interests. With scientific questions, these are nearly always raised within the tradition of normal science, which confines what are regarded as intelligible questions and intelligible answers. Based on your  De Regt, H.,  & Dennis, D. (2005). A Contextual Approach to Scientific Understanding. Synthese, 79, 585–597. 11  De Regt, H., & Gijsbers, V. (2016), p. 55. 10

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understanding of this tradition, you may offer explanations but you may as well pose questions to the tradition, in case it seems incapable of explaining certain supposedly relevant phenomena. Today, in the present scientific context, for instance, angels are not part of any scientific understanding; hence, they are not used by scientists as part of any scientific representation, and therefore to appeal to them in an explanation cannot be part of any legitimate scientific explanation. But, whether or not angels pushing the planets provide us with understanding depends on our background assumptions, knowledge, and beliefs. Angels are not part of scientists’ background knowledge, because science can successfully explain planetary motion without them. Nevertheless, before the mechanistic worldview became widely accepted, reference to angels might have provided their proponents with understanding and a legitimate explanation. Thus, understanding is conceptually distinct from both skill and explanation. Scientific representations in terms of well-established theories and models render scientists’ collective understanding. For that reason, an explanation, formulated in terms of the conceptual framework of this theory, is the evidence we have for scientific understanding. In other words, the skills of scientists in using a certain theory and setting up a model to explain successfully a given phenomenon are the result of the understanding they have acquired of this particular problem. Skills presuppose some forms of understanding. Manifesting a skill signifies an underlying cognitive state of understanding, just as we consider any other behavior to be expressions of certain corresponding cognitive states. Skills are behavioral dispositions; whereas understanding is a cognitive state. I distinguish reflection-based understanding conceptually from representations as well as from representational skills and effectiveness of representations. To have scientific understanding is to be in a cognitive state, and representations are our evidence of this understanding. In contrast, effectiveness is an epistemic norm that may be imposed on any scientific representation. Not many would argue, like the logical positivists, that logical analysis proves that the mind is identical to the evidence we have for the mind. In a similar way, scientific understanding is not equivalent to what scientist can do, or actually do, but equivalent to the cognitive states that enable them to represent the world in terms of language or mathematics in the proper circumstances.

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Being able to represent our experience of the world, or some part of it, in a technical vocabulary, which may (or may not) include mathematical representation, is a minimal necessary condition, but not sufficient for scientific understanding. Understanding also requires being able to fit the phenomenon in question into our whole picture of the world, or at least that part of it that is of concern to that science, as I emphasized earlier. We may be able to describe a phenomenon quite precisely, even mathematically, and still not have any idea what to make of it, how to fit it into our picture of the world. Atomic and molecular spectra were an example of this before Bohr’s atomic model. In particular, we seek to fit phenomena into causal stories we tell about how the phenomena we experience come to happen. However, reflection-based understanding, of which scientific understanding is a part, is a result of experiential awareness and abstraction, and therefore often required to meet certain epistemic values in addition to mere effectiveness in the form of, say, predictive success. At least some of these values are highly relative to the context, to the individual person, or to the community sharing that understanding.

Epistemic Values and the Naturalist Stance Observational and experimental data underdetermine most, if not all, scientific hypotheses. Models and theories interpreted realistically appear to say more about the world than their empirical support. Hence, we can never attribute truth with certainty to a scientific hypothesis. When we actually do believe them to be true, we risk our induction being wrong.12 Therefore, scientists must rely on some values that can help them to minimize the risk of error and increase the probability that the hypothesis is true. Richard S. Rudner was among the first philosophers to point out that in such cases scientists necessarily make value judgments. He focused mainly on the validation of a single hypothesis against the null hypothesis, but he also mentioned the scientists’ dependence on values in  Hempel, C.G. (1960[1965]). Science and Human Values. Reprinted in his Aspects of Scientific Explanation. Free Press, 81–96. A more recent discussion happens in Steel, D. (2010). Epistemic Values and the Argument from Inductive Risk. Philosophy of Science, 77(1), 14–34. 12

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selecting alternative hypotheses.13 We may add that in both situations scientists make an inductive inference in the form of an inference to the best explanation. Thus, the values in question here are epistemic and concern scientific judgments, in contrast to non-epistemic values concerning social, ethical and aesthetic matters. Epistemic values are internal to science as they belong to the processes of discovery and justification, whereas non-­ epistemic values are external to the scientific practice itself, but may play a role in judging the social impact of scientific results. I dispute the view of some philosophers that such a distinction is impossible to draw. First, it is possible to distinguish between epistemic and non-epistemic values, because basic epistemic values in science stem from fundamental features of human cognition that are adaptations evolved by natural selection (while non-epistemic value have no such origin). Second, the epistemic values are naturally the aim of scientific understanding, because they reflect how natural selection has shaped our intellectual capacity of understanding. Natural selection constrains any system of beliefs or information to be organized in certain ways in order to provide us with understanding independently of the content of those beliefs. Philosophers have identified various epistemic values that narrow the gap between empirical data and scientific hypotheses. They maintain that scientists use these values in making it more likely that their hypothesis is true. The proposal is that, apart from being empirically confirmed, a hypothesis provides a better explanation than alternatives if it accords with certain specific epistemic values. Thomas Kuhn listed five such values that he claimed scientists use in choosing between competing explanatory hypotheses, including accuracy, simplicity, internal and external consistency, breadth of scope, and fruitfulness. He did not consider those five to be exhaustive but sufficiently distinct to make his point.14 But let me emphasize that even though Kuhn discussed these values in the context of the change of scientific theories when a choice between rival 13  Rudner, R.S. (1953). The Scientist Qua Scientist Makes Value Judgments. Philosophy of Science, 20(1), 1–6. 14  Kuhn, Thomas S. (1977). Objectivity, Value Judgment, and Theory Choice. In his The Essential Tension, 320–339. University of Chicago Press.

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alternatives is made, they may equally as well be taken into consideration whenever scientists present or justify a single hypothesis. A hypothesis has to be accurate in the sense that predictions derived from it accord with observations and experimental results. It must be internally consistent but also consistent with respect to other well-­ established hypotheses. It must contain a broader perspective as far as its explanatory powers go beyond what it was originally intended to explain. It should be simple and still bring coherence among numerous observations and experimental results that otherwise would have been cognitively unconnected. Finally, it has to prove fruitful by predicting new phenomena or by bringing forth new relations between well-established phenomena. Kuhn was aware of the fact that these values may be imprecise, that their mutual fulfilment may be partly exclusive, and that different scientists may emphasize one value over another. Thus, on the one hand, Kuhn argued that some epistemic values form the objective (intersubjective) grounds for the selection of alternatives; they are shared by almost all modern scientists throughout history and should be considered as trans-paradigmatic values. On the other hand, he also argued that the actual use of these values—on which observational cases they are invoked, and how they are prioritized—depends very must on the individual scientist or his or her community. Consequently, Kuhn argued that how values, accepted universally across different cultures, might actually be used depends on the context of a given culture. Other philosophers have presented longer lists of values. Inspired by William Newton-Smith, in which he enumerates most of them, I have pointed to eleven values that guide scientists in their choice between alternative hypotheses.15 These are precision, observational range, fertility, previous success, inter-theoretical support, uniformity, consistency, coherence with metaphysical assumptions, simplicity, quantitative formulizability, and novel predictions. Five values are the same as those mentioned by Kuhn. Other values, I mentioned, are included in those specified by Kuhn, but divided into separate ones. Internal and external consistency overlaps in Newton-Smith’s distinction between consistency,  See Newton-Smith, W.H.  (1987). The Rationality of Science. Routledge and Kegan Paul; and Faye, J. (2002). Rethinking Science. Ashgate. Reprinted in 2018 by Routledge. 15

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intertheoretical support, and coherence with relevant metaphysical assumptions. In addition, Kuhn’s characterization of fruitfulness seems to cover both Newton-Smith’s fruitfulness and his requirement of novel prediction. Other philosophers cite generality, refutability, empirical adequacy, and explanatory power; values that more or less overlap Kuhn’s accuracy and breadth of scope.16 Thus, there is surprising consensus among philosophers of science that the most important epistemic values for hypothesis preference are at least approximately those identified by Kuhn. Obviously, many of the values mentioned are not epistemic values, the way I use this term, because they refer to natural features of successful thinking, adaptations determined by natural selection, and not socially established norms for cognitive improvements. These natural features set the standards for how to behave or think successfully. In contrast, epistemic values, as I use that term, are conventional means for justifying the outcome of our behavior or thinking. For instance, the predictability of mathematical theories is an important value by which we judge their preferability. I shall therefore say that a value explicitly or implicitly prescribes how a scientific representation ought to be justified in order to reach scientific agreement, while a natural standard is a requirement of how to accomplish such a goal in attempting to make it successful. Together cognitive standards and epistemic values constitute the norms we have for evaluating interpretations and explanations in science. Nevertheless, some philosophers have argued that it is impossible to distinguish between epistemic and non-epistemic values. This claim is what Heather Douglas calls the boundary challenge.17 However, neither she nor Helen Longino, as we shall see, attempt to distinguish cognitive standards from epistemic values, which implies that they consider all values as arbitrary conventions. For instance, Helen Longino contests the value-­ free ideal, or rather the non-epistemic value-free ideal, by questioning  Quine, W.V.O., & Ullian, J.S. (1978). The Web of Beliefs. Random House, focuses on these values of science. See also the discussion in Longino, H.E. (1990). Sciences as Social Knowledge. Princeton University Press. 17  See Douglas, H. (2000). Inductive Risk and Values in Science. Philosophy of Science, 67, 559–579; and Douglas, H. (2017). Why Inductive Risk Requires Values in Science. In K.  C. Elliott & D. Steel (Eds.), Current Controversies in Values and Science, pp. 81–93. Routledge. 16

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whether epistemic norms can be clearly distinguished from non-­epistemic norms. If not, the value-free ideal becomes unattainable. She argues that (1) the backgrounds for choosing allegedly epistemic values are set for quite non-epistemic reasons and these values therefore are not so purely epistemic after all, and (2) when carefully examined the alleged epistemic values turn out to be rather arbitrary.18 In her defense, Longino assumes  that the presence and influence of social structures in science are pervasive. She claims that because the so-­ called epistemic values are contextual, they are inseparable from non-­ epistemic values. She also argues, partly on the basis of a feminist critique of traditional philosophy of science, that these values are replaceable by other values like epistemic adequacy, novelty, ontological heterogeneity, mutuality of interaction, applicability to human needs, and diffusion or decentralization of power. She maintains that we ought to have value diversity and allow space for deliberative processes of “critical interactions among scientists of different points of view (…) to mitigate the influence of subjective preferences on background assumptions and hence theory choice.”19 This, Douglas explains, requires setting up social structures with the tasks of creating “critical pressure on existing scientific approaches and for bringing new ideas into the fore, thus fostering debate and discussion.”20 Longino stresses that “the point of intersubjective interaction is to transform the subjective into the objective.”21 A feminist contextual approach, in turn, takes seriously so-called non-epistemic values. It recognizes that assumptions, values, and cultural interests shape scientific knowledge, including theory appraisal, and that contextual features always influence the commitment to one or another theory. A pluralist, open-minded, and curious, but persistently critical approach to science, offers the best chance for avoiding dogmatic and paradigmatic elements—sometimes masquerading as something they are not—in our scientific practices. Values are another component in the pursuit of  Longino, H.E. (1996). Cognitive and Non-Cognitive Values in Science: Rethinking the Dichotomy. In L.H. Nelson & J. Nelson (Eds.), Feminism, Science, and the Philosophy of Science. Kluwer Acedemic Publishers, 39–58, pp. 44–45. See also Douglas, H. (2017), pp. 6–7. 19  Longino, H.E. (1996), p. 40. 20  Douglas, H.E. (2017), p. 6. 21  Longino, H.E. (1996), p. 40. 18

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knowledge that a pluralist must scrutinize with a critical approach. When we aim at objectivity, we must use such a critical attitude to come even closer to knowing how the world really is independently of our efforts to know it—thus diminishing the influence from the canons of reasoning and other dogmas and habits in science. Longino’s point that different norms play an important role in theory choice is important, but I also think mistaken on some essential points. As noted above, Kuhn did in fact acknowledge the contextuality of scientific values, recognizing that they played a varying role depending on the scientists and the hypothesis under discussion and illustrating it with numerous historical examples. Second, even though the use of values is contextual, that does not imply that we cannot distinguish between epistemic and non-epistemic values, and therefore that epistemic values are arbitrary. Both moral and aesthetic values are contextual, but still distinct from epistemic values and from each other. As I have argued, epistemic values, in contrast to non-epistemic values, serve to improve the justification of scientific understanding. The social norms for choosing scientific theories are epistemic values, but they are nonetheless rooted in the biological evolution of our cognitive capacities. In contrast, non-epistemic values are requirements mostly shaped by human culture in order to promote political, economic and social interests. That such interests also find expression in science is unquestionable. Although norms are socially constructed, the cognitive standards for scientific understanding, which are the object of the epistemic norms in science, are identifiable as originating in our biological development. Evolutionary forces have played a significant role in shaping not only our evaluative attitudes but also the cognitive content of our evaluative attitudes. Facts about epistemic evaluation are independent of the evaluative process itself. For instance, the methodological standards behind inference to the best explanation are epistemic norms cultivated by human reflection about our inherited cognitive practices. Thus, the internal criteria of scientific understanding, such as justification, vary according to the epistemic context in which such an understanding takes place. Norms regarding empirical understanding differ from those of theoretical understanding, and those of physics almost certainly deviate from those of archaeology. In physics alone, some scientists

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might prioritize norms like mathematical rigor, unification, simplicity, and consistency to claim understanding, whereas others prefer norms establishing causal mechanisms, predictions, novel observations, and experiments. These norms are among the more generally required commitments. However, sometimes non-epistemic values may influence the choice of epistemic values like, for instance, statistical significance. The significance level of a scientific study is a matter of choice and typically set to 5 percent, but sometimes much lower—depending on the field of study and the (e.g. social or economic) cost of being wrong or more precise.22 But because non-epistemic values may influence which epistemic values we may choose, this does not prove that such a distinction makes little sense. A mutual agreement among members of a scientific community is gradually being formed about what they know and what they don’t know. In the natural sciences, individual testimonies involve presentations of empirical data and expositions of interpretive models to yield predictions and explanatory hypotheses. Correct predictions and explanatory powers are the epistemic values that most natural scientists feel committed to take into account with the purpose of reaching intersubjective agreement. Confirmed predictions undoubtedly establish the usefulness of an interpretive and explanatory model in the natural sciences. In these sciences, the correspondence of model predictions with observation reports are what really establish agreement among scientists about the empirical adequacy of the particular model in question. No model is ever vindicated by the entire scientific community unless it is consistent with the observational data. Predictability is an objective feature of mathematically formulated models, whereas the explanatory efficacy of a model does not have the same objective status. Unquestionably, explanations of phenomena by interpretive models play a central role in scientists’ agreements, but scientific explanations deliver understanding not empirical knowledge. Explanations and understanding are very much context-dependent. If people do share the same knowledge and background assumptions, they may—even as scientists—still disagree over whether an explanation expresses their understanding of the matter.  See Douglas, H. (2000).

22

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The above description hardly applies in the historical or social sciences; many of these sciences make no claim to predictions or only predictions of the most general kind. The primary goal of these sciences is establishing an historical story or an interpretive narrative about, say, a particular development of events that have already happened. For example, evolutionary biology may attempt to tell us, based on empirical evidence, the story of how human cognitive capacities actually arose. We can appreciate the function of interpretation and explanation in science only by recognizing their purpose is communicating understanding. Our appeal to theoretical representations of the world, whenever we offer explanations, requires that our ability to understand the world is a natural adaptation we have as conscious beings. Being conscious of our own thoughts also enables us to account for how we scientifically represent and explain phenomena. Therefore, I conclude that we must seek outside philosophy to get a better grasp of what scientific understanding is or can be. I claim that evolutionary biology and cognitive science are the right starting points to advance our insight into the role of cognitive standards and epistemic values in scientific understanding. Of course, the content of much human understanding is of another and more abstract kind than what we find among animals. However, there is no empirical reason to deny that animals apprehend and understand their environment to an extent that is cognitively similar to ours. Thus, as a natural phenomenon, understanding is the result of natural selection and cognitive adaptations. It can be described such that particular norms do not have a defining role in the general specification of understanding. I suggest understanding as the cognitive organization of beliefs and information determined by adaptations evolved by natural selection. Beliefs, we say, are either true or false, but the same does not hold for the organizing relations among our beliefs. Although these relations are neither true nor false, we may form beliefs about such relations, which are either true or false. Consequently, beliefs and understanding play different epistemic roles in explanation. As a social phenomenon, scientific explanation is a communicative act by which one person responds to another person’s request for reflective understanding, or perhaps to his or her own desire for understanding. The explanation brings understanding

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by connecting some beliefs in two ways: either by adding new beliefs previously unknown to a body of old beliefs or by connecting old beliefs in hitherto unknown or unexpected ways. To understand scientific knowledge we must appreciate science as a social and cultural manifestation of our biological and cognitive adaptations.

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Index1

A

Abstraction, 59, 83, 140, 171, 192, 194, 196, 235, 237, 253, 267, 268, 290 Affordances, 33, 73, 73n5, 85 Agreement, 118, 159, 170, 171, 177, 180n9, 190, 193, 202, 203, 208, 213, 214, 216, 220, 223, 227–229, 248, 249, 261, 263, 271, 293, 296 Alhazen (al-Haytham, Hasan Ibn), 284 Antunes, M., 57n30 Arbib, Michael, 39n11 Ardiel, Evan L., 44 Argument no-miracles, 256 Aristotle, 99, 175, 284 Aspects, Alain, 258

Audi, Robert, 19 Austin, John L., 206 B

Bartlett, Frederic, 39n11 Bennett, Jonathan, 58 Berlin, Brent, 125 Biala, G., 57n30 Bloom, Paul, 144 Bohr, Niels, 239n8, 250–252, 250n19, 250n20, 259, 260n35, 261, 263, 290 Boyd, Richard, 45, 255 Brandon, Robert, 113, 217 Burge, Tyler, 157, 224 Burke, Kenneth, 216 Burling, Robbins, 135, 138, 144 Byrne, Richard, 36n8

 Note: Page numbers followed by ‘n’ refer to notes.

1

© The Author(s), under exclusive license to Springer Nature Switzerland AG 2023 J. Faye, The Biological and Social Dimensions of Human Knowledge, https://doi.org/10.1007/978-3-031-39137-8

311

312 Index C

E

Call, Josep, 143, 144n15, 164 Callistel, Charles, 25n18 Carruthers, Peter, 58, 58n35 Cartwright, Nancy, 233n3, 244n11 Chalmers, David, 86, 87 Chang, Hasok, 237n6 Chomsky, Noam, 141, 145n17, 179n8 Clark, Andy, 33, 86, 87 Coady, C.A.J., 222, 223, 226 Cognition, 25 embodied, 62, 74, 83–85, 89, 90 Cognitive schemas, 26, 39, 70, 74, 79, 130, 169, 172, 173, 204, 248, 274, 276, 278, 280, 282, 283, 285 Communication standards of, 220, 221, 263 Content broad, 136, 153–163 narrow, 156, 158

Epistemic values, 279, 283, 284, 290–298 Evans, Christopher, 152 Explanation, vii, 26, 35, 40, 41, 44, 45, 47, 52, 57, 76, 86, 89, 138, 142, 144, 156, 165, 170, 182, 204, 224, 228, 236, 247, 256, 256n28, 269, 272–274, 282–285, 288, 289, 291, 295–297 Expression theory of meaning, 175

D

G

Dalton, John, 243 Darwin, Charles, 2, 3, 12, 31, 120 Davidson, Donald, 57 Davis, Wayne, 64, 137n3, 175, 176, 176n4, 178 De Regt, Henk, 286–288 De Waal, Frans, 33, 138n4 Dennett, Daniel, 58, 58n33 Descartes, René, vi, 2, 4, 12, 99, 100 Devitt, Michael, 82 Dewey, John, 5 Dieks, Dennis, 288 Douglas, Heather, 293, 294

Gärdenfors, Peter, 275n1 Gettier, Edmund, 202 Gibson, James J., 73n5 Gijsbers, Victor, 286–288 Goldman, Alvin, 10, 56, 103, 218 Goodman, Nelson, 122 Graham, K, 36n8 Grice, Paul, 175, 176 Griffin, Donald, 32n1

F

Felicity conditions, 204, 206–209, 227 Felix, Catherine, 96n26 Ferrigno, Stephen, 179 Fodor, Jerry, 17, 142n9 Foglia, Lucia, 85 Franklin, Anna, 124 Frege, Gottlob, 137n3, 176, 177

H

Habits of thinking, 142, 278, 280, 282, 283

 Index 

Hacking, Ian, 91n24, 248 Hamilton, William D., 182 Harder, Peter, 164, 167 Hesse, Mary, 259 Hetherington, Stephen, 92 Hobaiter, Catherine, 36n8 Hoefer, Carl, 255 Hume, David, 2–4, 13, 14, 65n2, 100, 188, 221–224, 226, 238 I

Information, 26 Interpretation, vii, 35, 67, 75, 150, 215, 220, 222, 223, 235, 242, 245, 245n12, 250n19, 250n20, 251, 259–261, 263, 272, 274, 278, 285, 297 J

Jelbert, Sarah, 75, 75n6 Johansson, Lars-Göran, vii, 233n3, 235n5, 257, 260, 264, 266, 267n43 K

Kant, Immanuel, 39n11, 49n24 Kay, Paul, 125 Keller, Helen, 91, 140 Knowledge, 25–27 acquaintance, 32, 48, 50, 82, 90 actional, 29, 71–77, 82, 83, 90, 237 behavioral, vii, 29, 73–77, 82, 91, 95, 101

313

concept-based, 29, 56–61, 82, 91, 105, 107, 109, 123, 131, 192, 196 conceptual, 68, 69, 97, 107, 108, 129, 130, 179 dispositional, 15–18, 48, 63 doxastic, 32, 33, 59 embodied, 8, 29, 62, 63, 71, 72, 75, 83, 85, 87, 93, 94, 102, 105, 106 empirical, 8, 13, 29, 30, 63, 101, 102, 105, 113, 142, 169–171, 175, 190–195, 201–205, 210, 225, 236, 237, 239–242, 246, 253, 261, 263–270, 277, 279, 296 experiential, vii, 8, 29, 30, 32, 53, 62, 63, 71–77, 89–91, 93, 106, 139, 169–173, 190–194, 201, 202, 204, 207, 210, 218, 225, 236, 237, 277 image-based, 29, 47–52, 60, 61, 63, 82, 91, 105, 123, 196 non-propositional, 28, 29, 63, 81, 89, 90, 96, 97, 171, 218 operational, 237, 237n6 performative, 237 practical, 83 propositional, 29, 52, 62, 81, 90, 96, 96n26, 97, 106, 107, 171, 203, 207, 214, 216, 218, 237n6 semantic, 68, 139, 142 sensory, 2, 4, 8, 10, 15, 17, 26, 29, 32, 52, 53, 59–62, 71, 74, 100–102, 104–110, 113, 114, 116–118, 120–124, 131, 139, 161, 203, 227, 229, 239, 240

314 Index

Knowledge (cont.) theoretical, vii, 8, 14, 30, 62, 63, 87, 106, 113, 131, 170, 204, 232–237, 242, 252, 262, 269, 270, 272 Kornblith, Hilary, 7, 10, 34, 40, 41, 43–45, 54 Kripke, Saul, 249 Kuhn, Thomas S., 260n32, 291–293, 291n14, 295

Mind extended, 80–91 Mitchell, John, 244 N

Nagel, Thomas, 241 Newer, Rachel, 134n1 Newton, Isaac, 257 Newton-Smith, William, 292 Norman, Donald, 73n5 Norton, John, 238, 239

L

Laplace, Pierre-Simon, 244 Latour, Bruno, 88 Lavoisier, Antoine, 243 Leplin, Jarrett, 254 Lewis, David, 28, 106, 181n10 Locke, John, 65n2, 175, 176 Longino, Helen, 293–295, 293n16 Lowe, Jonathan, 58 M

Macadoni, Joseph M., 152 Mach, Ernst, 260 MacKinnon, John, 149n18 MacWhinney, Brian, 144 Marno, Hanna, 165n34 Marzluff, John, 33 Mathematics, 263–270 Matsuzawa, Tetsuro, 126 Maxwell, Grover, 255 McGrath, Matthew, 56 Meaning sentence, 176 speaker, 175 word, 176 Millikan, Ruth, vi, 180, 181n10

P

Pauli, Wolfgang, 259 Perception, 24 Perović, Slobodan, 239n8 Piaget, Jean, 39n11, 128 Pinker, Steven, 138n4, 144 Plato, 99 Plotnitsky, Akady, 233n3 Poincaré, Henri, 260 Presentation, 23 conceptual, 152n21, 156, 159 Proust, Louis, 243 Proust, Marcel, 51 Psillos, Stathis, 255 Putnam, Hilary, 157, 158, 162 Q

Quine, W.V.O., 5, 122–124, 135, 138, 139n7, 264, 265, 293n16 R

Rankin, Catharin H., 44 Reliabilism, 218

 Index 

Representation, 23 semantic, 152n21, 156, 159 Rowbottom, Darrell, 21, 233n3, 250, 250n19, 262 Rudner, Richard S., 290 Russell, Bertrand, 48 Ryle, Gilbert, 81, 92 S

Santayana, George, 5 Self-awareness, 47, 109, 136, 167, 170, 171, 173, 180, 181, 184, 187–189, 198n25, 204, 205, 228 Sellars, Roy Wood, 5 Sellars, Wilfrid, 4, 102, 113–121, 123, 124 Sensation, 24 Speech acts, 204, 206, 206n3, 207, 211, 212, 216, 227, 228, 256n28, 272, 285 Spelke, Elisabeth, 126, 128, 129n23 Stanley, Jason, 81, 82, 96, 96n26, 97 Stephens, Andreas, 96n26 Suppes, Patrick, 259 T

Testimony, 25, 74, 208, 221–226 Tomasello, Michael, 143, 144n15, 164, 167

315

U

Ulbæk, Ib, vii, 138n4, 141, 144, 182n12, 183n14 Understanding, 27 empirical, 28, 275 epistemic values of, 279, 283, 284 experiential, 172, 274 linguistic, 173 practical, 27, 28, 62, 173, 175, 177, 274 propositional, 28 sensory, 274 standards of, 279, 283 theoretical, 28, 275 V

Van Fraassen, Bas, 233n3, 247, 256, 267 W

Wallis, John, 257 Weisberg, Jonathan, 22n16 Widell, Peter, 164, 167 Williams, Michael, 113, 217 Wilson, Margaret, 83, 84 Wilson, Robert A., 85 Wittgenstein, Ludwig, 4, 147, 148, 173, 189 Wray, Brad, 233n3 Z

Zentall, Thomas, 191