Philosophy and methodology of information: the study of information in the transdisciplinary perspective [10] 2019003541, 9789813277519

The book gives up-to-date, multi-aspect exposition of the philosophy and methodology of information, and related areas w

186 95 31MB

English Pages 576 [558] Year 2019

Report DMCA / Copyright


Polecaj historie

Philosophy and methodology of information: the study of information in the transdisciplinary perspective [10]
 2019003541, 9789813277519

Table of contents :
The Study of Information in the Context of Knowledge Ecology ix
Gordana Dodig-Crnkovic and Mark Burgin

Part I: Philosophy of Information 1

1. Subject Is No Object: Complementary Basis of Information 3
Piotr Bobtuc
2. Information and the Vision of Stephane Lupasco: Science,
Logic and Philosophy 41
Joseph E. Brenner
3. Information or Noise? 67
Terrence W. Deacon
4. Reflections on the Concept of “Objective Non-Reality” in Information Philosophy 79
En Wang
5. Rethinking Mencius Classical Debate on the Difference Between Humans and Animáis Based on the Philosophy of Information 89
Lu Wang
6. Philosophy of Information — Radical Changing Forcé of Philosophy 99
Kun Wu and Ping Wang
7. In the Light of Shadows: Tracing an Information Profile 121
Rossella Lupacchini
8. The Philosophy of Information as an Ethical Application
of Social Epistemology: Informational Ontogénesis and Philosophical-Symbolic Dilemmas 147
Gustavo Silva Saldanha, Vimcios Souza de Menezes and Rodrigo Porto Bozzetti

Part II: Methodology of Information 169

9. Information-Oriented Analysis of Discovery and Invention in Mathematics 171
Mark Burgin
10. Evolutive Information in the Anthropocene Era 201
Rodolfo A. Fiorini
11. Computationalism in a Dynamic and Distributed Eco-cognitive Perspective 265
Lorenzo Magnani
12. Theoretical Study of the Concepts of Information Defined as Difference and as Identification of a Variety 289
Marcin J. Schroeder
13. Factors Space and Mechanism-Based Artificial Intelligence Theory 315
Peizhuang Wang
14. Beyond Metaphorization: A Blochian View onto Chaos and Fractality 337
Rainer E. Zimmermann and Zhang Xiaomeng

Part III: Philosophy of the Study of Information 351

15. The Situated Nature of Informational Ontologies 353
Jordi Vallverdú
16. Discussion on the Necessity of Integrating Information Philosophy and Unified Information Science from the Perspective of Thomas Kuhn’s Paradigm Theory 367
Zhensong Wang
17. Research on the Modernity of Confucianism from the Perspective of Philosophy of Information 399
Jun Liu

Part IV: Methodology of Information Studies 409

18. Can Cybersemiotics Solve the Problem of Informational Transdisciplinar ity? 411
S0ren Brier
19. Ten Principies of Information Science 443
Pedro C. Marijuán and Jorge Navarro
20. Knowledge Structures and Conceptual Networks for Evaluation of Knowledge Integration 457
José María Díaz-Nafría, Mark Burgin and Blanca Rodríguez-Bravo
21. Universal Logics for Intelligent Information Processing 491
H. C. He, Y. Q. Zhou and Z. C. Chen
22. Information Ecology and Cognitive Justice: Core Valué and Methodological Principies of Information Ecology 515
O. Kang
23. Information Ecology: The Methodology for Information Studies 525
Y. X. Zhong

Citation preview

Http:// Wap



World Scientific Series in Information Studies - V o l .

PHILOSOPHYAND m eth o d o lo g y of Inform ation The Study of Information in the Transdisciplinary Perspective Editors

Gordana Dodig-Crnkovic Mark Burgin

World Scientific


World Scientific Series in Information Studies (ISSN: 1793-7876) Series Editor: Mark Burgin (University o f California, Los Angeles, USA) International Advisory Board: Soren Brier (Copenhagen Business School, Copenhagen, Denmark) Tony Bryant (Leeds Metropolitan University, Leeds, United Kingdom) Gordana D odig-C rn kovic (Málardalen University, Eskilstuna, Sweden) W olfgang Hofkirchner (ICT&S Center, University ofSalzburg, Salzburg, Austria) William R K ing (University o f Pittsburgh, Pittsburgh, USA)


Vol. 10 Philosophy and Methodology o f Information: The Study o f Information in the Transdisciplinary Perspective

edited by Gordana Dodig-Crnkovic & Mark Burgin Vol. 9

Information Studies and the Quest fo r Transdisciplinarity Unity through Diversity

edited by Mark Burgin & Wolfgang Hofkirchner Vol. 8

The Future Information Society: Social and Technological Problems

edited by Wolfgang Hofkirchner & Mark Burgin Vol. 7

Information Theory Models o f Instabilities in Critical Systems

by Rodrick Wallace Vol. 6

Information and Complexity

edited by Mark Burgin & Cristian S Calude Vol. 5

Theory o f Knowledge: Structures and Processes

by Mark Burgin Vol. 4

An Information Approach to Mitochondrial Dysfunction: Extending Swerdlow ’s Hypothesis

by Rodrick Wallace Vol. 3

Emergent Information: A Unified Theory o f Information Framework

by Wolfgang Hofkirchner

More information on this series can also be found at

World Scientific Series in Information Studies —

Vol. 10

PHILOSOPHYAND Methodology of Information The Study of Information in the Transdisciplinary Perspective


Gordana Dodig-Crnkovic Chalmers University of Technology & Málardalen University, Sweden

Mark Burgin University of California, Los Angeles, USA


Published by World Scientific Publishing Co. Pte. Ltd. 5 Toh Tuck Link, Singapore 596224 USA office: 27 Warren Street, Suite 401-402, Hackensack, NJ 07601 UK office: 57 Shelton Street, Covent Garden, London WC2H 9HE

Library of Congress Cataloging-in-Publication Data Ñames: Dodig Crnkovic, Gordana, 1955- editor. |Burgin, M. S. (Mark Semenovich), editor. Title: Philosophy and methodology o f information : the study o f information in the transdisciplinary perspective / edited by Gordana Dodig-Crnkovic (Chalmers University o f Technology, Sweden & Malardalen University, Sweden) and Mark Burgin (University o f California, Los Angeles, USA). Description: New Jersey : World Scientific, 2019. |Series: World scientific series in information studies ; volume 10 |Ineludes bibliographical references. Identifiers: LCCN 2019003541 |ISBN 9789813277519 (he : alk. paper) Subjects: LCSH: Information theory. |Interdisciplinary research. Classification: LCC Q360 .P4945 2019 |DDC 003/.54~dc23 LC record available at

British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library.

Copyright © 2019 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. This book, or parís thereof, may not be reproduced in anyform or by any means, electronic or mechanical, includingphotocopying, recording or any information storage and retrieval system now known or to be invented, without written permissionfrom the publisher

For photocopying o f material in this volume, please pay a copying fee through the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA. In this case permission to photocopy is not required from the publisher.

For any available supplementary material, please visit! 0.1142/11190#t=suppl

Desk Editors: V. Vishnu Mohan/Tan Rok Ting Typeset by Stallion Press Email: [email protected]


Introduction: The Study of Information in the Context of Knowledge Ecology


Gordana Dodig-Crnkovic and Mark Burgin

Part I: Philosophy of Information 1.

Subject Is No Object: Complementary Basis of Information

1 3

Piotr Bobtuc 2.

Information and the Vision of Stephane Lupasco: Science, Logic and Philosophy


Joseph E. Brenner 3.

Information or Noise?


Terrence W. Deacon 4.

Reflections on the Concept of “Objective Non-Reality” in Information Philosophy


En Wang 5.

Rethinking Mencius Classical Debate on the Difference Between Humans and Animáis Based on the Philosophy of Information Lu Wang





Philosophy of Information — Radical Changing Forcé of Philosophy


Kun Wu and Ping Wang 7.

In the Light of Shadows: Tracing an Information Profile


Rossella Lupacchini 8.

The Philosophy of Information as an Ethical Application of Social Epistemology: Informational Ontogénesis and Philosophical-Symbolic Dilemmas


Gustavo Silva Saldanha, Vimcios Souza de Menezes and Rodrigo Porto Bozzetti

Part II: Methodology of Information 9.

Information-Oriented Analysis of Discovery and Invention in Mathematics

169 171

Mark Burgin 10. Evolutive Information in the Anthropocene Era


Rodolfo A. Fiorini 11. Computationalism in a Dynamic and Distributed Eco-cognitive Perspective


Lorenzo Magnani 12. Theoretical Study of the Concepts of Information Defined as Difference and as Identification of a Variety


Marcin J. Schroeder 13. Factors Space and Mechanism-Based Artificial Intelligence Theory


Peizhuang Wang 14. Beyond Metaphorization: A Blochian View onto Chaos and Fractality Rainer E. Zimmermann and Zhang Xiaomeng



Part III: Philosophy of the Study of Information 15. The Situated Nature of Informational Ontologies


351 353

Jordi Vallverdú 16. Discussion on the Necessity of Integrating Information Philosophy and Unified Information Science from the Perspective of Thomas Kuhn’s Paradigm Theory


Zhensong Wang 17. Research on the Modernity of Confucianism from the Perspective of Philosophy of Information


Jun Liu

Part IV : Methodology of Information Studies 18. Can Cybersemiotics Solve the Problem of Informational Transdisciplinar ity?

409 411

S0ren Brier 19. Ten Principies of Information Science


Pedro C. Marijuán and Jorge Navarro 20. Knowledge Structures and Conceptual Networks for Evaluation of Knowledge Integration


José María Díaz-Nafría, Mark Burgin and Blanca Rodríguez-Bravo 21. Universal Logics for Intelligent Information Processing


H. C. He, Y. Q. Zhou and Z. C. Chen 22. Information Ecology and Cognitive Justice: Core Valué and Methodological Principies of Information Ecology O.



23. Information Ecology: The Methodology for Information Studies


Y. X. Zhong Author Index


Introduction: The Study of Information in the Context of Knowledge Ecology Gordana Dodig-Crnkovic and Mark Burgin


The Study of Information (SOI) and Related Research Fields

Philosophy and Methodology of Information is the first volume, which together with Theoretical Information Studies comprises the two-volume edition with the aim of laying out the foundation of the emerging research field of the Study of Information (SOI). It is based on the summit of the International Society for the Study of Information held in Gothenburg in 2017 ( This volume contains a selection of the best philosophical and methodological contributions from the Gothenburg sum­ mit, together with number of invited contributions of leading contemporary researchers in the field of the Study of Information. It is divided into four parts: Philosophy of Information, Methodology of Information, Philosophy of the Study of Information and Methodology of the Study of Information. This volume presents works that establish philosophical and method­ ological aspects of a new interdisciplinary/transdisciplinary field of study, with new ways of knowing and models of explanation, based on data-information-knowledge ecology (Capurro, 1990; Zhong, 2011; 2017; Burgin, 2017a; Burgin and Zhong, 2018), and transdisciplinarity (Burgin and Hofkirchner, 2017). It provides perspectives on information as a phenomenon which connects together, and enables new non-reductive unifications of phenomena otherwise studied in isolation within domains of particular Sciences, humanities, technologies and arts, as well as other fields dedicated to the study of information. Currently, specialized academic



G. D odig-Cm kovic & M . Burgin

fields divide human knowledge and experience into silos isolated from each other. Based on the research results of the domain-knowledge, the Study of Information seeks a new, networked approach to enable an inclusive view, from which future research projects transcending disciplinary boundaries will derive, based on understanding of information structures and processes underlying particular domains. The study of information involves a recursive process of analysis and synthesis through continuous learning — about the natural as well as synthetic/created/cultural worlds, and about their actors — living beings and artificial agents. The methodology varies between multidisciplinary and transdisciplinary methods (Burgin and Hofkirchner, 2017), ecological approach (Capurro, 1990; Zhong, 2011; 2017; Burgin, 2017a; Burgin and Zhong, 2018) and networking techniques (Díaz Nafría, Burgin and Rodriguez-Bravo in this volume) where different parts of the whole retain autonomy in constant communication with other actors/agents in the network of networks of knowledge sharing agents. Information is a topic addressed in a variety of educational and research fields: Information Science, Library Science, Library and Infor­ mation Science (LIS), Information Studies, Study of Information, Informatics, Bioinformatics, Foundations of Information Science (FIS), Information Philosophy (IP) and more. Almost forty years ago, Machlup and Mansfield identified 39 information-based disciplines (Machlup and Mansfield, 1982), while in 2011 Yan listed 172 information disciplines (Yan, 2011). When it comes to Sciences of information, Yan distinguishes three historically developed basic domains: Computer and Information Science, Library and Information Science and Telecommunications and Information Science. The historical development of new information-based fields followed the development of new information and communication technologies as well as new insights brought about in information processing, information storage and communication. An important contribution to the understanding of information and its mechanisms comes from its applications in natural Sciences (physics, chemistry and biology), cognitive Sciences, neuroscience, social Sciences and especially, models of social and individual cognition (cf., for example, (Von Baeyer, 2003; Frieden, 2004; Seife, 2006; Vedral, 2010)).

Each of the new and more detailed insights into the role of information in the control of living organisms from the level of molecular processes and up, through subsequent emergent levels of organization, points towards fundamentality of information (Deacon, 2011) and computation as the dynamics of information (Dodig-Crnkovic, 2011; 2017).



The Study of Information (SOI) as an emerging contemporary foundational framework is dedicated to building a broader, inter/cross/ transdisciplinary approach to information in its different forms based on ecological view of information and knowledge (Zhong, 2011; 2017; Burgin, 2017a; Burgin and Zhong, 2018). It emphasizes the dynamic connection between the parts (particular knowledge domains) and the whole and their mutual interactions, as well as their context dependence, where context is given by the awareness of the presence of the whole ecology of information entities — structures and processes in different domains and on different levels of abstraction. Zhong (2017) argües that information ecology cannot be adequately modeled by “divide and conquer” method in which the Sys­ tem is partitioned into independent parts. Instead, complex nature of the ecological system must be recognized and the essential role of interaction between its parts. Complexity of information is addressed in the works of Burgin and Calude (2016) and Schroeder (2016). The SOI differs in its scope and methods from all other currently existing approaches to information. For instance, when it comes to LIS, its unique concern is described as: Humans becoming informed ( constructing meaning) via intermediation between inquirers and instrumented records. No other field has this as its concern (Konrad, 2007, p. 660). The difference between SOI and LIS is that main interest of SOI is not in the human use of information (such as information search and retrieval, library management, knowledge management, knowledge organization, etc.) but in the structures and processes of information in all its manifestations including the human use of information. Scientific approaches to information are grouped under the umbrella term of Information Sciences. With respect to the domain, Information Sciences can be divided in the Technical, Natural, Cognitive and Social Information Sciences. The term “Theoretical Information Science” is used for different fields — from theoretical Computer Science to theoretical aspects of Information Science (comprising “IS” in “LIS” ). Theoretical information Science sometimes refers to the development of information technologies including computing, programming and telecommunication systems addressing modeling and analysis of information processing systems. Modeling typically involves formal-logic and algorithmic models of computing systems, analysis and verification; data transmitting protocols in information networks, algorithms and programs for information processing, etc.


G. D odig-C m kovic & M . Burgin

Informatics is the term used in Europe as synonymous to both Computing and Computer Science, where Computer Science is often dominated by the study of algorithms and “automated abstraction” . Interesting to note this connection between information as a structure and computing as a process which often come together (Dodig-Crnkovic and Burgin, 2011). Development of Information Philosophy/Philosophy of Information can be traced back to works of Floridi (2002) who describes its aims as 1. the criticai investigation of the conceptual nature and basic principies of infor­ mation, including its dynamics, utilization and Sciences and 2. the elaboration and application of information-theoretic and computational methodologies to philosophical problems. Along similar lines, it is possible to find works of other philosophers of information, such as Adriaans and van Benthem (2008) and Adriaans (2018). At the same time, Wu (2016) points to the interaction and convergence between the philosophy of information and Science of information, while Wu and Brenner (2017) propose viewing Phi­ losophy of Information as an informational meta-philosophy of Science. In addition, Herold (2001) elaborates the relationships between Librarianship and the Philosophy of Information. In sum, Philosophy of Information is a dynamic and diverse research field (Adriaans and van Benthem, 2008). One may ask why we don’t simply label this book “Philosophy of Information” instead of insisting on it being a part of the emerging field of The Study of Information. In the first place, we are doing this because we want to establish explicit knowledge ecology of information studies in which Philosophy of Information informs all other actors in the network of networks as well as being informed through mutual Ínteractions. Here we are elucidating these connections. Besides, we make a distinction between philosophy of information and philosophy of information studies treating methodology of information and logic of information as sepárate fields. We also want to emphasize essential dependence of The Study of Infor­ mation in general, and philosophy of information, in particular, on method­ ology of information and logic of information as essential parts of the Study of Information. Examples of work offering new logical perspectives are Brenner (2006) exploring transconsistent logic for model-based reasoning, Alio (2007) studying necessity of logical pluralism, and Brenner (2008) addressing the logic of transdisciplinarity. While van Benthem and van Rooij (2003) proposed the way of “connecting the different faces of information, van Benthem (2010) connects logical dynamics of information and interaction. In addition to connecting (in both ways) Philosophy of



Information with Sciences and technology, we also make connections with its methodological and logical foundations that are in a continuous evolution. We can see the development of the Study of Information within the IS4SI community as grounded in the activities of the Foundations of Infor­ mation network,, led by Marijuán (2013); UTI (Unified Theory of Information) network led by Hofkirchner (1999, 2017) and Glossarium Bitri network and information glossary project led by José María Díaz Nafría (Nafría et a/., 2016). All three networks focus on theory of information and its different aspects. In the publication area, the work of Mark Burgin as the Editor of the World Scientific book series on Information Studies 7Pt3 W is an important contribution to the progress of the research field. Burgin has also extensively published on data, information and knowledge (Burgin, 2010a, 2010b, 2011, 2016, 2017b). Other members of the IS4SI community have also essentially contributed to SOI: Rafael Capurro with the concep­ tual analysis of the concept of information (Capurro, 2009) and the study of the social aspects of its utilization (Capurro, 1990); Yixin Zhong with the development of information ecology as a methodological approach to the study of information (Zhong, 2011, 2017; Burgin and Zhong, 2018); and Gordana Dodig-Crnkovic with the study of dynamics of information in the form of morphological computation by cognizing agents (Dodig-Crnkovic, 2008, 2011, 2016, 2017). Deacon (2011) in his book Incomplete Nature: How Mind Emerged from Matter, addresses information as appearing in hierarchy of dynamic processes in nature — homeodynamics, morphodynamics and teleodynamics connecting biosemiotics, origins of life and philosophy of mind. 2.

Exploring Philosophy and Methodology of Information on Different Levels

In this volume, philosophy and methodology of information are explored through their various facets, with information as the fundamental concept that is changing philosophy and methodology of research and knowledge generation in general, and of the study of information, in particular, while philosophical and methodological insights affect our understanding of the information as a fundamental phenomenon. According to Howell (2013, p. 32), research (on a given topic) establishes the relationship through succession between philosophy (ontology and epistemology), theory, methodology and methods.


G. Dodig-Crnkovic & M . Burgin

Philosophy of Information: Philosophy of Information, as a part of philosophy, ineludes ontology, epistemology, ethics and aesthetics of information. The basic questions of the ontology of information being: how infor­ mation exists, what information is; how information functions, how it is generated, communicated and processed; relations of information to other fundamental phenomena and in particular, relations between data, knowledge and information. Existence of information, its processes and structures are derived from Sciences, which provide our best present day knowledge about the world (Zuse 1969; Wheeler 1990; Schmidhuber 1997; Wolfram,

2002). The basic questions of epistemology of information are: how knowledge about information is obtained; how knowledge about information is justified, the role of information in cognition and knowledge generation. With regard to epistemology, information is used both as an object of study and as a means of study. Again even in this respect, fundamental insights are made by connecting knowledge of diverse areas (Dodig-Crnkovic, 2017). Aesthetics of information is a vivid research field, dedicated often to visual arts and music and exemplified in the works of Schmidhuber (1997), Adriaans (2008), Kang Zhang et ai (2012) and McLean and Dean (2018). Methodology of Information: (The) methodology is defined as the research strategy that outlines the way one goes about undertaking a research project, (Howell, 2013, p. ix) whereas methods identify means/tools of knowledge generation. In this context, methodology of information studies methods of information observation, measurement, evaluation and utilization such as information production, acquisition, processing, preservation, protection, restoration, comprehension and communication. Philosophy of the Study of Information: It ineludes ontology, episte­ mology, ethics and aesthetics of the study of information. It explores the place of the study of information in knowledge production, its interaction with other scientific and technical/applied/practical disciplines, the goals of the study of information and how knowledge about information and information processes is obtained. Methodology of the Study of Information: The methodology of the study of information is the research strategy that outlines the way one goes about undertaking research projeets in the field of the study of informa­ tion, while methods of the study of information identify means of knowledge generation within the field of the study of information. This presents the



level of meta-theorizing with respect to the basic level of studies of the information phenomenon. Methodology of the Study of Information is con­ cerned with problems such as how different fields of study of information relate, how to organize studies of information and how to utilize knowledge obtained in the studies of information. 3.

C on trib u tion s to th e B o o k

T h e first part o f th e b o o k is dedicated to the Philosophy of Information, with chapters encompassing a broad spectrum of ontological and epistemological issues of information. Peter Boltuc sets the stage by investigating the fundamental philosophical question of differences between subject and object in the context of the Philosophy of Information. Joseph Brenner addresses information in Science, logic and philosophy through the visión of Stephane Lupasco. Terrence Deacon focuses on relativity of information. It is an important cognitive challenge in general and scientific problem, in particular, because in many situations it is hard to differentiate between information and noise. Indeed, relativity of information is affirmed in the first Ontological Princi­ pie of the general theory of information, which, in particular, States that empirically, it is possible to speak only about information for a system and not information in general (Burgin, 2010; 2017b). Analyzing the real situation in the history of Science, Deacon’s work gives a brilliant example of this principie. En Wang investigates the concept of “ Objective Non-Reality” connecting it to the phenomenon of information in the context of Information Phi­ losophy. The concept of non-reality, non-being and nothingness has been discussed both in Western and Eastern philosophy for millennia. In West­ ern philosophy, it goes back to the Sophist of Plato (1961) and to Physics of Aristotle (1984). In Eastern philosophy, this concept appears in Tao Te Ching by Lao Tse (cf. (Kirkland, 2004)): . . . advantage comes from what is; usefulness comes from what is not. Philosophers introduced different types and modes of non-being. For instance, Marius Victorinus splits non-being into four categories: negation, the nature of the other (secundum naturam alterius), as potential being, and as transcendent non-being (Victorinus, 1960; Piemonte, 1986). Eriugena defines five modes of being and non-being admitting that it is possible


G. D odig-Cm kovic & M . Burgin

to find more by crafty reasoning (Moran, 1989). Contemporary approach goes even further being able to differentiate between non-reality, non-being or nothingness (Burgin, 2012). Lu Wang analyzes the difference between humans and animáis based on the philosophy of information in a twodimensional attributive setting. Kun Wu and Ping Wang argüe for the Philosophy of Information as a radical changing forcé in philosophy as a whole. Indeed, all cognition, including philosophical cognition, is based on information acquisition, procession and comprehension. Rossella Lupacchini’s contribution presents a broad picture of reality starting with Plato’s Allegory of the Cave and going through theories of painting to quantum interference to Leibniz’s monads to photons and light to matter to quantum computation, quibits and information. In her exposition, Lupacchini contrasts light and shadow in her qualitative characterization of the phenomenon of information. Gustavo Saldanha, Vinícios Souza de Menezes and Rodrigo Bozzetti explore informational ontogénesis and philosophical-symbolic dilemmas in the context of ethical applications of social epistemology. In particular, they persuasively disprove the ridiculous contention of Luciano Floridi that infor­ mation Science as applied philosophy of information. Floridi’s declaration means that information scientists, e.g., Shannon or Kolmogorov, applied philosophy to build their mathematical theories of information and this completely contradicts reality. In essence Floridi’s declaration is similar to the assertion that natural Sciences, e.g., physics or chemistry, are applied philosophy of nature, i.e., ontology. The second part of the book, Methodology of Information, treats the research strategies involving study of information. Mark Burgin explores relations between information-based knowledge discovery and the processes of invention in the realm of mathematical creativity, based on the information core of both processes and the global structuration of the world in the form of the Existential Triad. The goal is to provide an explanation, argumentaron and empirical evidence validating the claim about existence of both processes in mathematics. Rodolfo Fiorini’s contribution presents evolutive information as an idea whose specific and contingent understanding involves interdisciplinary, trans-disciplinary, cultural and ontological multi-perspectives in the context of Cybersemiotics (Brier, 2008). Lorenzo Magnani describes the connection between information, computation and cognition explicating the evolutionary emergence of

information, meaning and cognition in humans, as the outcome of dynamic co-evolutionary Ínteractions between brain/mind processes, body and environment. Marcin Schroeder’s contribution provides scientifically motivated mathematical foundation for a dual role of information as “a difference that makes a difference” and as “identification of a variety” based on the ideas of invariance and symmetry. In such a way, Schroeder explicates two types of information, which are important special cases of the general concept of information which is described in the general theory of information. It is possible to obtain these two types by a relevant choice of the infological systems (Burgin, 2010). This gives additional evidence that the general theory of information encompasses all kinds and types of information. At the same time, it is necessary to accentuate that existence of the general theory of information does not decrease the role and importance of various special information theories, such as Marcin Schroeder’s infor­ mation theory (Schroeder, 2015) or Krassimir Markov’s information theory (Markov et a/., 2006). We can see how theories of groups, of rings and of fields occupy principal places in mathematics although all of them are special subtheories of the theory of universal algebras (Cohn, 1965). Wang Peizhuang proposes a unified mechanism for the transformation of information into knowledge in artificial intelligence, synthesizing in such a way characteristics of structurgjism, functionalism and behaviorism. Rainer Zimmermann and Xiaomeng Zhang study the grounds for the concepts, formal or hermeneutic, in the relationship of philosophy and the Sciences, as well as in relation to the arts. T h e th ird part o f th e b o o k is dedicated to the Philosophy of the Study of Information. In the opening chapter, Jordi Vallverdú explores the situated nature of information ontologies. Wang Zhensong argües for necessity of integration of information Science with information philosophy to form a unified knowledge field. Liu Jun demonstrates modernity of Confucianism from the perspective of the philosophy of information. In particular, we know that Confucius * thoroughly considered knowledge and its sources paying much attention to ñames as carriers (bearers) of information about reality (Confucius, 1979): If ñames be not correct, language is not in accordance with the truth of things. If language be not in accordance with the truth of things, affairs cannot be carried on to success.


G. Dodig-Crnkovic & M . Burgin

At the same time, ñames play more and more important roles in the contemporary technology in general and Computer networks such as the Internet, in particular (cf., for example, (Shoch, 1978; Ballintijn et a/., 2001; Burgin and Tandon, 2006)). T h e fou rth (last) part of the book is devoted to Methodology of the Study of Information. Spren Brier’s contribuí ion presents an argument for using the cybersemiotics approach for building a foundation of the transdisciplinary study of information. Pedro Marijuán offers ten principies of information Science as methodological principies of its development. These principies are oriented towards life Sciences and are aimed at a transition from a fragmented landscape of information fields to a consistent disciplinary body of the unified “infor­ mation Science,” which is critically important because blinded by the contemporary promises of global big data researchers barely recognize the perils and pitfalls of information contained in these data and its acquisition.

José María Díaz Nafría, Mark Burgin and Blanca Rodriguez-Bravo ded­ ícate their chapter to the study of conceptual representation of knowledge. They develop a mathematical model of conceptual knowledge representa­ tion and suggest knowledge integration based on this model, network tech­ nology and formation of a hypertext of conceptual knowledge. Huacan He, Y. Q. Zhou and Z. C. Chen propose Universal Logics for intelligent information processing required by information ecology. Ouyang Kang uses Information Ecology to explore Cognitive Justice through its Core Valúes and Methodological Principies. The concluding chapter, written by Yixin Zhong, argües for information ecology as a fundamental methodological approach of the Study of Information. In sum, this book gives an up-to-date multi-aspect exposition of contem­ porary studies in Philosophy and Methodology as being addressed in the field of the Study of Information. Collaboration of researchers from different research fields opens new perspectives for innovative developments in a variety of areas of Sciences, humanities and technologies with applications. The book is aimed at readers who conduct research into fundamental aspects of information, information society and information technology. It opens new perspectives for those who develop or implement scientific, technological or social applications, and especially for those who are participating in setting the goals and policies for Science in general, and Sciences of information in particular.



A ck n ow led gm en ts Last but not least, the editors want to express their gratitude to all the contributors to this project. It was a great pleasure to collaborate! The majority of the detailed review process has been done in an open and transparent forum of the research community. Special thanks are due to Yixin Zhong, President of the China Chapter of the Society for the Study of Information, who played the central role in the preparations of contributions from China Chapter for both volumes. B ib liog ra p h y Adriaans, P. (2008) Between order and chaos: The quest for meaningful information. Theory o f Computing Systems 45 , 650-674. Adriaans, P. (2018) “Information”, The Stanford Encyclopedia o f Philosophy (Winter 2018 Edn.), E. N. Zalta (ed.), ( es / win2018/ent ries / inf ormat ion /) . Adriaans, P. and van Benthem, J. F. A. K. (eds.) (2008) Handbook o f Philosophy o f Information (Elsevier Science). Alio, P. (2007) Logical pluralism and semantic information. Journal of Philosophical Logic 36 (6), 659-694. Aristotle, (1984) The Complete Works o f Aristotle (Princeton University Press, Princeton). Ballintijn, G., van Steen, M. and Tanenbaum, A. S. (2001) Scalable user-friendly resource ñames. IEEE Internet Computing 5 (5), 20-27. Brenner, J. E. (2006) A transconsistent logic for model-based reasoning, in Proceedings o f the 2004 Pavia Conference — Model-Based Reasoning in Science and Engineering, L. Magnani (ed.) (K ing’s College Publications, London), pp. 353-378. Brenner, J. E. (2008) The logic of transdisciplinarity, In Transdisciplinarity. The­ ory and Practice, Basarab Nicolescu (ed.) pp. 155-163. Brier, S. (2008) Cybersemiotics: Why Information is not Enough (Toronto University Press, Toronto, ON, Cañada). Burgin, M. (2010a) Theory o f Information: Fundamentality, Diversity and Unifícation (World Scientific, Singapore). Burgin, M. (2010b) Information operators in categorical information spaces. Information 1 (1), 119-152. Burgin, M. (2011) Information in the structure of the world. Information: Theories & Applications 18 (1), 16-32. Burgin, M. (2012) Structural Reality (Nova Science Publishers, New York). Burgin, M. (2016) Theory o f Knowledge: Structures and Processes (World Scien­ tific, Singapore). Burgin, M. (2017a) Principies of general ecology. Proceedings 1 (3), 148. doi:10.3390/IS4SI-2017-03996.


G. D odig-Cm kovic & M . Burgin

Burgin, M. (2017b) The general theory o f information as a unifying factor for information studies: The noble eight-fold path. Proceedings 1 (3), 164. doi: 10.3390/IS4SI-2017-04044. Burgin, M. and Calude, C. S. (2016) Information and Complexity (World Scientific, Singapore). Burgin, M. and Hofkirchner, W . (eds.) (2017) Information Studies and the Quest fo r Transáisciplinarity: Unity through Diversity (World Scientific, Singapore). Burgin, M. and Tandon, A. (2006) Naming and its regularities in distributed environments, In Proceedings of the 2006 International Conference on Foundations of Computer Science (CSREA Press), pp. 10-16. Burgin, M. and Zhong, Y. (2018) Information ecology in the context of general ecology. Information 9 (3), 57. Capurro, R. (1990) Towards an information ecology, in Information and Quality (Wormell, I. ed.) (Taylor Graham, London), pp. 122-139. Capurro, R. (2009) Past, present, and future of the concept o f information. tripleC 7 (2), 125-141, h ttp:// p/tripleC /article/view /113. Cohn, P. M. (1965) Universal Algebra (Harper & Row, New York). Confucius, (1979) The Analects (Harmondsworth, New York). Deacon, T. (2011) Incomplete Nature: How Mind Emerged from Matter (W .W . Norton & Company, New York). Díaz Nafría J. M., Gutiérrez, P. M. and Alemany, S. F. (2016) Glossarium BITri: Glossary of Concepts, Metaphors, Theories and Problems Concerning Information. Dodig-Crnkovíc, G. (2008) Knowledge generation as natural computation. Journal of Systemics, Cybernetics and Informatics 6 (2), 12-16. Dodig-Crnkovíc, G. (2011) Dynamics o f information as natural computation. Information 2 (3), 460-477. Dodig-Crnkovíc, G. (2016) Information, computation, cognition. agency-based hierarchies of levels, In Müller V. C. (ed.), Fundamental Issues of Artificial Intelligence, Synthese Library, Vol. 377, pp. 139-159 (Springer International Publishing, Switzerland), DOI 10.1007/978-3-319-26485-1-10. Dodig-Crnkovíc, G. (2017) Nature as a network o f morphological infocomputational processes for cognitive agents. European Physical Journal: Special Topics 1951-6355 226 , 181-195. Dodig-Crnkovíc, G. and Burgin, M. (2011) Information and Computation (World Scientific, New York/London/Singapore). Floridi, L. (2002) W hat is the philosophy o f information? Metaphilosophy 33 , 123-145. Floridi, L. (2011) The Philosophy o f Information (Oxford University Press). Frieden, B. R. (2004) Science from Fisher Information: A Unification, 2nd edn. (Cambridge University Press, Cambridge, UK). Herold, K. R. (2001) Librarianship and the philosophy of information. Library Philosophy and Practico 3 (2), 1-15. Hofkirchner, W (ed.) (1999) The quest for a unified theory o f information, In Proceedings of the Second International Conference on the Foundations of



Information Science. World Futures General Evolution Studies (Gordon and Breach Publ, Amsterdam). Hofkirchner, W . (2017) Emergent Information. A Unified Theory of Information Framework. World Scientific Series in Information Studies, Vol. 3 (World Scientific). Howell, K. E. (2013) An Introduction to the Philosophy of Methodology, Kindle edn. (SAGE Publications). Kirkland, R. (2004) Taoism: The Enduring Tradition (Routledge, London). Konrad, A. (2007) On inquiry: Human concept formation and construction of meaning through library and information Science intermediation. University of California, Berkeley. h ttp://escholarsh /ls76b6hp. Machlup, F. and Mansfield, U. (1982) The Study of Information: Interdisciplinary Message (John Wiley &; Sons: New York). Marijuán P. C. (2013) The uprising of the informational: Towards a new way o f thinking in information Science, In Proceedings o f the First International Conference on Philosophy of Information. X i’an Jiaotong University. Marius, V. (1960) Traites theologiques sur la Trinite, P. Hadot and P. Henry (eds.), 2 vols., SC nos. 68, 69 (CERF, Paris). Markov, Kr., Ivanova, Kr. and Mitov, I. (2006) Basic structure of the general information theory, International Journal: Information Theories & Applica­ tions 14 (1), 5-19. McLean, A. and Dean, R. T. (2018) The Oxford Handbook o f Algorithmic Music (Oxford University Press). Moran, D. (1989) The Philosophy o f John ScottusEriugena. A Study of Idealism in the Middle Ages (Cambridge University Press, Cambridge). Piemonte, G. (1986) L ’Expression quae sunt et quae non sunt: Jean Scot et Mar­ ius Victorinus, In G. H. A llafd'(ed .), Jean Scot ecrivain, Institut d ’Etudes Medievales, Montreal, pp. 81-113. Plato, (1961) The Collected Dialogues of Plato (Princeton University Press, Princeton). Schmidhuber, J. (1997a) A Computer scientist’s view o f life, the universe, and everything. Lecture Notes in Computer Science 1337 , 201-208. Schmidhuber, J. (1997b) Low-complexity art. Leonardo 30 (2), 97-103, MIT Press. Schroeder, M. J. (2015). Structural and quantitative characteristics of informa­ tion and complexity. In M. Kondo (ed.), RIMS Kokyuroku, No. 1964, Kyoto: Research Institute for Mathematical Sciences, Kyoto University, pp. 88-97. Schroeder, M. J. (2016) Hierarchic information Systems in a search for methods to transcend limitations o f complexity. Philosophies 1 (1), 1-14; doi: 10.3390/philosophiesl010001. Seife, C. (2006) Decoding the Universe: How the New Science of Information Is Explaining Everything in the Cosmos, from Our Brain to Black Holes. (Penguin Group Inc.: Brockman, CA, USA). Shoch, J. (1978) Inter-network naming, addressing, and routing, In Seventeenth IEEE Computer Society International Conference (C O M PC O N ), pp. 72-79.


G. Dodig-Crnkovic & M . Burgin

van Benthem, J. F. A. K. (2010) Logical Dynamics o f Information and Interaction (Cambridge University Press). van Benthem, J. F. A. K. and van Rooij, R. (eds.). (2003) Connecting the different faces of information. Journal o f Logic, Language and Information 12 (4), 375-379. Vedral, V. (2010) Decoding Reality: The Universe as Quantum Information (Oxford University Press). Von Baeyer, H. C. (2003) Information: The New Language o f Science (Weidenfeld & Nicolson, London). Wheeler, J. A. (1990) Information, physics, quantum: The search for links. In W . Zurek (ed.) Complexity, Entropy, and the Physics o f Information (AddisonWesley, Redwood City, C A). Wolfram, S. (2002) A New Kind o f Science (Wolfram Media Inc). Wu, K. (2016) The interaction and convergence of the philosophy and Science of information. Philosophies 1 (3), 228-244. Wu, K. and Brenner, J. (2017) Philosophy of information: Revolution in phi­ losophy. Towards an informational metaphilosophy of Science. Philosophies 2 (4), 22. Yan, X. S. (2011) Information Science: Its past, present and future. Information 2 (3), 510-527. doi:10.3390/info2030510. Zhang, K., Harrell, S. and Ji, X. (2012) Computational aesthetics: On the com­ plexity of computer-generated paintings. Leonardo 45 (3), 243-248. Zhong, Y. (2011) Unity-based diversity: System approach to defining information. Information 2 (3), 406-416. Zhong, Y. (2017) Information ecology and information studies. Proceedings o f the ISfSI 2017 Summit Digitalisation fo r a Sustainable Society 1 (3), 200. Zuse, K. (1969) Rechnender Raum (Friedrich Vieweg & Sohn, Braunschweig) (Translated as “Calculating Space” MIT Technical Translation AZT-70-164GEMIT, MIT (Proj. M AC), Cambridge, MA, Feb. 1970).


Philosophy of Information

Chapter 1

Subject Is No Object: Complementary Basis of Information Piotr Boltuc

University of Illinois Springfield One University Plaza, UHB SOSO Springfield, IL 62703, USA Warsaw School of Economics, Poland [email protected] com Subject is not an object, at all. This is true as long as we try to analytically purify those notions. W e move the objects to one side of the equation, irrespective of their ontological status: material, mathematical, phenomenal objects, even qualia. W h a t’s left on the other side is epistemicity , which is the subject side of the atomic subject-object relationship. On the other side is the theory of potential objects. Only interaction between subject and object results in onto­ logical reality; it allows for information as their shaped relationship. I build very little here, while standing on the shoulders of somewhat unexpected giants: W e enjoy early Fichte and Husserl-style puré subject ( contra K an t’s transcenden­ tal subject busy with categorizing things); Leibniz’s argument that unknowable universes cannot exist segues into the ontological condition of epistemicity; I follow Russell 1921, making a complementary scaffolding that starts by juxtaposing first- and third-person epistemologies; I follow Plato, Peirce, and Burgin in exploring triadic structures that transcend the basis of subject-object complementarity. The non-reducible first-person subject is shown as not merely epiphenomenal. I spend some time demonstrating how privileged access may no longer be quite privileged (Gallant’s experiment) and how Jackson’s M ary’s problem consists in her lacking the word-to -phenomenal-content link in her cognitive architecture. The main point of this part of the argument is to dis­ perse the mist of qualia that hazes over the non-reductive subject. This exposes information as always already information for an epistemic subject, for some general consciousness.




P. Boltuc

Easing In

Das Subjekt ist kein Objekt. The most reduced notion of the subject is not any object. It is the locus of epistemicity. Such an object, apart from any subject, is mere potentiality. Leibniz was right in that the possible world, which is not causally connected with our world, cannot exist, since we would have no reason to assert its existence. Assertability produces an epistemic condition of any ontology. Also, epistemology without ontology is empty. Even subjects of phenomenal experience are subjects nevertheless — it is impossible to be epistemically aware of nothing. The above is true of the most reduced notion of subject (Fichte’s or Husserl’s) and object (Russell’s atomic object). A similar structure replicates at the level of building consistent conceptual frameworks, or basic philosophies. Non-reductive epistemic subject is impossible to establish within ontology. Epistemic subject boils down to an epistemic grasp of objects, but such epistemicity itself can never be grasped. Likewise, ontological entities are impossible to establish within first-person epistemology. Here comes an unexpected analogy between the status of subject-perspective and object-perspective: Within ontology, puré subject seems epiphenomenal — it changes nothing in the causal structure of the world, and postulating it is superfluous within ontic framework. Surprisingly, within consistent firstperson epistemology, those are ontological objects that seem epiphenomenally unnecessary (Berkeley saw this, but failed to provide its non-religious account.) Thus, in a purely epistemic (phenomenal) frame of mind, objects with ontologies that go beyond phenomenal experience become ... well ... strangely epiphenomenal. They change noting in the workings of such a world, and the postúlate of their existence turas out to be superfluous. Those perspectives function complementarily. If any ontology is impossible without relation to the subject, then this is even more so specifically for ontology of information. Exemplis gratias, Floridi’s theory of information is built as an ontology. He tries to provide its epistemological grounding with his Kantian starting point, but replaces it with realism along the way.a If we are to take Leibnizian condition of epis­ temicity seriously, Floridi’s theory of information would be better viewed

aThis is shown in Sec. 8.

Subject Is No Object: Com plem entary Basis of Information


as an epistemology; yet this would be a different mode of his theory than the one he emphasizes. Burgin’s General Theory of Information provides a conceptual framework within which this article can be seen as a study on some of the basic philosophical grounding issues in ontology of information. In particular, ontology must always be grounded in epistemicity and, vice versa, episte­ mology must always be defined in relation to some objects. My focus on epistemicity could easily be misunderstood as anthropologization and subjectivisation of information theory. Yet, epistemicity does not lead to anthropocentrism or subjectivism: Today’s theory of Artificial General Intelligence is an empirically grounded view that presumes continuity between human, animal and artificial cognitive architectures. In particular, Goertzel’s cognitive synergy approach [Goertzel] shows how epistemicity does not have to be human-centric. This has been a broad-brush roadmap; now we are ready for a proper introduction. 2.

In tro d u ctio n

In this chapter, we tackle one of the deepest issues in philosophy: the relationship between the two sides of the human experience. Some cali it subjective and objective, others mind and body, or self and the world, or awareness and its object, still others the epistemic and ontological viewpoint. We argüe for the following methodological approach: To begin with, one should look for the most basic, reduced conceptual framework. Only clarity at the starting level gives us the sharp distinctions required to go beyond those basic dichotomies. It makes sense to distinguish the subject from all the objects. The objects may have different ontologies, some are material things outside of our bodies, others are objects of thought (thus, confabulations of our minds), still other objects may be theoretical generalizations built upon directly observable ones. Many philosophers think that the subject (self) has a special status among the objects. We argüe that such status is very special indeed, since — in its most straightforward sense — the subject is not an object at all! It can be viewed, metaphorically, as a mirror that reflects the objects of all kinds, while not being any of them; but this is merely a metaphor. The subject, in its most reduced sense, is not an ontological object. It is nothing but puré potential for epistemicity. In its less reduced sense, it appears as an object to others, and to oneself — but this is more of


P. Bottuc

its outer shell, which in fact is an object. Objects that are not subjects may internet in the universe of possibilities, but they are merely potential; they can be said to actually exist only as, and as soon as, they present themselves to a consciousness (thus, an epistemic subject). In the ontological narrative, objects are possible if and only if such (subject-object) interaction occurs with a special higher-level-object — the one that is characterized by direct epistemicity. This point requires an explanation: atomic objects do not have epistemicity — since puré epistemicity is not an object. Yet, objects form more complex structures, high-level monads of sorts. Some such higher order structures have the feature of first-person epistemicity. This is the subject viewed from the outside, which is objectified as an it. The relation of epistemic objects is much like Leibnitz’s conscious monad among the unconscious ones. This point can fully be appreciated only in the complementary framework, in which we see the first-person (epistemic) perspective as one aspect of the world accessible to human cognition, and the third-person (ontolog­ ical) perspective as the other aspect. None of those aspeets has priority — just like in the old-style wave-corpuscular theory of light, each of the com­ plementary descriptions has some unique advantages over the other. There also has been no known more general framework allowing one to retranslate the two complementary frames. It is possible that, one day, humans may discover that we have more such cognitive viewpoints (the second-person relationship is a strong contender in philosophical anthropology and ethics), or we may even attain an overarching meta-theory. But the complementary framework, of the puré subject of epistemicity and the puré ontological object, seems to be the most analytically reduced, and henee conceptually most basic, perspective. The complementary framework looks like the right way to gain more than we would be able to endorse within the solé theory, either puré phenomenalism (on the subjective side) or reductive physicalism (on the objective side). This way we do not have to cut human experience to fit within the Procrustean bad of one limited framework, whether phenomenalism or a sort of reism. We work with the most reduced notion of puré subject, based on Husserl’s view of the passive transcendental subject, which may rely on the puré transcendental subject from Fichte’s second introduction to the theory of knowledge (which is only a distant relative to Kant’s transcen­ dental subject active in the process of constituting the world). Importantly, we also endorse Leibnitz’s point that possible worlds that do not Ínteract with our known universe cannot exist — this is just because we would not

Subject Is No Object: Complementary Basis of Information


have any reasons to make judgments about them. This simple point establishes strong (sine qua non) relevance of epistemology for ontology. Every ontology seems to need epistemicity to acquire its fully blown ontological status — and not just a status as potentiality. Information-based ontology is an ontology after all; so, Leibniz’s argument about unknowable possible worlds applies. We try to demónstrate that the epic attempt of Floridi to have ontology (and ethics) based on information reveáis the edge beyond which ontology always already turns into (or, at least turns towards) epistemology. Critiques by Beni {the theory of information is not grounded in ontology but epistemology [Beni]), Barker (the too much information approach [Barker]) and Fultot (the information as a servant to entropy approach [Fultot]) may be viewed as one way of exposing the need to center informational ontology around epistemicity. The epistemic framework needs to be added to the supposed infinity of subject-less information advocated by Floridi. If so, epistemic subject is sine qua non of any ontology, and thus sine qua non of ontology based on information. After múltiple introductions, it is time to move to the main body of the chapter, and to move a bit more slowly at that. 3.

S u b je ct and O b je c t

Das Subjekt ist kein Objekt — this Germán sentence conveys the idea that “the subject does not belong to the set of all and only objects” ; it does so a bit more clearly than the English “A subject is not an object.” The English versión may easily be misinterpreted as a trivial idea, analogous to the sen­ tence “an apple is not an orange” . Our point is that epistemic subject is not an ontological object at all, it does not directly belong to the class of objects. It belongs to the class of objects only indirectly. The subject presents itself through the manner in which it is to the other observers (and also to oneself, if put in some sort of metaphysical mirror that places it among the objects in the world). This happens if one engages in self-reflection, proprioception or, say, watches oneself in a mirror. The subject under such description manifests itself through objects, a bit like a ray of light, or a shadow. In most situations, people talk of subjects in a broader way, as complex objects with some epistemic features, such as human beings, animáis, maybe societies or robots. But the notion used in those contexts is not quite the notion of the subject as such. My regulative definition of the notion of the subject tries to refer to the most distilled notion of the subject. This


P. Bobtuc

notion needs to be distinguished from a broader definition of subject as an object characterized by some features of epistemicity (such as perception or agency). My goal is not to abandon the other, more relevant in real life, uses of the concept of subject, but to purify the gist of the notion of the epistemic subject, so as to have clarity of what it is. This is accomplished by defining a puré epistemic subject The most reduced definition of puré epistemic subject leaves such sub­ ject with no direct predicative features. To réstate it, we can predicate about it, the way we do in the present sentence, but we cannot predicate of it, in the narrow sense of providing a direct description. By predicating about the epistemic subject, we use a meta-level of reference — the difference is, roughly, between that of a person people talk about at a party versus characterizing someone present at the party, known to us in person (speaking of him or her). Every attempt to predicate directly of the puré epistemic subject would make us miss the point of such attempted reference. This is because we would be describing some object, no doubt related to the epistemic subject, but not the subject — not the features that make it the subject. The solé grasp of puré subject is from the inside. From the outside it can be viewed, at most, as the empty space, so to say, that remains after we put all the objects to one side. Why would we attempt to move all predicative features to one side? It is primarily for the sake of clarity. Specific features of some object do not overshadow what one is looking for when searching for puré subjecthood. In algebra, it helps to move all variables to one side of the equation; also in simple chemistry and other natural Sciences, one defines the unknown substance by leaving it alone on one side of the equation. There is much confusión among people who try to grasp the epistemic subject by identifying it with a certain set of advanced features, such as memory, secondary qualities (Locke) or the feel of “what it is like” (Nagel). Those features are just intuition pumps (Dennett), quite misleading under literal interpretation. In his early works ( original and best), Thomas Nagel [Nagel, 1979; 1987] identified subjectivity as the view from nowhere. Bertrand Russell — in the early versión of his neutral monism [Russell, 1921], which seems so much better than Spionza’s pantheism, and Russell’s own later and more discussed neutralism [Russell, 1927] — juxtaposed the subjective perspective to the view focused on objects. He established a complementary framework where two descriptions, phenomenal (based on the fact that we perceive)

Subject Is No Object: Com plem entary Basis of Information


and ontological (based on the fact w hat we perceive), are both required, yet not reducible to each other. Unfortunately, attempts to cast puré subjectivity into specific ontologi­ cal categories — such as qualia — are hard to resist within Anglo-American philosophy. This was not the case in Germán philosophical tradition of the past. Fichte, in the early introductions to his Wissenshaftslehre, and Husserl, in the second chapter of his Ideas, defended puré subject with some resolve. It is not my goal here to engage in- the history of philosophy debates, or some kind of exegesis of those texts. We need the category of puré epistemicity as a way to sail between Scylla of rejecting the uniqueness and non-reductive character of first-person awareness and Charybdis of substance dualism. The latter is bad because of the problem of interaction between the material and mental substance, viewed as radically different in kind, as pointed out by Elizabeth Stuart of Bohemia (and also due to the problem with finding the mental substance apart from its physical carriers [Stuart]). The former is hard to accept as it runs counter to the basic experience of being conscious, often viewed intuitively as different from just functioning and behaving the way conscious beings do. 3.1.

Conceptual framework

Let us clarify some of the concepts used in the previous sections. The relation of the most reduced object to the most reduced subject is the basis of any possible ontology. It is also the basis of any possible epistemology. The most reduced (atomic) object is an object that can enter into only one kind of relation with another object [Boltuc, 1984a,b; 2009]. It is the object tout court, since complex objects are permutations of the atomic ones. The structure of those permutations, of such relations, allows for new features of object (ive) reality. The most reduced (atomic) subject can enter into only one kind of relation with objects: it is the relation of basic awareness. Atomic sub­ ject can be viewed as the locus of consciousness. Subject is not an object just like an object is not a subject. Any predicative knowledge about subjects is possible only through objects. Subject-subject relationship is, by ontological necessity, always a relation I-Thoughb and never an I-I.

bTechnically, it is an I-it, yet further analysis of

objects with the features of subject

allows us to introduce this Buberian category presented among the Parerga (Sec. 3.2.2).

P. Bobtuc


The locus of awareness is always the only one, and thus ontologically alone. It can be recognized by other subjects only through specificities of the object it creates — a dyadic (subject-object) relation. Thus, to put it with Continental pathos, creativity in the world of objects is the expression and bridge of existential loneliness. Subjects are not epiphenomenal, since they co-constitute the(ir) reality with the objects — we say more about this a bit later. Objects are impossible without sub­ jects [Leibniz, Fichte, Husserl] just as subjects are impossible without objects. Primary complementarity is the relation of the most reduced object to the most reduced subject. It is the basis of any possible ontology. It is also the basis of any possible epistemology. At the basic level of analysis, subject and object are always complementary. Russell’s structures of higher generality, of complementarity of the whole epistemic and ontological framework, or way or knowing, can be called secondary complementarity. We revisit and develop this point further when focusing on complementary philosophy in Sec. 4.

3.2. 3.2.1.

Parerga Not a Kantian transcendental subject

Now let us highlight the difference between the Fichte-Husserl take on puré subject and Kant’s. This can pass for a cursory explanation of why the subject we talk about is not akin to Kant’s transcendental subject, possibly more akin to his transcendental unity or apperception. For Kant, things in themselves are beyond our knowledge. We need to put pre-information about them in the categories of apperception such as time, space, causality and also relations of sense making (the source of eschatology and ethics). But mechanisms of construction of reality are, well, mechanisms. And all mechanisms belong to the side of objects, whether they are internal to the mind or external. Kant’s active transcendental subject is a thing due to being a mechanism, that of putting knowledge into the categories. This is a stinging critique of Kant’s subject as not truly a subject but a mechanism. In narrow agreement with Descartes, far short of endorsement of his metaphysics, we may say that things are mechanisms and objects. There is going to be more, on other aspects of Kant’s metaphysics, when we discuss Floridi’s ontology of information.

Subject Is No Object: Complementary Basis of Information



T h e s e c o n d -p e r s o n p e r s p e c tiv e

The second-person source of valúes is well worth mentioning as a sense that goes beyond the world of objects that appears to the subject. I-Thou is the beginning of valué. But this perspective appears at a high level of complexity, where there are two or more persons ( th e s u b je c ts at high level of generality). This point may be the main contribution of the early 20th century Continental philosophy: Buber, Levinas and, in his own way, Exupéry. Valué in the subjective perspective is always, well, subjective. Valúes in the objective perspective is always a movement of things; it is instrumental in its nature. The social grounding of valué in the realm of third-person (minimally social) interaction is dependent on the more primary categories: e it h e r

subject (I), object (it), o r the second-person relationship (I-Thou).

Only the second-person relationship can launch, if not ground, valúes to u t co u rt.


Complementary Philosophy

According to Spinoza — within an often overlooked aspect of his neutral monism — there are, in principie, infinitely many modes of presentation of the world. Yet, such multiplicity of modes is available only to the angels. Human beings have two such modes: the one starting with intuition that “I am” (Cartesian c o g it o ) , the other taking existence of the world of objects as the main intuition (Hobbes). We are all privy to either perspective, but not to both at the same time. Let me add that this is just the way it is with the famous rabbit/duck Gestalt experiment, most people are capable of seeing the world in either Gestalt, but not within both alternative Gestalts at the same time. Both manners of seeing the image are complete and internally sufficient, and there is no way to build the bridge between them. Descartes tried and failed to proceed from the perspective of what I perceive (phenomenal experience), to the veridical grounding of those perceptions in the ontological structure of the world. Yet, his idea that “clear and distinct” perceptions are certain to be veridical needed further ontological grounding in the idea of the good and caring God, which philosophically is an ad h o c move. In the phenomenological, subjective mode of presentation, the external world is always just a conjecture built upon the content of internally given phenomena. On the other hand, Hobbesian resitic materialism has a hard


P. Bottuc

time introducing the first-person subject into the world of objects. Human first-person conscious experience in Hobbesian model becomes a spurious conjecture, never able to fully satisfy the criterion of intersubjective verification. This view, which we may cali complementary philosophy, was taken up by Russell in his The Analysis of Mind [1921] and by some followers of Husserl [e.g., Ingarden]. The young Russell,c who closely followed Spinoza in building his versión of neutral monism, argued for a neutral substance that can be interpreted under the two modes of presentation — either with the subjective (Carthesian) or objective (Hobbesian) focus. Russell followed Spinoza in viewing those modes of presentation as equally valid, and thus complementary. A few years later, in his The Analysis of Matter, Russell gave obvious priority to the material mode of presentation as more consistent with ontological realism dominant in science.d It is unfortunate that discussion of modes of human perception has been often mixed up with ideological juxtaposition of the scientific world-view, mostly disputes of materialism versus religión. This is surprising since there is no cióse overlap between those views. For instance, materialism is consistent, at least in some Catholic interpretations, with the Thomistic theology (which is why Román Catholics view resurrection of the bodies after death as a religious dogma — the soul is defined as a form of the body, and this requires the actual body). But Russell’s early neutral monism avoids those irrelevancies. The view that there are two distinct, and mutually non-reducible, starting points of human enquiry, one epistemic and the other ontological, is the only way to maintain the most important insights of each view. One of those starting points is the background of epistemology, the other one of ontology — in the most basic, abstract sense of those terms. If we begin our inquiry with the epistemic view, all we have access to is phenomenal information. This approach does not have to be tied to any specific interpretation of phenomenal information: It can follow the oíd, now largely rejected, sense data theory (H. H. Price), or Gestalt theory, or some other

cSome readers of the draft of this paper thought that I relate to Russell as a materialist, since the materialistic versión of his theory ( The Analysis of Matter , 1927) is better known. But his ( The Analysis of Matter , 1927) is an even-handed versión of neutral monism that follows on Spinoza. dW e shall see that Floridi makes a very similar move.

Subject Is No Object: Com plem entary Basis of Information


versión of phenomenalism. What presents an open question in this framework is the ontological status of the correlates of phenomenal objects in the outside world. One radical view is phenomenal idealism (Berkeley-style), in which all that exists are the phenomena. But even Berkeley ventured to saying something about their external, ontological status and origin — in his case, the claim is that they come from the mind of God, with a theological story (about the lack of need in G od’s plan to be creating primary qualities) to go with it. On the other side we have representational materialist-realism. According to one of the more plausible versions of it, phenomenal data give us overwhelming inductive reasons to believe that they all origínate in the physical world, the way Science teaches. According to this cluster of views, we have barely any reasons to doubt the existence of the external, material world, yet we still face an explanatory gap (however practically benign) between the epistemic source of knowledge and the ontological conclusions drawn from such first-person source. For all practical purposes, such a view lies very cióse to Hobbesian materialism, despite its epistemic starting point. In the middle, between those two somewhat extreme positions within phenom­ enalism, we should place Humean skepticism. Roughly speaking, according to Hume we have merely inductive reasons to believe in our knowledge of the external world. Yet, those are viewed as very weak reasons; the only thing we know directly are phenomenal experiences. The ontological perspective on the world also comes in múltiple varieties, but the gist of the problem was first demonstrated in Leibniz’s mili — the idea that those “relations of bodies in motion” can never generate, or fully explain, the first-person experience, or the stream of phenomenal consciousness. Philosophers seem to have a strong tendency to stick to one of those frameworks — to the subject-based (epistemic), or object-based (ontologi­ cal) starting point. People argüe about unique advantages of their favorite perspectives over and over. The complementary framework that views both of those viewpoints as non-unique manifestations of human ways of knowing the world are rather rare, but such attempts have happened, not only in the early Modern philosophy, or one versión of Russell’s neutral monism, but also among the followers of Hegel’s model of thesis, antithesis and synthesis — from Peirce, to non-Marxist dialectics [Gonseth] as well as Marxist dialectics of subjective and objective [Ilinenkov, Ojzerman]. One just needs to go beyond one’s


P. Bottuc

favorite Gestalt and see things in motion. This would lead us directly to the section on the triads and triangles, which comes a bit later. We should view the oíd and serious debate between phenomenalism and materialism as a debate between two difFerent Gestalts, or perspectives, both actually consistent with methodology of Modern empiricism. The complementary model of explanation is similar to the old-style wavecorpuscular theory of light, according to which the equations describing the light as a wave explain some aspects of light and those describing it as a stream of small objects (corpuscles) as the other aspects. It was assumed that there is no meta-theory that guarantees retranslation of the terms of corpuscular and wave theories into a broader set of categories. Such a com­ plementary approach seems helpful at least at some stages of development of scientific theories. It also seems like the only approach capable of cash out the complementarity of (analytically basic) human modes of knowing: epistemic/first-person and ontological/third-person.


Differentia Specifica — W h y Not the Qualia

There are many functions or features that philosophers view, or used to view, as the gist of the epistemic subject. Over time, those features have been proven inadequate to serve as correlates of the most reduced, and essential notion of the self. Already, Princess Elizabeth shows the problem with mind-body interaction in Descartes’ dualism. Leibnitz accepts this point and demonstrates (in the case called the Leibniz mili) how no story about objects and mechanisms could explain out first-person consciousness. Trying to respond to of problems of this kind, Leibniz developed his monadology. He thought that only those monads that are human souls have reason, while animal and human monads both have memory, and finally plant, animal and human monads all have appetites. While reason was not the explanation of human consciousness, it was at least its dif­ ferentia specifica. Also for Kant, and most of the Enlightenment thinkers, rationality, or reason, were the powers of the human self that distinguish us from animáis and inanimate objects. Today we know, from Artificial Intelligence, that rationality (defined in any customary way) can be a feature of Computer programs and robots. Quite emphatically, rationality is no longer a good candidate for being a defining feature of the epistemic subject.

Subject Is No Object: Complementary Basis of Information



M a r y ’s one-way connection

A stronger candidate are qualia,e or secondary qualities of experience [Locke]. In the late 20th century, they were viewed through the prism of the question “what it is like” (to see, or feel, smell, hear, or taste something). The Hard Problem of Consciousness (Chalmers) has been defined as the problem of experience — as the special feel caused by such qualities. But this view seems one sided, just like the holy grail of reason and logic was for the earlier generations. It may sound like a platitude given by a reductive physicalist, but we have robots fully equipped with “the sensory apparatus” and able to “perceive” neural markers that human beings view as qualities of perception. Also, animáis can now be equipped with artificial senses. So, having the functionality of perceiving what we view as qualia is not even cióse to the gist of the problem of first-person epistemicity. This point can be made clearer within the framework of the case of the Black and White Mary — the so-called knowledge argument [Jackson]. Imagine that there is a person who has never seen any colors due to the fact that she was kept in the black and white environment (details are unnecessary, so we may assume special lighting conditions). She became a scientist and an expert on colors; yet, she has never seen any. One day she gets out of her black and white environment. Would she learn anything when seeing her first red tomato? Most people think that she would say “Oh, that’s what red tomatoes look like” ; thus, she seems to have a qualitatively new experience. Jackson’s original intention was to show that qualia bring about some knowledge, henee the case is called the knowledge argument I used to agree with the Nermiroff and Lewis line of critique of this case as their ability response was: Mary does not gain new knowledge but she gains a new ability, kind of like the ability to ride a bieyele [Lewis, 1890; Nemirow, 1990; Boltuc, 1998]. Today, we know, from AI, that abilities can also be cashed out as knowl­ edge (even if such knowledge is tacit in some verbal contexts). It requires information to program functional abilities into a robot, just like it is to program verbal and intellectual subroutines. This helps us look back at human

eW hen one talks about qualia, some philosophers think that this is about emergentism. I am not talking about the origin of qualia here. The point is to disperse the mist of qualia that hazed non-reductive subject.


P. Bottuc

abilities as non-verbal knowledge, gained from learning but not necessarily from instructions transmitted in propositional language. A broader point is this: The case assumes that all “knowledge” can be cast in a (human-readable) propositional language — something one can read in a book. However, propositional language is actually a somewhat crude measure. Even Turing computing is a crude measure (e.g. neural networks or Gestalt computing has no problems with incomputable functions, such as Pi, and better conveys some information than discrete comput­ ing of the Turing machines). Some knowledge is best transmitted by psychomotoric conditioning or, as in the case at hand, by acquaintance not by propositional communication [Boltuc, 2018a]. But this is not where the story ends. Im agine a B IC A M a ry — Mary viewed as a biologically inspired cognitive architecture.f If we think of the Black and White Mary in terms of a unified theory of cognitive architectures, we have the following re-description (or a new versión) of the case: 1. Mary has a one-way link between knowledge by description and phenomenal qualia; it goes from qualia to description, but not the other way. 2. She is missing the path from description to qualia; so, when she is fed descriptions she has no qualia associated with them. 3. Only when she is “initialized” by acquaintance with some qualia (they are projected to her sensory apparatus) would she be able to create the link from description to the actual feelings How do we fix the problem? Well, not to worry! We can engineer the link from description to qualia as a part of the initial set-up of Mary-thecognitive-architecture. We could also, presumably, bioengineer such a link from language centers back to the visual cortex in a human Mary. Why do human beings lack such link? Evolutionarily, color recognition is an order of magnitude older than propositional language. More importantly, does BICA-Mary tell us anything about nonreductive consciousness? No, it is not relevant to that topic. The case turns out to be about the lack of the original neural link that goes from descrip­ tion to the feel of experience. It would be peculiar if one was to claim that

f I want to thank Frank Jackson and David Chalmers for encouragement when working on this case at A N U in 2014.

Subject Is No Object: Com plem entary Basis of Information


an artificial cognitive architecture (with the same cognitive architecture as Mary) BICA Mary — would have first-person consciousness just because it would need to acquire it by acquaintance. By cióse analogy, the nonsensical flavor applies to the instance of Mary-the-human. The kind of first-personal experience needed for BICA Mary is just the link from description to qualia, and not non-reductive consciousness that Jackson used to be interested to defend [for further details, see Boltuc, 2014]. 5.2.

Gallant-readable brains

The only thing that distinguishes robot perception from human perception is presumably the epistemic viewpoint, the feel of what it is like, that humans (and animáis) are expected to have and robots to lack. If so, isn’t the brush with which the problem has been sketched in qualia theories overly broad? Isn’t it better to speak of the first-person feel, or just first-person epistemic perspective, and leave qualities of experience aside? They belong to the world of objects; namely, they are the objects of experience. They are not exclusive to the epistemic, non-reductive side of the equation. This is, incidentally, where we can see that the empiricist Locke (as well as Hume and their followers) is missing the point visible to Kant, and especially his followers (Fichte, some neo-Kantians and Husserl): The point is that perceptions are objects, while non-reductive subjects need to be discovered beyond them. Perceptions or phenomena are objects in our head. The privileged access argument, pertaining to such objects, is based on an empirical difficulty of inspecting another person’s thoughts in the interpersonal framework — they seem safely locked in one’s private head. The problem existed back then, when neuroscience didn’t exist, or in mid-20th century, when it was just fledgling, but does not seem to be a major obstacle today. The point can be made clearer when we consider Jack Gallant’s experiment that reads dynamic images from one’s visual cortex and puts them back on screen.g As the first step of future research, let us focus on Jack Gallant’s team that can read the content of what one sees — even as a dynamic movie of one’s visual perceptions — from fMRI of one’s visual cor­ tex. They can put the movie of what one sees on screen just reading a visual cortex. New versions of the project provide more and more crisp readings

SI want to thank Ben Goertzel for sharing this case in his lecture at B IC A 2014 at M IT , and for a number of related conversations in Shanghai.


P. Bottuc

of phenomenal qualities. This and other similar experiments demónstrate that the content of one’s mind is no longer entirely private. Other teams of scientists are able to reconstruct what one is thinking about, though this is quite a bit more difficult. We have scientifically based reasons to believe that one would be able to also read images that a person generates in their mind, not just those they view, as well as their other thoughts. In particular, one would be able to read the subject’s qualia (say one’s subjective feeling of temperature or pain) and put them in the objective context, by comparing them with the qualia of other subjects. Just like we can compare the picture on different TV sets, at a store — in terms of tilt, sharpness, and various hues — we should be able to compare the objective features in the equipment that is the animal or human brain. Thus, we would be able to know, quite exactly, what a given person sees or feels or tastes. Chalmers and many others maintain that the Hard Problem of Consciousness is the problem of the exact feel of qualia. However, this seems like a difficult but surmountable versión of the easy problem of consciousness. The point what exactly another person feels can be learned in an interpersonally verifiable way — e.g. in Gallant’s experiment, by putting the images from one’s brain onscreen. The confusión comes from philosophers trying to hold on to the remnants of the problem of privileged access, which is not so privileged anymore. The puré subject is beyond this sort of discussion. The fact that somebody can read our visual cortex bears no direct relevance to the question of the epistemic subject, though it does have direct relevance to the problem of perception. This gives us one more opportunity to say, contra Chalmers, that the problem of first-person experience, and its uniqueness, is no longer the problem of perception. It cannot be that, since it would fall within the easy problem of consciousness. The hard problem is different. It is the problem of epistemicity that is hidden behind the problem of qualia. 6.

Epiphenomenalism á rebours

We say that there is parity between the standard charges of epiphenome­ nalism, raised by materialists against non-reductive views, and the charges that consistent phenomenalists could bring against the materialist view. To maintain the existence of the external world is a speculative metaphysical assumption if considered within first-person epiphenomenalism. We shall cali the latter argument “epiphenomenalism á rebours” . Berkeley went in this direction, but left the field of philosophy and

Subject Is No Object: Com plem entary Basis of Information


got stuck in controversial theology. But Leibnitz’ in his monadology has done a better job — he provides a more persuasive model of a similar approach. There are several definitions of epiphenomenalism: One way to define it is as a position that mental States are caused by physical States; yet, they do not cause anything. The main point of focus in my discussion is the conclusión often drawn from epiphenomenalism that epiphenomenal qualia are irrelevant. I try to show that mental States can be relevant to oneself (in fact, they are the gist of oneself). Such epistemicity — as the argument of this article goes — is required for any ontology. At a less abstract level, it is relevant for me, whether I am first-person conscious or not — and most people seem to feel this way about their respective feel of consciousness. Finally, we seem to have good reasons, moral at least, to care about firstperson consciousness of our significant others! — a point that is going to be argued for in some detail. The standard charges of epiphenomenalism directed towards nonreductive physicalism are unbeatable in their own terms (already Leibniz’s mili can be interpreted in this way). Yet, in the case of Church-Turing Lovers [Boltuc, 2011; 2017], to be presented below, we shift the argument to the second-person perspective. This change of the framework seems to be helping repel the charges of epiphenomenalism for first-person conscious­ ness. Actually, a similar second-person shift should be effective against the charges of epiphenomenalism á rebours, which we shall propose as a sort of paradoxical charge against materialists. The existence of other people (the second-person relationship) seems harder to reject than the existence of the external world. To this we now proceed.


Materialism as epiphenomenalism?

The old-school sense-data theory has been dismissed in favor of Gestalt psychology, but it is sometimes overlooked that the latter is also a form of phenomenalism. Within any of the first-person approaches, there is no direct way outside of phenomenalism; the best ways are inductive conjectures. Hume demonstrated beyond reasonable doubt that they would never guide us all the way to the object itself, and on this point Kant agrees. A simple way to illustrate this point is the case of Sylvia Plath’s tulips: In her famous poem Tulips, American Poet Sylvia Plath describes, with some surprise, the tulips that appeared in her white hospital room when


P. Bottuc

she was recovering. From the purely phenomenal description, we could infer that they could be holograms, they could be products of her overmedicated mind, they may be Raphael-type paintings on the wall, they may be dreams; for all we know they could be fata morgana. She can believe that there is a good chance that her geekish friend brought in a hologram (those were starting already in the 1960s), but there is a better chance that they are real physical objects, and an even better chance that she hallucinates. Sometimes phenomenal experience does not bring about the one obvious ontological interpretation but several strong alternatives. And let us remember Hume’s lesson that phenomenalism is the background of the true empiricism! We are all in Plath’s position, to various degrees. There is no way to get outside of the bubble of one’s senses — not from the first-person perspective. For instance, within Leibnizian narrative one stays inside their epistemic monad, merely able to just inspect its inside walls. Does the idea whether there exists an outside world matter? If it is irrelevant in the world of phenomena and not attainable (for the reasons common to phenomenalism of Leibniz, Hume and, against his wishes, even Kant), then the claim that material objects exist attains many features of epiphenomenalism. The existence claim becomes as inconsequential in the world of phenomenal experiences as consciousness within deterministic physicalism. Let us move through this last point more slowly: As long as one has a consistent Berkeley-style view that perceptions are the only mode of existence, the view that the outside objects exist fails to bring any practical implications for her daily life. This is the case for as long as we treats those “perceptions” seriously so as to not jump under a running car (which is consistent with Berkeley’s guidelines — perceptions are the whole reality; henee, they are the reality after all). From this radi­ cal phenomenalist viewpoint, belief in the external ontology, e.g. in matter, is irrelevant. Henee, ontology of the external world is epiphenomenal for first-person phenomenalism. The view that there are just epiphenomena is epistemologically sufficient, and therefore, from the purely epistemic view­ point, sufficient overall. While Berkeley’s religious narrative explaining this fact is unpersuasive (the standard objection: God would not deceive us into believing in the external world), a Leibnizian versión, that we are inside our minds (the conscious monads) and see their internal walls, seems fine. In some way, this is what the human perception is about — and Helen Keller’s

Subject Is No Object: Com plem entary Basis of Information


experience, when she learned about the world just by touching a plástic ball, makes this point stunningly obvious. 6.1.1.

The standard charges of epiphenomenalism

The standard charges of epiphenomenalism are launched by materialists against those who argüe in favor of non-reductive consciousness. If the world is fully deterministic, then functional processes happen in the same manner whether people have the first-person feeling of consciousness or not. Without first-person experiences they would be the so-called philosophical zombies, able to function in the external world exactly the way conscious beings do,h but lacking the subjective first-person feel. Henee, the firstperson consciousness is epiphenomenal, which amounts to saying that it doesn’t change anything in the external world. There are several ways to question the charges of epiphenomenalism, but I know of just two ways to defend the first-person consciousness. The clearest one proceeds by referring to the second-person perspective — it is the Church-Turing Lovers argument [Boltuc, 2017]. The second-person argument, to be presented below, seems valid, despite its narrow scope. Perhaps the second-person perspective is the only philosophical bridge between the first- and third-person approaches. The Church-Turing Lovers are defined as one’s ideal lovers, except that they are lacking first-person consciousness. I prefer not to use the term Zombie-lovers due to the connotation that implies their potential for nefarious or spooky actions. Church-Turing Lovers behave exactly as the kindest person you would think of, and the behavior is consistent. Their only difference from particularly good human lovers (by whatever standards) is that they lack the first-person feel. They are functionally conscious, they behave lovingly, and they understand what you are saying, insofar as learning and generating completely proper conversations (they meet the Turing Test for robots); also their body language, even touch, is exactly the way the human’s would be. Their may have various kinds: They may be biological human beings, just with no first-person feel, or bioengineered beings, or they may be perfectly engineered robots. So, what is the problem with such perfect lovers? Aren’t we supposed to care about what our partner feels for him- or herself? There is a difference

hActually, within this framework Zombies are impossible since we are all Zombies (thus, there is no contrasting reference frame).


P. Bottuc

between being happy and just behaving happy; the latter is one way of just faking it. Only the lovers who do not care about their significant others have no interest in knowing whether the loved one feels love or is just faking it while feeling nothing. This seems like a relevant difference between the two functionally identical beings: the one with and the one without consciousness. The difference seems visible, and relevant, solely from the second-person perspective. As long as one cares about the significant other for him- or herself, not just for his or her functionalities, the difference between a lover tout court and a Church-Turing Lover is relevant. Yet, it consists solely in the former having first-person epiphenomenal consciousness. Thus, we show that functionally epiphenomenal consciousness can be relevant. 6.1.2.

Epiphenomenalism and intersubjective verification

The issue of epiphenomenalism should not be confused with the problem of interpersonal verifiability of one’s first-person consciousness — the problem of how we would know whether an entity is first-person conscious. The latter issue may require very intricate research to establish weak inductive reasons (based on testimonies, self-observation of researches and neural cor relates of consciousness using inference to the best explanation). Yet, Science may discover a rather simple, and inductively strong, way to identify first-person conscious versus functionally conscious brains. One such attempt has been presented by Darmos and Krundel recently: Within old-school interpretations of quantum physics, it was assumed that the outcomes of double-slit experiments depend on whether they are observed by conscious beings. If this was reliably the case (and if the notion of “conscious beings” used was the notion of beings with non-reductive con­ sciousness) , it is easy to see how those experiments could lead to detection of conscious observers. If a philosophical zombie observed such an experiment, it would not behave as if it had taken place in the presence of a con­ sciousness. On the other hand, if a conscious robot (or an animal) observed such experiment, we would be likely to gain the results characteristic of the experiments observed by a conscious being. Interpretaron of double-slit experiments as dependent of consciousness has been largely abandoned in the 20th century (though a few physicists seem to cling to this interpretation). At the very least, this idea may serve as an opening of the conceptual possibility how future Science could perhaps provide experimental solution to the empirical versión of the problem of other minds.

Subject Is No Object: Com plem entary Basis of Information



Epiphenomenalism á rebours revisited

Let us sum up the epiphenomenalism á rebours argument since it may be new and crazy sounding. It presents the charges of epiphenomenalism against materialists that could be raised by someone like Leibniz. Imagine that you are an epistemic monad. Then the existence of other objects would be impossible to prove since one could not get in direct contact with any of them. We can explain everything there is to be explained by the phenomena. Henee, the external world plays no causal role and is epiphenomenal to the story based entirely and exclusively on phenomena. (To be consistent, Berkeley should have said that God is one among the phenomena. The original answer puts God outside of the universe of phenomena and thereby gives priority to the external world, however reduced). Here is a weakness of such argument: direct relations with other peopie would also be impossible, even within monadology, since they appear to us as objects in the universe (their epistemic selves speaking to us always indirectly, through some objects — even so intimate as the vocal cords of their bodies). The second-person relationships would require spiritto-spirit direct links, which would still establish primacy of those spirits over the world of phenomena. This link does require a broader ontology than the subjective and objective viewpoints. The argument based on the second-person shift (used against the charges of epiphenomenalism, that are mounted against non-reductive consciousness) would also be effective against epiphenomenalism á rebours. This supports the argument at hand, since it reveáis a structural analogy between the two forms of epiphenom­ enalism (the standard one, and the one á rebours). It seems that existence of other people (and the possibility of secondperson relationship with them) would be harder to reject for an idealist like Berkeley or Leibniz, than the existence of the external world. Henee, the charges of epiphenomenalism both towards non-reductive materialists and non-solipsistic phenomenalists can best be repelled by recourse to the second-person relationships.



The subject-object relationship can create a broader ontology, and epistemology, solely if it is put in a further relation — namely relation to the third element. Such an element constitutes the minimal reference frame.



P. Boltuc

Triangles in Plato’s later dialectics

This triadic structure is known from Plato’s response to Aristotle’s main objection to the theory of ideas: the so-called Third-Man Paradox. Aristotle shows that if we have an idea (say, of a horse) and a physical horse as its instantiation, we need a third element (a meta-idea of the horse and the physical horse together) to establish the relation of similarity between the idea and the thing that instantiates it. Yet, this is not the end of the story: The same question can be posed about the relation of this new idea and the collective set incorporating the idea of the horse and the horse. We need a higher level idea to establish the relation of the first-level meta idea and such a pair, and so on ad infinitum. Following the traditional Germán interpreters, as well as John Findlay, I say that Plato bites the bullet and endorses this intended reductio ad absurdum argument as constitutive aspect of his later metaphysics, especially in the dialogue Parmenides [Boltuc, 1984a,b]. This is the gist of Plato’s fully formed dialectics, which became the basis of Hegel’s method leadings from thesis, though anti-thesis (and their fierce rivalry) to the synthesis — the latter always already figuring out as the thesis at the dialectical triangle at the next level. Peirce’s triads of meaning, which are also his ontology, are a subtle theory of meaning based largely on a similar Ínterpretation of Plato’s dialectics. The process of interpretation, as creation of meaning — henee, information — is an ontological process. 7.2.

Subject-object interaction

The above model has been generalized in Burgin’s approach to named sets, which are viewed as structural models of communication and information. According to Burgin, within “information exchange between systems, we employ the most fundamental structure in mathematics, nature and cognition, which is called a named set or a fundamental triad” [Burgin, 2017]. This approach relies directly on the legacy of Plato’s triangles, analyzed clearly in East European publications [Burgin, 2018; Boltuc, 1984a,b]. In their recent article, Burgin and Zhong [2018] intégrate Burgin’s named sets theory with Zhong’s information ecology. The authors make a very good use of the important phrases by Lao Tse: The Way produces one: one begets two; two begets three; and the three brings about the whole world.

Subject Is No Object: Com plem entary Basis of Information


The authors continué: “In a more general context, the structure ‘subjectobject-interaction’ is an important kind of bidirectional fundamental triad, which is also called a bidirectional named set.” In the most general sense, Lao Tse’s verses grasp the core of the idea how most reduced notions of puré subject and object enter into the most basic primary relation that brings them both from potentiality to actuality. This first step is described by the most reduced versión of Burgin’s triad subject-object interaction. We need to be clear that such basic interaction between a primary subject and a pri­ mary object puts a merely potential subject and a merely potential object in the realm of existence — since existence tout court requires interaction between the two. This helps us avoid the subject-object gap generated in Modern European philosophy. Subject and object are the universal triad as applied to the basis of ontology and epistemology. Higher level objects exist only as related to the perceiving subject — as Leibniz shows, the talk of possible worlds that are epistemically unavailable is empty, so there is no such ontology. On the other hand, epistemology must have some content, some kind of objects it pertains to, even if the status and context of those objects is very unspecified, they are always already information. Then the third ontological element emerges, the reference frame (which is not the relation but another object). Burgin’s interaction that creates the triad does not seem to be that of a reference frame; instead, the interaction is seen in the active verb “begets” . This is because the object is impossible without the subject, and subject without object — by entering in the triadic relation of existence both subject and object beget each other, i.e. they start to exist. Then there needs to be the reference frame, as is clear to us from modern physics. This is the framework that the genius Lao Tse sees as the way towards the ontological possibility of the whole world. The article by Burgin and Zhong helps us differentiate clearly between the level of fundamental triads as “the most critical structure in nature” [op. cit., p. 8] and the level of the whole system. Further, I am proposing a further distinction — between two important levels of generality within the former framework. Those are: (1) the level of minimal ontology at which the basic subject-object interaction pertains to the most conceptually reduced entities (those entities are purely potential before entering in the relation); (2) the fundamental triad (subject-object information) at the level of cognitive entities, in particular human beings. At the latter level, subject is an intelligent system in possession of knowledge and goals [op. cit., p. 7]. It seems that Burgin’s triads are situated most clearly at the level of person, but we can move to more basic ontology since in Burgin’s work those


P. Bobinó

triads sometimes function at the level that I cali primary subject-object relationship. My article may be read in the context of this typology. The process of triadic constitution of reality is not only the basis of ontology but it is also epistemic since the requirement of basic epistemicity applies to any possible ontology. This point, visible from the previous arguments, is the methodological background of my discussion of Floridi’s ontology of information, which comes in the next section. In the following section, we explore a follow-up on the epistemicmetaphysical structure (in its best known Kantian versión) erected by Floridi within his ontology of information. In the section that comes after it, we sketch out a proposal by Ben Goertzel that may be viewed, by a philosopher, as a follow-up on Leibniz’s non-anthropomorphic general epistemology. Those are the important theoretical applications of the above theory.


Ontology of Information as an Existential Challenge

We join the camp of those authors who are friendly to Floridi’s informational realism but emphasize the need for stronger accentuation of the epis­ temic aspect of information. Information is always epistemically situated and — if we follow Leibniz — so is ontology. First, we focus on Luciano Floridi’s ontology (and epistemology) of information; then we extend this analysis to the ethics of information. We agree with Beni, in ontology, and Barker, in ethics, that Floridi’s relationism would benefit from enhanced grounding in epistemicity.


Beni on Floridi’s ontology o f information

Floridi’s informational ontology views the ultimate nature of reality as structural, so that ontological reality is the totality of structures dynamically interacting with each other. Floridi’s ontology of structural objects can be cast in terms of informational objects, which leads to his informa­ tional structural realism (ISR). Henee, ontology of the world is the total­ ity of informational objects dynamically interacting with each other. From among múltiple works by Floridi and about his work [Dodig Crnkovic, G.; Hofkirchner. W], I reconstruct this ontology largely following a well-written article by Beni (from whose interpretation I diverge in many comments). The later part of this section is based on my speech in honor of Luciano

Subject Is No Object: Complementary Basis of Information


Floridi at the ceremony of awarding him Doctórate Honoeis Causa of the University of Suceava (2011). Floridi views information as the “concept as fundamental and important as being, knowledge, life, intelligence, meaning, or good and evil — all pivotal concepts with which it is interdependent — and so equally worthy of autonomous investigaron” [Floridi, 2002]. Yet, I would argüe that those concepts do not seem fundamental, except in the metaphorical sense of the sort used by Continental philosophy. Floridi argües that information is “a more impoverished concept, in terms of which the others can be expressed and interrelated, when not defined” [Floridi, 2002]. This is an important point, though the word impoverished used by Floridi seems unfortunate — more reduced or less loaded with specific content would sound like better terms to express Floridi’s idea. His point is that information is a more generic (and thereby more general) concept, into which one could retranslate all other general concepts. The real question for us is whether infor­ mation is indeed such most general concept, and if so, in what sense of the word “information” . Moving to Floridi’s epistemology, he views knowledge of the world as knowledge of those dynamic ontological structures. Importantly, Beni noticed that Floridi’s ontological structural realism (OSR) is noneliminativist since, “eliminativist OSR betrays the original Kantian polarization between knowable phenomena and unknowable noumena, which lies at the roots of SR” [Floridi, 2008, p. 223]. At the same time, “ISR is committed to the existence of mind-independent structural properties and structural objects which constrain our knowledge [Floridi, 2008, p. 240].” But, as Beni noticed, Floridi distanced himself “from the mimetic view on knowledge and endeavored to replace it with a constructionist theory which holds that epistemic agents know something when they are able to build and model something and plug the obtained model into the correct network of informational relations that account for it [Floridi, 2011]” . In this vein, Floridi has sought to deprioritize “knowledge that” in favor of “knowledge how” . We can recall that my analysis of Jackson’s knowledge argument was going in the same direction. For Floridi knowledge “is not about getting the message from the world; it is first and foremost about negotiating the right sort of communication with it” [Floridi, 2011, p. 284]. (Beni, p. 335) Floridi’s constructivist information relies on relationality, so it is neither absolute ñor relative. Beni focuses on Floridi’s pragmatic approach, according to which information has to be defined as user-dependent [Floridi, 2011]. As Beni point s out, such “constructionist not ion of information underwrites


P. Bobtuc

Floridi’s theory of knowledge as well as his realism” . (Beni, p. 336) Henee, Beni argües that “departing from its constructionist origin and moving towards the ontic thesis costs the ISR its integrity” . Furthermore, “by construing the ISR as a branch of the ESR, the haunting objections could be easily avoided.” (Beni, p. 338) However, Beni does not sketch out such theory in suíhcient detail. Here is an important point where my account diverges in a major way from Beni’s: While Floridi follows Putnam’s argument for realism, he seems to miss the fact that the “no-miracles” argument is a backward-looking argument that tries to strike down post-religious spiritualism of some sort. On the whole, this kind of realism is no longer in need for defending; it is even defended by some of the religious philosophers [Jaki]. Yet, pragmatic as well as epistemic components of reality have nothing to do with motivation or structure of Putnam’s argument for realism. The main conversation is much further along, thanks to the onset of artificial cognitive architectures — and Floridi is one of the top persons to be credited for taking this onset seriously. Reality is mind-independent, the way Putnam conceived of it, within the oíd game; but it is not so clear that it is independent within the Liebnizian relationship of ontology requiring the subject of knowledge, or even Goertzel’s view on general intelligence.1 It is particularly hard to fit it with Kantianism, which is, in its very essence, an objective idealism. This can be seen as the view according to which existence of the world may be observer-independent but the form of it is observer-dependent — yet, the observer-independent aspect is amorphous enough to grant only a very min­ imal notion of its existenceJ The reason this is important is that Floridi, while using the Kantian theory of reality (to say it again, a versión of objec­ tive idealism), uses the notion of information that many Kantian scholars would deem non-critical, though, as Beni underlines, he does it in a subtle manner. Floridi emboldened the Kantian model of reality with the concept of dedomena, which allow for things in themselves to influence the world of epiphenomena. This is what I would consider one of the most meaningful additions in recent post-Kantian scholarship, though it brings Kantianism closer to materialist-realism. Information and structure are meant to be

irThis point will be explained in the final section. jFloridi’s dedomena are meant to take care of the nebulous character of things in themselves.

Subject Is No Object: Com plem entary Basis of Information


objective in the vein of Kant’s mathematics, but they are more like categories of apperception — specificity always comes with the observer and not so much with the object. Floridi tries to add the missing link to make things in themselves empirically relevant, while never quite phenomenally available. While Kant was an idealist, Floridi is building a sort of Kantian realism on the ruins of the original Kant’s theory. As Beni put it: “Floridi emphasized the distinction between the inaccessibility of the source of knowledge and its inexhaustibility. The distinction indicates that the Kantian component of Floridi’s theory is not completely conforming to Kant’s own views on the inaccessibility of noumena. There are several con­ textual pieces of evidence for this claim. For example, in elaborating on the Kantian thesis Floridi remarked that “the method of levels of abstraction allows one to understand that reality in itself, though not epistemically inaccessible, remains an epistemically inexhaustible resource out of which knowledge is constructed.” [Floridi, 2011, p. 331] In a more conspicuous departure from the orthodox construal of Kant, Floridi stated that the relational entities, as the sources of our knowledge, “are unknowable not because they are somehow mysteriously unreachable, but because their epistemic malleability is inexhaustible” (ibid, p. 356). These indicate that Floridi tailored his con­ strual of Kant to his own view about the informational richness of the world ( . . . ) This attitude eventually resulted in an interesting invitation for rethinking the philosophy as a dynamical process of outsourcing and insourcing of the problems and Solutions, through which the “semanticisation of Being is pursued and kept open.” [Floridi, 2013, p. 218] (Beni, p. 329)

Beni concludes that the strongest form of structural realism that Floridi’s argument could ground, is epistemic. On the other hand, the Ontic SR — which is centered on the elements of the memetic view — couldn’t be incorporated into Floridi’s informational structuralism, without undermining the constructionist foundations of his theory. Again, I quote Beni in extenso since I happen to agree with his point, including the sympathy towards ontological relationism: “Floridi’s ontological step indicates that ‘there are ontologies — in particular those supported by ontic structural realism and by informational structural realism — that treat the ultimate nature of reality as relational.’ ” Beni continúes: This conclusión is somewhat debatable. Although the relational ontologies appeal to me, my reservation is that Floridi’s informational approach doesn’t allow for such ontologies to be developed in accordance with the metaphysical assumptions of the Ontic” (Beni, p. 330). Beni follows up by arguing that Floridi “doesn’t establish the validity of the inference from the


P. Bobtuc

modal (and weaker) claim that reality-in-itself could be neither digital ñor analogue to the stronger assertion about the non-digital and informational nature of the reality.” (Beni, p. 131) In what I view as a very helpful move, Floridi dismisses the digital versus analogue distinction as similar to the wave-corpuscular dichotomy in physics and argües that informational ontology helps bridge the former dichotomy. According to Beni, it is not OSR but “ESR that holds that all that we can know about the world is its structure. ESR also holds that we must remain agnostic about the nature of things over and above, or ‘behind’ that structure.” Henee, epistemic SR not ontological SR is a good fit with Floridi’s broader theory.


Ethical implications

Floridi’s ethics of information is part and parcel of his ontology of Informa­ tion. This is because his axiology is fully vested in the ontological structure. The need for more epistemicity is even more visible in Floridi’s ethics, or rather general axiology, of information. The theory views the axiological goal, the basis of the moral vector (goodness), as creation and preservation of information. Floridi argües that this does not run counter to the second law of thermodynamics. We have no need to scrutinize this last claim at this place, though Fultot’s analysis (sketched out below) addresses it at a higher level of generality. Instead, we shall focus on the ethical controversies that follow from this issue. I find less-known objections to Floridi’s ethics of information, by Barker and Fultot, particularly relevant for the very ontology of information.


Barker: the too much information argument

John Barker characterizes the gist of Floridi’s information ethics in the following way: “Information Ethics holds that all beings, even inanimate beings, have intrinsic moral worth, and that existence is a more fundamental moral valué than more traditional valúes such as happiness and life. Correspondingly, the most fundamental moral evil in the world, on this account, is entropy — this is not the entropy o f thermodynamics, but entropy understood as “any kind of destruction, corruption, pollution, and depletion of informational objeets.” [Floridi, 2007, p. 9]

Subject Is No Object: Complementary Basis of Information


Here is where ontology comes in: “Floridi identifies existence as the fundamental positive moral valué, and inexistence as the fundamental negative valué.” (Barker) And the punchline of Barker’s argument is: “The trouble with this proposal is that given the broad conception of objects that we are working with, every act both creates and destroys objects. Since objects are simply instantiated patterns, there are indefinitely many objects present in any given physical substrate.”

Having discussed Shannon’s information, and demonstrated that it depends on the context that cannot be set as universal (at least, outside of physical entropy), Barker argües “the whole notion of complexity or information content becomes trivial unless it is tied to our interests (or someone’s interests) as producers and consumers of information.” Then, Barker presents a Searle-style example of the glass of water that can be encoded as representing the informational content of the Library of Congress. We may dismiss such encoding as uninteresting, but this re-opens the can of warms “If moral worth is tied to interesting information, then it appears that moral worth is directly tied to human concerns after all.” Barker concludes that “there is a problem with viewing information’s intrinsic valué as something independent of our own interests as producers and consumers of information. The problem is that information does not exist independently of our (or someone’s) interests as producers and con­ sumers of information” (Barker, p. 14) — alternatively, information exists in an unlimited number of ways, thus being intr act able. 8.2.2.

Fultot: information as an efficient way towards entropy

According to Flament Fultot, in Floridi’s theory, “when it comes to defining what the valué of Being is, his informational-ontological interpretation is based on order, organization, and structure.” However, “the kind of entities that are of importance to us for our judgments and interventions as agents are ordered and thus valuable because they exist far from equilibrium.” (Fultot, 4) The author focuses on Rayleigh-Bénard experiment in which one fries viscous fluid (such as a shallow layer of oil) in a frying pan. Nothing interesting happens as long as temperature is relatively low, but “when the magnitude of the potential exceeds a given threshold, a new regular pattern of organization emerges from the interaction between the partióles in the fluid.” Namely, “in a circular recipient, the patterns are constituted by hexagonal convection cells visible to the naked eye. Each cell consists of hundreds of millions of molecules moving in a coordinate fashion” . So, the


P. Bottuc

oil is dynamically ordered in a manner that is most conducive to sending the energy away from the frying pan, which amounts to producing entropy. Based on such simple physics, Fultot seems to be successful in demonstrating that “far-from-equilibrium systems attain ever increasing degrees of order at the cost of faster entropy production. Yet, inversely, by promoting an increase in entropy production, more complex and ordered forms emerge on Earth. Entropy production and order are thus complementary; they imply each other reciprocally.” This leads to a paradox: “By promoting Evil in Floridi’s sense, Good happens lawfully because order is nature’s favorite way of producing entropy. In short, moving against entropy only creates more entropy.” (ibid.) This moves the argument from Barker’s objection about the lack of interpretation of what counts of information, for as long as there is no privileged set of agents and their interests, to an empirical claim that, as more structure gets created it paradoxically becomes a means towards more efficient creation of entropy.


Existential interpretation

Floridi’s project in ethics may be viewed as hard to formúlate outside of human pragmatics (Barker). It may even lead to the paradoxical (at least for Floridi’s ethics) conclusión that order should be defined as efficiencies in producing entropy (this seems to follow from the argument by Fultot). Infor­ mation can be viewed as measure of entropy, but for Floridi it is a measure of order — its paradigmatic examples are complex crystals (stalagmites) and living organisms. But what if what we view as order is what amounts to a measure of efficiency in transforming producing entropy? Metaphysically, and with some level of extrapolation from the previous argument, what if the solé perfect realization of order is non-existence? Thus, Floridi’s project may also be viewed as an existential challenge. Ontology based on information is an attempt to find a non-anthropomorphic ápxn (arché), the principie of existence, the way preSocratics thought of it. Ethics based on information is an attempt to ground axiology upon ontology, the way similar to Plato’s. An attempt to build the concept of information based on the unconscious links between our phenomenal world and the things in themselves provides the missing piece in Kant’s theory of things in themselves. So, Floridi seems right in that if things in themselves guide our epistemic reality in any way — which is the

Subject Is No Object: Com plem entary Basis of Information


only manner to make them relevant — then there must be a specific way in which phenomenal reality is dependent on things in themselves. Yet, all those attractive theories, if taken jointly, fail. Kant teaches us that ápxq is not attainable since the world is built upon the forms of apperception that we bring into the world: What we see in the mirror of the world is our own face. Plato’s failure, so clearly seen in the collapse of all kinds of axiological absolutism (including its political implementation, which manifested itself already in Plato’s arrest and fall into slavery in Syracuse), demonstrates the perils of the ethics grounded in metaphysics. Then, what is left? Camus is left, with his analysis of the Sisyphus. The challenge is in pushing our stone up the hill and watching it fall, again and again — such a simplistic versión of Sein zum Tode. But being towards death is different than being in a precarious, yet precious, balance. To revisit the myth of Dedalus: Sometimes Icarus of our spirit is flying too high, too cióse to the sunshine (the way Plato and the idealists of all times do). Less existentially and ethically challenging conclusions come with less ambitious attempts, those that keep us in the middle between the extremes, the way Dedalus (or Aristotle) recommends. In this frame of reference, Floridi’s project formulated within human pragmatics, both for epistemology and ethics, seems doable and attractive. The structuralist theory of information provides a broad ontological framework, within the human epistemic sphere. The ethics emerges, that is based on creating structural complexity, development, and respecting the masterpieces of nature and human genius available to us, as a noble way to go through life. It is a way to remain within human rfOos (ethos), which, by Heideggerian interpretaron of its archaic meanings may be read as the space where a living being dwells. Floridi does not seem resigned to remain in this sphere. Yet, Leibniz seems right that we are unable to predicate about the possible world we have no epistemic contact with — if so, shouldn’t we try anyway? Not every attempt to go beyond human existential conditions is deemed to failure (only those most impressively ambitious). Information seems always already for somebody, somewhere, in some cognitive reference frame. Religious thinkers apply this notion to divine beings. Science-fiction writers extend it to extraterrestriáis. But today, the most up to date chal­ lenge seems to be coming from cognitive architectures, some of which belong to educationally (or medically) enhanced human beings and other animáis while others come from AI. We cióse with the section pertaining to this topic.



P. Bottuc

Cognitive Synergy

Cognitive synergy is a dynamic in which múltiple cognitive processes, cooperating to control the same cognitive system, assist each other in overcoming bottlenecks encountered during their internal processing [Goertzel]. It is the key feature of general intelligence, artificial or biological, — if the difference makes much of a difference. Within general intelligence, the question of subjective and objective, and even epistemic and ontological, gains resolution in a more general cognitive framework. Ontology, informational or otherwise, becomes a sub-category within general intelligence [Burgin]. We come back to the Kantian model, that Floridi and many structuralists before him took as their starting point. Yet, this is Kant at a different level of interpretation; the one applicable to robotics and to intelligence in general. There seem to be a continuum between biological and biologically inspired intelligence, going all the way to the non-humanoid intelligence, or even consciousness. Ricardo Sanz argües that we should avoid excessive anthropocentrism in formal work on consciousnessk [Sanz] since not all consciousness must be built on the principie of trying to imitate the human mind. In this regard Leibnitz’s ontology seems more modern (by being less anthropocentric) than Kant’s metaphysics, though both pay due attention to the epistemic subject, which is possible — and I claim hereby, also required — in any possible ontology. As Goertzel put it “cognitive processes relating to each other synergetically, associate in a certain way with functors that map into each other” [Goertzel]. Such functors are of course task-related. Intelligence is practical, although exponents of this view tend to over-restrict their favorite domains of such practice — from psychomotoric interactions [O’Regan], to social praxis. Intelligence is always already situated, related to the tasks, and in that way necessarily dynamic. Floridi sees this point, but his ontology/axiology of information may be lagging behind some of its creator’s razor-sharp ideas. As [Beni] pointed out in his analysis of Floridi’s ontology, information (however structural) is never just ontological, but by its nature pragmatic. Syntactic, or semantic information cannot be defined without the pragmatic component because

kSanz’s point recently encountered a counterargument by Block: How would we recognize non-humanoid consciousness? The gist of this disagreement lies in the different criteria for consciousness: Sanz’s are broadly functional, Block’s pertain to first-person feel and its extrapolaron (at IA C A P June 2018, Warsaw).

Subject Is No Object: Complementary Basis of Information


syntactic features, such as simplicity, are essentially pragmatic [Boltuc, 1998]. Syntax alone is just geometry. Without verification in the outside world, syntax does not tumble just into semantics, it tumbles down all the way to pragmatics [Boltuc, 2018a]. Thus, information is always already for a cognitive agent, never prior to the reference frame. Floridi is very right to define it in a relationist framework. The general intelligence approach allows us to narrow the scope of such framework to intelligence, very broadly understood. Henee, let me cióse with a platitude: Information is information for general intelligence. This takes into account Barker’s clause that such intelligence has its own interests, in particular the interest in surviving, which would serve as a nicely myopic way to justify Floridi’s priority towards existence. Any attempts at a more generally metaphysical justification violates what we are calling Leibniz’s condition of epistemicity. In a recent paper, I emphasized the role of non-reductive epistemicity for reality creation, particularly in the area of ethics [Boltuc, 2018b]. This follows up on a broader point that the one thing today’s machines lack is firstperson non-reductive stream of consciousness, or puré epistemicity [Boltuc, 2009; 2012]. In the first part of the current essay I develop this point in more general terms of subject that is not an object. I remain agnostic whether such puré subject has to be instantiated in animal brains, with a strong predilection to the negative answer ( contra Searle’s and Block’s opposite predilections). I do not think my view leads to panpsychism [Chalmers], though it is not inconsistent with it. The talk of panpsychism has been, strangely enough, a kind of religious talk. Let me do a vague ending1 for those who want to examine this topic further: Non-reductive consciousness is a concept that may or may not be viewed as anthropomorphic — this depends on whether we want it as cognition or hard-consciousness. One easy way out is to say that cognition is functional, but h-consciousness first-personal (that’s what I do in footnote k above). But this is quitter-shallow. Here is the vague piece: General ontology, while pragmatically related to cognition, does not need the anthropocentric tilt. Cognition should not be viewed as anthropocentric. I’m trying to struggle through, between Sanz and Block, searching for nonanimal-centric first-person h-consciousness that is ontologically general. Cognitive synergy, and in general the framework of general intelligence,

^ la r ity is not enough, argued H.H. Price and Hywel Lewis.


P. Bottuc

opens a much broader frame of reference than phenomenalism; as long as it does not forcé metaphysical reductivism upon itself. 10.

Easing Out

In this chapter, I have been trying to build very little, while standing on the shoulders of giants. The triadic ontological structure may have already been present in Heraclitus and is in full blossom in Plato’s later metaphysics, where Plato bites the bullet on Aristotle’s third-man argument raised against his early theory of ideas. Later work along similar lines ineludes Hegel, Peirce and Gonseth. In dialectical tradition, there is much pressure (coming largely from left-Hegelians, including Marx and Habermas) to zero in on social philosophy. Such pressure should be resisted since it has led to under-development of the ontological aspect of modern theory. The focus on puré epistemic subject, and its object, can be distilled from Fichte’s Wissenschaftslehre and HusseiTs Ideas. Similar notions of subject and object provide conceptual grounding for Russell’s early ver­ sión of neutral monism ( The Analysis of Mind, 1921). The theory builds two independent conceptual structures — the epistemic and the ontological one — that provide complementary, irreducible descriptions of the world. Russell rejected this model (in his The Analysis of Matter, 1927) in favor of metaphysical materialism, but the debate at that time was partly centered around Russell’s atheism and not just philosophy of mind. Within general intelligence and consciousness studies, those topics should be addressed in neutral terms, such as those brought by general information theory. In those terms, information is complementary, not merely subjective, or epistemo­ lógica!, but also, in a deep sense, not merely ontological. More broadly, it is a dialectical process, a spiral movement back and forth between the objective and subjective take on reality (and maybe also between entropy and complexity, Fultot-style). Application of Plato’s triadic structure allows us to move beyond static subjective and objective dichotomy. It pro­ vides a link with the triads in Indian and Chinese traditional philosophy, today known especially within complementarity of yin and yang. Without the technical, non-anthropomorphic ontology of the epistemic subject, humanism becomes purely emotive and socio-political, or teological. Au bout du compte, dialectics based on complementarity of subject and object as well as on the epistemic/ontic structures built upon those mutually irreducible concepts provides the background for the philosophical the­ ory of information. It also seems helpful in creating a unified theory of

Subject Is No Object: Com plem entary Basis of Information


intelligence, and o f consciousness. Incidentally, and quite incredibly, it m ay also address the m ain issues in philosophical m etaphysics.

Bibliography J. Barker, Too Much Information: Questioning Information Ethics. APA Newsletter on Philosophy and Computers, Fall (2008). M. D. Beni, Epistemic Informational Structural Realism. Minds & Machines, 26 , 323 (2016). G. Berkeley, Treatise Concerning the Principies of Human Knowledge. Jacob Tonson: London (1734). P. Boltuc, Ideas of the Complementary Philosophy [Idee Filozoff Komplementarnej]. Przypis, 1, 4-8 (1984a). P. Boltuc, ‘Parmenides’ , Introduction to Plato’s Dialectics [Parmenides’ jako wprowadzenie do dialektyki Platona]. Studia Filozoficzne, 10 , (1984b). P. Boltuc, Introduction to the Complementary Philosophy [Wprowadzenie do filozofii komplementarnej]. Colloquia Communia, 4, 221-246 (1987). P. Boltuc, W hy Emeralds are Not Grue: A Case for Pragmatic Simplicity. Eidos, 6, 7-36 (1998). P. Boltuc, The Philosophical Issue in Machine Consciousness. International Jour­ nal o f Machine Consciousness, 1, 155-176 (2009). P. Boltuc, Metaphysical Theory of Information: Beyond the Theory of L. Floridi. Delivered at the Doctórate Honoris Causa for Luciano Floridi Ceremony, Suceava, unpublished, October (2011). P. Boltuc, The Engineering Thesis in Machine Consciousness. Techné: Research in Philosophy and Technology, 16 , 187-207 (2012). P. Boltuc, Is There an Inherent Moral Valué in the Second-Person Relationships? In Abbarno, G.J. (ed.). Inherent and Instrumental Valué. University Press of America: Lanham, MD (2014), pp. 45-61. P. Boltuc, Church-Turing Lovers. In Lin, P., Abney, K. and Jenkins, R., (eds.). Robot Ethics 2.0: From Autonomous Cars to Artificial Intelligence. Oxford University Press: Oxford (2017), pp. 214-228. P. Boltuc, Cognitive Agents: Is There a Moral Gap Between Human and Arti­ ficial Intelligence? In Tzafestas, S. (ed.). Information, Communication and Automation Technology Ethics in the Knowledge Society Age. Nova Science Publishers (2018a). P. Boltuc, Strong Semantic Computing. Procedía Computer Science, 123 , 98-103 (2018b). M. I. Buber, I and Thou. Kaufmann, W . (ed.). Charles Scribner and Sons: New York (1970). M. Burgin, Theory of Named Sets. Nova Science Publishers, New York (2011). M. Burgin, Bidirectional Named Sets as Structural Models of Interpersonal Com­ munication. Proceedings, 1, 58 (2017). M. Burgin, Platonic Triangles and Fundamental Triads as the Basic Elements of the World. Athens Journal o f Humanities and Arts, 5(1), 29-44 (2018).


P. Bottuc

M. Burgin and Y. Zhong, Information Ecology in the Context of General Ecology. Information, 9(3), 57 (2018). D. Chalmers, Facing Up to the Problem of Consciousness. Journal o f Consciousness Studies, 2, 200-219 (1995). D. Chalmers, Moving Forward on the Problem o f Consciousness. Journal of Con­ sciousness Studies, 4, 3-46 (1997). S. Darmos, Using Quantum Erasers to Test A nim al/R obot Consciousness. APA Newsletter on Philosophy and Computers, 17(2), (2018) (in publication). D. Dennet, Quining Qualia. In Marcel, A. and Bisiach, E. (eds.). Consciousness in Modern Science. Oxford University Press: Oxford, (1988), pp. 42-77. G. Dodig Crnkovic, W . Hofkirchner and W . Floridi’s, Open Problems in Philos­ ophy o f Information, Ten Years Later. Information, 2, 327-359. J. G. Fichte, The Science of Knowledge: With the First and Second Introductions, Heath, P. and Lachs, J. (eds.). Cambridge University Press: Cambridge (1970). L. Flor idi, W hat is the Philosophy of Information? In Moor, J. H. and Bynum, T. W . (eds.). Cyberphilosophy: The Intersection o f Computing and Philoso­ phy. Blackwell: Oxford (2002), pp. 115-138. L. Floridi, Understanding Information Ethics. APA Newsletter on Philosophy and Computers, 7(1), 3-12 (2007). L. Floridi, A Defence o f Informational Structural Realism. Synthese, 161, 219 (2008), h ttps:// L. Floridi, Against Digital Ontology. Synthese, 168(1), 151-178 (2009). L. Floridi, The Philosophy of Information. Oxford University Press: Oxford ( 2011). M. F. Fultot, Ethics of Entropy. APA Newsletter on Philosophy and Computers, 15(2), 4-9 (2016). B. Goertzel, Mapping the Landscape of Human-Level Artificial General Intelligence. AI Magazine: Menlo Park, CA (2015). B. Goertzel, From Abstract Agents Models to Real-World AGI Architectures: Bridging the Gap. In Everitt, T., Goertzel, B. and Potapov, A. (eds.). Arti­ ficial General Intelligence. Lecture Notes in Computer Science, Vol. 10414. Springer: Cham (2017a). B. Goertzel, Toward a Formal Model of Cognitive Synergy. Cornell University Press. (2017b), arXiv: 1703.04361 [es.AI]. F. Gonseth, Remarque sur l’idée de la Notion de Complémentarité. Dialéctica, 2, 413-420 (1948). E. Husserl, Ideas: General Introduction to Puré Phenomenology. Routledge: Abingdon (1931). E. Ilienkov, Dialectical Logic, Essays on its History and Theory. Creighton C. H. (trans.). Progress Publishers (1977). R. Ingarden, D er Streit um die Existenz der Welt: Existentialontologie, Niemeyer, M. (ed.). The University of California: Oakland, CA (1964). S. Jaki, God and the Cosmologists. Scottish Academic Press: Regnery Gateway Inc., Edinburgh (1989). F. Jackson, Epiphenomenal Qualia. Philosophical Quarterly, 32, 127-136 (1982).

Subject Is No Object: Complementary Basis of Information


I. Kant, Critique of Puré Reason. Cambridge University Press: Cambridge (1781). D. Lewis, PostScript to Mad Pain and Martian Pain. In Philosophical Papers, Vol. 1. Oxford University Press: New York (1983), pp. 130-132. G. M. Duncan (ed.), The Philosophical Works of Leibnitz. Tutle Morehouse Taylor: New Heaven, CT (1890). T. Nagel, Mortal Questions. Cambridge University Press (1979). T. Nagel, The View from Nowhere. Oxford University Press: Oxford (1986). L. Nemirow, Physicalism and the Cognitive Role of Acquaintance. In Lycan, W . G. (ed.). Mind and Cognition: A Reader. Blackwell: Oxford (1990), pp. 490-499. K. O ’Regan, Why Red Looks Red Rather Than Sounding Like a Bell: Understanding the Feel of Consciousness. Oxford University Press (2011). S. Plath, Tulips: In Collected Poems. Harper Collins Publishers Inc. (1992). H. H. Price, Perception. Methuen: London (1932). B. Russell, The Analysis of Mind. Alien and Unwin: Crows Nest (1921). B. Russell, The Analysis of Matter. Spokesman Books: Nottingham (1927). R. Sanz et al., Consciousness, Action Selection, Meaning and Phenomenic Antic­ iparon. International Journal of Machine Consciousness, 4(2), 383-399 ( 2012).

A. Shalom, Body/Mind Conceptual Pramework and the Problem of Personal Identity: Some Theories in Philosophy, Psychoanalysis and Neurology. Prometheus Books: Amherst, NY (1989). E. Stuart, The Correspondence o f Elizabeth Stuart, Queen of Bohemia, Vol II. Akkerman, N. (ed.). Oxford University Press: Oxford (2011).

Chapter 2

Information and the Vision of Stephane Lupasco: Science, Logic and Philosophy Joseph E. Brenner Vice-President, Transáisciplinary Projects, International Society for Studies of Information, Vienna, Austria joe. brenner úbluewin. ch The creation of new ideas, which might contribute to the development of the field of information, is neither a continuous ñor a linear process. I have therefore, here, only summarized my published papers in lieu of producing a completely new one. All my prior works involve the application, in infor­ mation Science and philosophy, of the updates and extensión I have made of the logical system of the Franco-Romanian thinker Stephane Lupasco (1 9 0 0 1988). This non-propositional system, grounded in the quantum mechanics of our world, allows inferences to be made about the evolution of complex processes at biological, cognitive and social levels of reality. By placing my papers in conjunction, I attempt to further show here the relevance of this logic of real processes to ongoing studies of the nature and function of information.


Introduction: The Logic of Stephane Lupasco

Classical and modern logics are epistemological domains concerned with the truth of propositions or their mathematical equivalents. Science deais with the ontology of our physical world and its change — reality. Change can be seen as a consequence of the underlying duality of the universe: the metaphysical dualities — presence and absence, actual and potential trans­ íate into physical dualities and oppositions “first” of the quantum world 0 to < 1. Other theories of non-quantum phenomena which make use of quantum formalism do so in a highly selective manner, but we claim that the relation of potentiality to actuality describes that the logical-dynamic relations in macroscopic ontological change in general are isomorphic to some fundamental features of the quantum world which could be a contribution to the basic physics of both.

Integral Biomathics Support Action,



J. E. Brenner

Sustainability and ecology

This paper was written at the suggestion and with the encouragement of my “mentors” in the Philosophy of Information, Wu Kun and Zhong Yixin, an associate and friend of Wu and a pioneer in China in the field of Artificial Intelligence. Zhong has also led the development of Intelligence Science in China. Most recently, he applied his approach to the definition of an Infor­ mation Ecology. I have related this in my paper to the earlier conception of an Information Ecology by Capurro, whose work is discussed in Sec. 4.1. I have included a reference of this paper despite that fact that it was rejected by the Journal Sustainability for a Special Issue of which it had been submitted. This perhaps unusual move was made because of the valué of the critiques by the reviewers, both of my general approach and its application in the specific areas indicated. Parts of their criticisms are not tenable: they reproduce the error I mentioned in the Introduction of judging LIR by the standards which LIR supersedes. However, the reviewer brought out aspects of my approach to which I refer in Sec. 5. I consider the critique as exemplary of a correct scientific dialogue. 5.

W hat is Missing in LIR?

This essay cannot have a scientific conclusión of its own. In lieu of one, I offer some final comments. 5.1.

Areas fo r further research

Whatever the not yet fully imagined details may be of any further Infor­ mation studies, it will clearly inelude reference to the in-depth studies of aspects of information by Burgin and Dodig-Crnkovic, Wu, Marijuan, Deacon, Schroeder and Capurro, among several others. Specific projeets of mine inelude (1) the comparison of Eastern and Western logics, building on the initial study reported in [Brenner, 2017]. “Linking the Tao, e t c ” , and (2) a graphical representation, in the complex plañe, of the movements of LIR logical elements from actuality to potentiality and from identity to diversity. 5.2.

Lupasco’s errors

It is also necessary to point out what is missing in LIR, and in the theory of Lupasco on which it is based (cf. Deacon [2010] on what is missing

Information and the Vision of Stephane Lupasco: Science, Logic and Philosophy


in the concept of information). Let me first mention where I think the latter is wrong or at best misleading. From the initial presentation of his ideas in his 1935 thesis, Lupasco repeatedly defended a concept of affect or affectivity as a phenomenon sui generis, totally outside his logic and its picture of the dynamics of real processes. Affect for Lupasco was the only totally ontological entity, in a sense going away from his own conception of the absence of absolutes in reality. Such a position, if nothing else, is incompatible with current views of the embodiment of emotion by Damasio and others. Another error that I consider Lupasco made was his repeated proposal, e.g., in [1987] of the universe as comprehending a trinity of universes based on a purely formal analogy with his triadic pictures of dynamic processes, causality and time and space. He referred to Russian work by Blokhinstev (which I have been unable to lócate) but seems to me to follow a pattern of pseudo-science with which I have had some direct experience. It might be more to the point, today, to determine if there are dynamic relations between the currently postulated but not yet characterized forms of dark matter and energy and “ordinary” matter — energy. Nicolescu maintains a modified versión of Lupasco in his differentiation between a logical included middle LIR; an ontological included middle, applicable to the constructed entities of Transdisciplinary Subject and Object; and a hidden included middle, at the heart of reality and its movement. I believe the properties of the (dynamic) logical included middle are adequate for both a scientific and moral view of human thought and existence. My work is thus complementary to that of Nicolescu, but I consider the latter an essential component of a future synthesis, a “New Eclecticism” (see Sec. 5.3).


Toward a new eclecticism

Under these circumstances, what can be done to remove whatever it is that blocks the acceptance of LIR as a subject of study and debate, something that can be criticized and improved? There is an absence of “experimen­ tal’ case histories and data, but this is a common problem in philosophy, logical or not. Wu’s expression, mentioned above of “the scientification of philosophy” is relevant here. I conclude this overview with an extensión of the plea that I made in Logic in Reality for a “New Skepticism” . Now, I suggest a need for a New Eclecticism” of which Science, philosophy, art and logic are not only


J. E. Brenner

components, as in the transdisciplinarity of Nicolescu, but which are jointly applied jointly. Let me give just a few current examples: the concept of Luhn of a causal-compositional theory of information [Luhn, 2012a]; the work of Cottam and Ranson on bridging the gap between life and physics [Cottam and Ranson, 2017]; the concepts of operators in the sense developed in my article with Burgin [Burgin and Brenner, 2017]. The model for such a universe of serious discourse is also suggested in my article on LIR as not only linking the principies of Eastern (Chinese) and Western Science but also philosophy and art [Brenner 2017]. The dialogue should be able to intégrate “open” metaphysics such as that of McGinn [2011]. It is obvious that such a concept flies in the face of the current fragmentation of knowledge and the massive amount of detail required for progress in scientific disciplines. To say that eclecticism is a positive alternative has its own problems: the term eclecticism is sometimes associated with dilettantism and lack of rigor, but historically it refers rather to selection of the best of available alternatives. This implies, however, the development of new forms of knowledge which incorpórate form, method, attitude, stance and ways of thinking [Capurro, 2013] in conjunction with content [Nicolescu,



Critiques o f L IR

The most common comments made are that the theory is not new or that it is “just” like quantum logic. However, no one has cited a logic or a philosophy which addresses the problems of concern in the papers discussed above. Quantum logic applies to the quantum world, and LIR applies to the common and at the same time most complex aspects of our everyday world. It is not a substitute of Science, but a partner, with a function similar to that of mathematics if you like. In an eclectic study of the foundations of consciousness, Clarke stated the need for a context-dependent logic, but could refer only to the undeveloped system of Matte Blanco, also mentioned in Brenner [2018]. Roland Scholz, Academic Editor of the Journal Sustainability, pointed to the pioneering work on transdisciplinarity, cited by Nicolescu, by Eric Jantsch, Jean Piaget and Leo Apostel in the early 1970s. Scholz notes that the propositional logic retained by these authors is insufhcient for describing the behavior of living Systems. What is striking, however, is that Scholz cited no other authors in the last half-century who have used a non-propositional logical perspective. Until further notice, accordingly, my

Information and the Vision of Stephane Lupasco: Science, Logic and Philosophy


thesis stands that Lupasco occupies an essential place in the thought of our time. Acknowledgments I would like to express my gratitude to the people who have accompanied as well as led me in this enterprise: Basarab Nicolescu who launched me on my work on Lupasco; Johanna Seibt and John Symons who helped me shape Logic in Reality; Wolfgang Hofkirchner, Pedro Marijuan and Gyorgy Darvas from whom I first learned about information Science, systems and symmetry; Wu Kun with whom I have collaborated on the philosophy of infor­ mation; Rafael Capurro who brought to me the essential ethical perspective; Robert Ulanowicz, Terrence Deacon, Andrei Igamberdiev and Gordana Dodig-Crnkovic for their on-going shared insights and helpful criticisms. I also thank the following people for their interest in LIR and for the opportunity of collaborating with them in the indicated areas: Mark Burgin on the concept of operators; Plamen Simeonov on biomathics and East-West thought; Marc-Williams Debono, Editor of the journal Plasticite, on the concept of plasticity. My special thanks go to Professor Wu Kun, Director of the International Center for the Philosophy of Information at the X i’An Jiaotong University in Xi’An, China. In the period 2013-2017, Wu has published in Chinese, not only our joint articles, but several additional papers and conference presentations of mine. Bibliography Bishop, R. S. and Brenner, J. E. (2017). Potentiality, Actuality and Nonseparability in Quantum and Classical Physics: Res Potentiae in the Macroscopic World. Preprint, arXiv: 1801.01471v i. Brenner, J. E. (2005). Process in Reality: A Logical Offering. Logic and Logical Philosophy 14, 165-202. Brenner, J. E. (2008). Logic in Reality. Dordrecht: Springer. Brenner, J. E. (2009). Prolegomenon to a Logic for the Information Society. tripleC 7(1), 38-73. Brenner, J. E. (2010a). The Philosophical Logic of Stéphane Lupasco. Logic and Logical Philosophy 19(3), 243-285. renner, J. E. (2010b). The Logic of Ethical Information. Knowledge , Technology & Policy 23(1-2), 109-133. renner, J. E. (2011a). Information in Reality: Logic and Metaphysics. tripleC 9(2), 332-341.


J. E. Brenner

Brenner, J. E. (2011b). On Representation in Information Theory. Information 2, 560-578. Brenner, J. E. (2011c). Wu Kun and the Metaphilosophy of Information. Inter­ national Journal “Information Theories and Applications” 18(2), 103-128. Brenner, J. E. (2012a). The Logical Dynamics of Information. Deacon’s “Incomplete Nature” . Information — Special Issue on Modes o f Information, Materiality and Organization 3(4), 676-714. Brenner, J. E. (2012b). Systems and Information: A Transdisciplinary Study. Transdisciplinary Journal o f Engineering & Science (.ATLAS) 3, 57-76. Brenner, J. E. (2012c). Mark Burgin’s Theory of Information. Information 3(2), 224-228. Brenner, J. E. (2014a). Information: A Personal Synthesis. Information 5, 134-170. Brenner, J. E. (2014b). The Logic of the Physics of Information. Information 5, 389-403. Brenner, J. E. (2015a). Three Aspects of Information Science in Reality: Symmetry, Semiotics and Society. Information 6, 750-772. Brenner, J. E. (2015b). Information and the Future of Transdisciplinarity. Trans­ disciplinary Journal o f Engineering & Science (ATLAS) 6, 86-100. Brenner, J. E. (2016). The ‘Naturalization’ of the Philosophy of Rafael Capurro; Logic, Information and Ethics. In Information Cultures in the Digital Age: A Festschrift in Honor o f Rafael Capurro, Kelly, M. and Bielby, J. (eds.). Springer: Wiesbaden. Brenner, J. E. (2017). Linking the Tao, Biomathics and Information with a Logic of Energy. Progress in Biophysics and Molecular Biology 131, 15-33. Brenner, J. E. and Burgin, M. (2011). Information as a Natural and Social Operator. International Journal “Information Theories and Applications” 18(1), 33-49. Brier, S. (2008). Cybersemiotics: Why Information is not Enough. University of Toronto Press: Toronto. Burgin, M. (2010). Theory o f Information: Fundamentality, Diversity and Unification. Singapore: World Scientific. Burgin, M. (2012). Theory of Information. Fundamentality, Diversity and Unification, Information 3(2), 224-228. Burgin, M. and Brenner, J. E. (2017). Operators in Nature, Science, Technol­ ogy and Society: Mathematics, Logic and Philosophy. Philosophies 2, 21, h ttp ://w w w .m dpi.eom /2409-9287/2/3/21 (accessed 17 September 2017). Capurro, R. (2000). Einfuhrung in den Informationsbegriff. http://w w w .capurro .de/in fovorl-kap2.htm (accessed 26 January 2015). Capurro, R. (2003). Foundations o f Information Science: Review and Perspectives. http://www pere91.htm (accessed 23 February 2012). Cottam, R. and Ranson, W . (2017). Bridging the Gap between Life and Physics. Cham, Switzerland: Springer International Publishing.

Information and the Vision of Stephane Lupasco: Science, Logic and Philosophy


Clarke, C. (2013). Knowing, Doing and Being. New Foundations fo r Consciousness Studies. Exeter, UK: Imprint Academic. Deacon, T. W . (2010). What is missing from theories of information? In Infor­ mation and the Nature o f Reality: From Physics to Metaphysics, Davies, P. and Gregersen, N.H. (eds.). Cambridge, UK: Cambridge University Press. Deacon, T. W . (2012). Incomplete Nature. How Mind Evolved from Matter. New York: W .W . Norton & Co. Dodig-Crnkovic, G. and Hofkirchner, W . (2011). Floridi’s “Open Problems in Philosophy of Information” , Ten Years Later. Information 2, 327-359. Dodig-Crnkovic, G. (2017). Nature as a Network of Morphological Infocomputational Processes for Cognitive Agents. The European Physical Journal Special Topics 226, 181-195. Floridi, L. (2010). The Philosophy o f Information. Oxford: Oxford University Press. Floridi, L. (2014). The Fourth Revolution. How the Infosphere is Reshaping Human Reality. Oxford: Oxford University Press. Hofkirchner, W . (2009). How to Achieve a Unified Theory of Information. tripleC 7, 357-358. Hofkirchner, W . (2013). Emergent Information: A Unified Theory o f Information Framework. Singapore: World Scientific. Kastner, R. E., Kauffman, S. and Epperson, M. (2017). Taking Heisenberg’s Potentia Seriously. Preprint arXiv:1605.05907vl [quant-ph]. Luhn, G. (2012a). The Causal-Compositional Concept of Information Part I: Elementary Theory: From Decompositional Physics to Compositional Infor­ mation. Information 3, 151-174. Luhn, G. (2012b). The Causal-Compositional Concept of Information — Part II: How Does the Relationship Between Information, Fairness and Language Evolve, Stimulate the Development of (New) Computing Devices and Help to Move Towards the Information Society. Information 3, 504-545. Lupasco, S. (1987). L ’energie et la matiere vivante. Monaco: Editions du Rocher (Originally published 1962, Juillard, París). Magnani, L. (2017). The Abductive Structure o f Scientific Creativity. Heidelberg/Berlin: Springer. Marijuan, P. C. (2013). The Uprising of the Informational: A New Way o f Thinking in Information Science. Presented at lst International Conference in China on the Philosophy o f Information, X i’an, China, 18 October 2013. McGinn, C. and Nicolescu, B. (2002a). Nous, la particule et le monde. París: Editions du Rocher (Originally published 1985, Éditions Le Mail, París). Nicolescu, B. (2002b). Manifestó o f Transdisciplinarity. Albany, NY: State Uni­ versity of New York Press. Simeonov, P. L. et al. (2012). Stepping Beyond the Newtonian Paradigm in Biol°gy- Towards an Integrable Computational Model of Life: Accelerating Discovery in the Biological Foundations of Science. INBIOSA W hite Paper. In Integral Biomathics: Tracing the Road to Reality, Proceedings of BioMath

J. E. Brenner


2 0 1 1 , P a r ís a n d A C I B ’ 1 1 , Stirling UK., Simeonov, P. L., Smith, L. S. and Ehresmann, A. C. (eds.). Springer. Wu, K. (2010). The Basic Theory of the Philosophy of Information. In P r o c e e d in g s o f th e f t h In t e r n a t io n a l C o n f e r e n c e o n the F o u n d a t io n s o f I n f o r m a t i o n S c ie n c e ,

Beijing, China, 21-24 August 2010. Wu, K. (2012). The Essence, Classification and Quality of the Different Grades of Information. I n f o r m a t i o n 3, 403-419. Wu, K. (2016). The Interaction and Convergence o f the Philosophy and Science of Information. P h i l o s o p h ie s 1, 228-244. Wu, K. and Brenner, J. E. (2013). The Informational Stance; Logic and Philoso­ phy. Part I: The Basic Theories. L o g ic a n d L og ica l P h i l o s o p h y 22, 1-41. Wu, K. and Brenner, J. E. (2014). The Informational Stance; Logic and Phi­ losophy. Part II: From Physics to Society. L o g ic a nd L og ica l P h i l o s o p h y 23, 81-108. Wu, K. and Brenner, J. E. (2015). An Informational Ontology and Epistemology of Cognition. F o u n d a t io n s o f S c ie n c e 20, 249-279. Wu, K. and Brenner, J. E. (2017a). A Unified Science-Philosophy of Information in the Quest for Transdisciplinarity. In I n f o r m a t i o n S tu d ie s a n d th e Q u e s t f o r T r a n s d is c ip lin a r ity : U n ity T h ro u g h D i v e r s i t y . Singapore: World Scientific. Wu, K. and Brenner, J. E. (2017b). Philosophy of Information; Revolution in Phi­ losophy. Toward an Informational Metaphilosophy of Science. P h i l o s o p h ie s 2, 22-40.

Chapter 3

Information or Noise? Terrence W. Deacon University of California, Berkeley, USA

W h e r e is th e w i s d o m w e h a v e lo s t in k n o w l e d g e ? W h e r e is th e k n o w le d g e w e h a ve lo s t in I n f o r m a t i o n ? T S E lio t

Pigeons? The pigeons were chased off with the bang of a shotgun. But a much bigger bang was soon to be “heard.” In 1960, Bell Labs built a 20-foot horn-shaped microwave antenna in Holmdel, New Jersey. It was part of an early effort to beam microwave Communications across the globe by bouncing them off a large reflective balloon satellite called Echo. To pick up the weak signáis reflected back to earth required a large highly sensitive microwave antenna. The experiment worked, but within two years, another far more efficient approach replaced the Echo project. A satellite called Telstar became the first Communications satellite to collect and amplify radio signáis and beam them back to earth. Telstar was thus the forerunner of all our modern Communications satél­ ites now crowding the heavens. But with this more effective technology to amplify the signáis, a large supersensitive microwave antenna was not required. Indeed, today any household can mount a small “dish” antenna on their roof to pick up the vast amount of microwave-based T V and internet signáis being beamed from the great great grandchildren of Telstar. So in 1962, Bell Labs offered two astronomers — Arno Penzias from ermany and Robert Wilson from the US, both interested in the new field 67


T. W. Deacon

of radio-astronomy — the opportunity to use the antenna to search for microwave signáis coming from interstellar space. While tuning the sensitive antenna, however, they noticed an annoying problem: there was a faint but constant background “hiss” always present. When this apparent radio static didn’t change irrespective of whether they aimed it skywards or at New York City they determined that the problem was likely in the apparatus itself. They ruled out radiation from nuclear testing and seasonal variations because it didn’t change with time. They then became suspicious of the pigeons that tended to roost in the large antenna. With a shotgun and a serious cleaning of bird droppings, they eventually dispensed that possible source only to find that it made no difference. The noise was unaltered no matter what they did. They checked and rechecked their equipment assuming that the noise had to arise from some electronic source, which was not unlikely, considering the sensitivity they were hoping to achieve. But no. To their frustration they couldn’t seem to eliminate this constant uniform static irrespective of what they did to clean up the system. After checking and rechecking, they eventually became convinced that the noise couldn’t be originating from the device itself or from any specific local sources. So, by this process of elimination they had to conclude that it must be coming from outside. But this posed another even more counterintuitive problem. If the uniform static that persisted irrespective of where they aimed the antenna carne from outside, then it must be coming from everywhere at once! As Conan Doyle’s fictional sleuth Sherlock Holmes reasoned: “Once you eliminate the impossible, whatever remains, no matter how improbable, must be the truth.” If it wasn’t locally or internally generated noise then it had to be “cosmic noise.” And since it was coming from everywhere at once, it couldn’t be coming from individual stars or galaxies. The only remaining possibility, as odd as it seemed, was that this “hiss” of microwave radiation was emanating from empty space itself— i.e. from the cosmic background. Does that make any sense? Luckily, they were well informed about current debates in astrophysics and were also in the right place at the right time. Down the road at Princeton University an astrophysicist named Robert Dicke had theorized that the grand cosmic explosión — the “Big Bang” — that appears to have ereated the whole of the known universe should have left its signature in the form of heat radiated throughout the universe. Heat is radiated through space as infrared radiation, below the spectrum of visible light, but typ1 cally at a much higher frequeney than microwave radiation. Since the Bk

Information or N oise?


Bang occurred over 13 billion years ago, the heat radiation from that event striking earth now would have originated over 13 billion light years away. Following the work of the astronomer Edwin Hubble earlier in the 20th Century it was known that radiation (e.g. light) emanating from stars and galaxies further away from our own galaxy is red-shifted (i.e. its wavelength is elongated and so its frequency is lower). This is because, as Hubble reasoned, these sources are all moving away from us as the universe expands in all directions, and because this expansión is taking place everywhere at once more distant cosmic objects are moving away faster than nearer objects. The consequence is that more distant radiation sources are more red-shifted than nearer sources. The most distant sources will therefore be hugely red-shifted, and nothing is more distant in space and time than the Big Bang. Based on these considerations Dicke had predicted that the residual heat emanating from the Big Bang would be dispersed everywhere and massively red-shifted. He was designing an experiment to test this theory when he learned of Penzias and Wilson’s finding. Despite the fact that Wilson doubted Big Bang cosmology, the ubiquitous microwave “noise” picked up by the Bell Labs antenna had all the characteristics predicted by Dicke’s theory. As a measure of heat it was appropriately a uniform random bell-curve of frequencies. It was massively red-shifted to the extent that it was registering heat at just slightly above absolute zero (—270K), and it was coming from everywhere at once with no discernible differences, as would be appropriate since the Big Bang involved the whole universe at that distant time. It was a meaningful signal, not noise, despite all appearances. Years later, Penzias and Wilson received the Novel Prize for their discovery, the Bell Labs antenna was dedicated as a National Historical Landmark, and the COBIE satellite mapped this cosmic background radi­ ation with sufficient precisión to demónstrate that there are indeed subtle inhomogeneities in its distribution after all. A phenomenon that had been present since the beginning of the universe a become information about something — the heat of this originative cosmic explosión — once the technological and theoretical interpretive aPparatus became available. It took years of doubting, testing and theoWils^ ^ PeaCk consensus on what it represented. In this process Penzias, int ^ Cke and innumerable other scientists progressively updated their it a rí?r^ a^ons °f this “noise” many times as they struggled to understand The aÜOn ab° Ut SomethinS else* 6 mora^ One man’s noise is another’s information.


T. W. Deacon

W hat Is It All About? So whether it is random or organized, caused by the droppings of pigeons or just the residual heat left over after some unimaginably huge and distant explosión, even a ubiquitous static hiss can be about something if one knows what to look for. But when did the heat of the Big Bang become information? Was it always “about” the origins of the universe? Or was it just radiation traversing vast distanees and time until it was noticed and correctly interpreted by these astrophysicists? Was it information when Penzias and Wilson were convinced that it was a flaw in their detection device, or that it was due to pigeon poop? And what if modern physics turns out to be wrong about this cosmic background? Would that hiss cease to be information? Or would it then become information about something else? Indeed, does it need to be about something in order to be informa­ tion? Surprisingly, there is considerable confusión still lingering over such questions. Our current era is often rightly described as “the information age.” In our everyday lives, information is a necessity and a commodity. It has become ubiquitous largely because of the invention, perfection and widespread use of computers and related devices that record, analyze, replí­ cate, transmit, correlate and encrypt data entered by humans or collected by sensor mechanisms. This stored and transmitted information is used to pro­ duce correspondences, invoices, sounds, images and even precise patterns of robotic behavior on factory floors. We routinely measure the exact infor­ mation capacity of data storage devices made of Silicon, magnetic disks, or laser-sensitive plastics. Scientists have even recently mapped the molecular information contained in a human genome and studied its correspondence to protein structure and regulatory processes inside cells. And household users of electronic Communications have learned that the information “bandwidth” of the cable and wireless networks that they depend on for connection to the outside world matters for the clarity and reliability of their video entertainment. Although we use the concept of information almost daily without con­ fusión, and use computers and cell phones and vast data networks to exchange, analyze and store information, I believe that we still don’t really know what it is. Despite our seeming familiarity with these many uses and aspeets of information, it is my contention that we currently are working with a set of assumptions about it that are only sufficient to handle the tracking of its most minimal physical and logical attributes.


Information or N oise?

Surprisingly, even our most sophisticated theories about information are insufficient to explain one of the most basic and elementary defining feature of information. That is they fail to explain what makes it possible for information-bearing media to be about something else, and what constitutes its significance and functional valué. These are serious shortcomings that impede progress in many scientific and social endeavors. The concept of information is a central unifying concept in the Sciences. It plays critical roles in physics, engineering, computation, biology, cognitive neuroscience and of course the psychological and social Sciences. It is, however, defined somewhat differently in each, to the extent that the aspects of the concept that are most relevant to each may be almost entirely nonoverlapping. Although it is often said that questions about meaning and valué are issues for philosophical reflection, not scientific investigation, all our scientific endeavors depend on assessing the meaning and significance of our observations and experiments.

In fact, debates about the nature of physical processes at the very small subatomic (quantum) scale turn on how we understand the process of measurement and the information it provides. While the adequacy of our mathematical descriptions of quantum effects are beyond dispute, what is meant by these formalisms is open to wildly diverging speculations. In other words, experiments performed to discern what is taking place at this extreme smallest limit of size provide information that we find difficult to interpret. In fact, nobody is certain what this information is about. Thus, a recent chronicler of the history of quantum theory, Jim Baggott, cites two of the most important ñames in quantum physics to make this point. Thus: “Niels Bohr claimed that anybody who is not shocked by the theory has not understood it. The charismatic American physicist Richard Feynman went further: he claimed that nobody understands it.” 1 Feynman concludes that trying to understand what information from quantum level events is about is to go down a “blind alley from which nobody has yet escaped.” 2 But how much of this is due to the intrinsic weirdness of what this information is actually about and how much is due to not quite understanding how information Can about anything? Perhaps at this tiniest scale the very nature of this aboutness” relation becomes problematic. Without a clear physical


(2011). The Quantum Storu: A History in LO Moments. (Oxford University (from the book description).

Jfew York) York)



The Character of Physical Law.





T. W. Deacon

account of how anything can be about anything else, however, we can’t be sure how to even start to answer such questions. Beyond the Bits The most precise technical definition of information carne from the work of Claude Shannon, who while working at Bell Labs in the late 1940s found a way to precisely quantify many of the most important factors affecting the transmission and storage of information. His theory enabled engineers to determine how much information could be transmitted over a given communication channel (whether conveying a phone conversation or a string of numbers), how many “bits” of data can be stored in a given médium (whether book or magnetic disk), and how one might be able to compress and decompress a signal in order to maximize the capacity of a given trans­ mission or storage system. This theoretical breakthrough played a critical role in the development of information technologies over the next halfcentury. It has transformed 21st Century civilization in ways that no one could have predicted at the time. As we will see, however, this progress carne at the cost of entirely ignoring the ultimate defining property of information: being about something. So, this technical use of the term was effectively devoid of any trace of its original and colloquial meaning. On the one hand, by stripping the concept of its links to reference, meaning and significance, it became applicable to the analysis of a vast range of physical phenomena, engineering problems and even quantum effects. This made it the ideal tool for use in communication technologies and computation. But, on the other hand, this reduction of the concept to only refer to its minimal physical and logical attributes, specifically obscured those features that are critical to understanding living and mental processes. In many ways, we are currently in a position analogous to the early 19th Century physicists in the heyday of the industrial age, with its explosive development of steam-powered machines revolutionizing transportation and industry. Their understanding of the concept of energy was still laboring under the inadequate and ultimately fallacious conception of ethereal substances, such as phlogiston or caloric, that were presumably transferred from place to place to animate machines and organisms. So even though energy was a defining concept of the early 19th Century, the development of a relational rather than substantive concept of energy took many decades of

Information or N oise?


scientific inquiry to clarify. The contemporary notion of information is likewise colloquially conceived of in substance-like terms, as for example when we describe the “purchase” and “storage” of information, or talk about it being “lost” or “wasted” in some process. The concept of energy was ultimately explained by recognizing that it was a quite general sort of physical difference, and that it could be embodied in many forms (elevated weights, heat differences, incident light, Chemical bonds, etc.). Energy turned out not to be a thing but a relationship. It could be transformed but never created or used up. Eventually, scientists carne to recognize that the presumed ethereal substance that conveyed heat and motive forcé from one context to another was an abstraction from a process — the process of performing work — not anything material. Importantly, this abandonment of a substance-based explanation did not result in the concept of energy becoming epiphenomenal or mysterious. The fallacious conceptions of an ineffable special substance were simply abandoned for a dynamical and relational account that enabled precise assessment. Yet, as familiar as its use has become today, the term “energy” wasn’t even coined until 1807. Even today, look for an explicit (not indirect) definition for “energy” and you will be disappointed. As Van Ness comments: “Pick up a chemistry text, a physics text, or a thermodynamics text, and look in the Índex for “Energy, definition of,” and you find no such entry.” 3 This does not mean that the concept is in any way impre­ cise or ill-defined for the physicist or engineer. Indeed, just the opposite is the case. Abandoning the colloquial meaning of energy that treats it as a substance that can be extracted, stored, bought and sold, and used up, has revolutionized Science and technology. It was necessary to get over this more intuitive conception of energy to finally understand heat and Chemical reactions, and eventually to make sense of such weird phenomena as super conductivity and nuclear fusión. To understand the nature of information a similar reframing is neces­ sary. But the figure/background shift required is even more fundamental and more counterintuitive than that for energy. This is because what matters is not an account of its physical properties or even its formal properties.

'Nq 10^

k) ^

^ an ^ eSS

Understanding Thermodynamics. (Dover Publications,


T. W. Deacon

What matters in the case of information, and produces its distinctive physical consequences, is a relationship to something not physically there: what it is about. Ignoring this, the concept of information reduces to a physical attribute not fundamentally different from the arrangement of pebbles on a beach or stars in a constellation. These configurations can of course be precisely measured and analyzed. Studying these patterns might even provide evidence about how they carne to be organized that way. But aside from being treated as potentially useful to a mind eager to discern these causal relationships, they are just physical arrangements. There is nothing that makes them intrinsically meaningful. And the way that information causes things to happen is also unlike the way that other material and energetic processes produce effects. Consider a few typical examples. Information about an impending storm might cause one to cióse Win­ dows and shutters, information about a stock market crash might cause millions of people to simultaneously withdraw money from their bank accounts, information about some potential danger to the nation might induce idealistic men and women to face certain death in battle, and (if we are lucky) information demonstrating how the continued use of fossil fuels will impact the lives of future generations might affect our patterns of energy use worldwide.

These not-quite-present, non-intrinsic relationships can thus play the central role in determining the initiation and form of physical work. It is in this way that something not immediately present can make a difference in the world. In contrast, the material features that mediate these effects (a darkening sky, a printed announcement, a stirring speech, or a scientific argument, respectively) do not in themselves have these sorts of causal consequences. To develop a precise practical Science of information, it was necessary to give up thinking about information as some artifact or commodity as well as some intangible meaningful stuff. A radical paradigm shift in the scientific understanding of information made this possible. Like the scientific reconception of energy in the mid 19th Century, a revolutionary reconception of information took place in the middle of the 20th Century. Like its 19th Century predecessor, it gave rise to a highly successful technical concept that transformed the world. This redefinition of information made it possible to understand how any physical phenomenon, whether sig traveling within wires and electromagnetic waves, or patterns of ink soaJced

Information or N oise?


into paper and charges embodied in semiconductor devices, could be quantitatively analyzed. Information understood in this technical sense, however, had nothing to do with being about anything. This technical redefinition of the term ‘information’ referred to an intrinsic physical property of a given physical médium and became roughly synonymous with difference, order, pattern, or the opposite of physical entropy, depending on who was using it. Because “content” in the sense of meaning and significance were not intrinsically measurable attributes they were assumed to be non-physical, and therefore merely subjective glosses or causally irrelevant. Indeed, leaving these non-intrinsic non-physical attributes out of the technical definition of Infor­ mation proved to be essential for the explosive development of information technology that now underlies the vast web of human telecommunication and the computational tools that have transformed the society as well as the Sciences. But this redefinition of the concept of information, which is now the basis of nearly every technical use of the term, implicitly treats human thought and the meaning-making process itself as illusory. It is as though our mental experience is a mirage on the horizon of knowledge that will disappear as Science draws us closer to the details of brain function. Indeed, many have argued that the traditional sense of “information” is an anachronism destined for the refuse heap of ideas, along with notions of phlogiston and the ether wind. Are these reports of the demise of the traditional con­ cept of information exaggerated? To step beyond this impasse, we must try to make sense of the representational function that distinguishes information as non-technically under­ stood from other mere physical relationships. This requires finding a precise way of showing how what can be called the reference being communicated can be causally efficacious, despite not being physically embodied in the médium that “conveys” it. And yet at the same time this analysis must also maintain compatibility with the technical concept ion of information. 0 ignore either paradigm would be a mistake. But developing a bridge een ^ ese ways of conceiving information is not a trivial challenge. requires overcom ing som e deep con cep tu a l incom patibilities.

Inexistence syn th es^ a^ k ^ Ca^ com m itftients have significantly hindered attem pts at a This enterprise has been a casualty o f a ph ilosoph ical im passe


T. W. Deacon

that has a long and contentious history; the problem of specifying the ontological status of the contents of thought. These seemingly incompatible conceptions of information reflect the perpetuation of an intellectual schism that dates to the dawn of the enlightenment and which was eloquently articulated by René Descartes. In philosophy his argument became enshrined in what is known as the m ind/body problem. But it is not merely of philosophical relevance. I would argüe that it is implicit in the way that modern Science still divides the world into the physical and semiotic Sciences, with biology and psychology each internally divided into corresponding methodological subfields. It still motivates debates between those who believe that it will be possible to reduce mental phenomena to material relations and those who deny this possibility. This is paralleled by the debate about the definition of “information” between those who think that we can dispense with the concept of representation in favor of just analyzing physical correlations and those who argüe that “aboutness” is something more than just physical correlation. The enigmatic status of this relationship was eloquently, if enigmatically, framed in 1874 by the Germán philosopher Brentano’s use of the curious word “inexistence” when describing mental phenomena. He says: Every mental phenomenon is characterized by what the Scholastics of the Middle Ages called the intentional (or mental) inex­ istence of an object, and what we might cali, though not wholly unambiguously, reference to a content, direction toward an object (which is not to be understood here as meaning a thing), or immanent objectivity. This intentional inexistence is characteristic exclusively of mental phenomena. No physical phenomenon exhibits anything like it. We can, therefore, define mental phenomena by saying that they are those phenomena which contain an object intentionally within themselves.4

For a century and a half since Brentano’s words were first printed, we have proceeded as though the existent and inexistent aspects of information needn’t be related; as though the physical and the meaningful realms were incompatible conceptions of the world. Since then, whole realms of intellectual analysis and technical applications have flourished by explk' itly bracketing out one or the other side of this dilemma and pretending that it can be ignored. But in each case something critical is sacrificad*

4 F. Brentano (1874). Psychology Prom an Empirical Standpoint. (Routledge & Keg^ Paul, London).

Information or N oise?


The exclusively physical conception takes the referential use for granted, but then proceeds to bracket it from consideration, treating it as a sort of illusion, whereas, the exclusively intentional conception disregards the physicality of information and as a result renders the efficacy of this content thoroughly mysterious. Of course, there is the everyday compromise of sometimes working in one realm and at other times working in the other. Thus, for example, biologists feel equally at home describing the molecu­ lar basis of genetic inheritance as mere chemistry and also as information about bodies and their relationship to the environment. But the result is that even in the realm of scientific research we are trapped in Descartes’ world divided against itself. Throughout popular culture, where the split is simply taken for granted and this dilemma goes unnoticed, its corrosive influence on social organization, interpersonal relations, ethics and spiritual traditions grows with every advance in communicative technology. How did this dilemma arise? How could we ever have imagined that information is only physical stuff or that meanings only exist in some nonphysical realm? Ideas and meanings clearly aren’t ineffectual illusions and the sounds and pixels and electronic bits of charge that convey them aren’t dispensable. It is obviously the content that matters, but matter gives this content its efficacy. But how? This is the challenge that a unified theory of information must ultimately address, and we shouldn’t assume that just because we are now in possession of many unprecedented new tools for sharing, storing, manipulating and analyzing information that these questions have been answered.

Chapter 4

Reflections on the Concept of “Objective Non-Reality” in Information Philosophy En Wang Department of Philosophy, XVan Jiaotong University XVan, China welg^glewúqq. com On the one hand, although ancient Greek and medieval philosophies discuss “nominalism” and “realism,” the concept of “objective non-reality

is not

explained. On the other hand, modern philosophy is unable to guide the development of scientific rationality. It is even challenged by the scientific reason. Until the rise of the contemporary information Science revolution, the philosophers have been forced to explore the scope and substance of information. From the viewpoint of the inherent unity of universal rationality in Science and philos­ ophy, the Chinese philosopher W u Kun has revived the concept of


non-reality” and developed his “philosophy of information” system. Because the existence of “objective non-reality” is inherently a kind of “crossover


ontology, it may provide a new solution to the traditional philosophy problems. This may lead to a new paradigm breakthrough in philosophy.


Analysis of the Concept of “Objective Non-reality” from the History of Philosophy

*n ancient Greek philosophy, Plato proposed the ideal world as our cognitive object. According to his “cave theory,” he believed that the sense object is unreliable and the ideal world is the real entity. Only When we grasp the ideal world, we can complete the task of knowmg the w°rld. However, Aristotle argued that the individual things P sented in the sensory experience are the first entities. All modals 79


E. Wang

(including attributes, commonalities, ideas) are contained in individual concrete things, and thus they are not independent entities. Following this thinking, “Porphyry problem” was presented. In the book Introduction to the Aristotle’s Book “Categories”, Porphyry (AD 234-305) stated: about the species, do they exist independently or rely solely on the idea? If they exist, are they objective or non-objective? Does the existence of species company with the sensible thing or sepárate with it? This is a very esoteric question that requires more discussion (J. Barnes, 2003). After 200 years, Boethius (480-524) translated Porphyry’s questions into Latin, which sparked a heated discussion between “nominalism” and “realism” in the medieval times. There are both extremist and moderatist versions of these two views, respectively. The representative of extreme realism is Anselm, who thinks that the commonality is preceded by and independent of the individual. The commonality is more essential, and the universal things cannot just exist in mind (Taiqing Wang, 1981). In contrast, the representative of extreme nom­ inalism is Roscelinus (1050-1125), who believes that only individual things are real, and there is no realism at all. The concept is just a noun, sound, and even a gust of wind or shock of air (Lin Zhao, 2009). Roscelinus not only denies the independent reality of the commonality but also denies that commonality is a natural abstraction of the objective things. He attributes commonality itself as only a subjective ñame. As the explanations evolve further, two more modérate and compromised points gradually emerge. The representative of modérate realism is Thomas Aquinas, who explains the relationship between the commonality and the individual in a dialectical view. For Thomas, the commonality is before, in, and after the existence of individual things. In the beginning of the creation, the commonalities of all things existed in G od’s mind in the form of concepts. When the world was created, commonality existed only in the individual and was not separated from the individual. When we began to know the object, we understood the individual sensible things first and then through abstract thinking, we obtained the commonality in our mind (Taiqing Wang, 1981). Abelard is the representative of modérate nominalism. He argües the commonality is a concept, and the concept indicates the object. Although the object is not an independent entity, it exists as a universal natuie in sensible things. Abelard explains that “commonality as a universal concept has its objective content, not entirely subjective and arbitrary nonsense ñames. But they themselves are not an independent reality

Reflections on the Concept of “Objective N on-Reality” in Information Philosophy 81

(Xiaomang Deng and Lin Zhao, 2014).” It seems that Abelard’s “conceptualism” contains the thought of “objective non-reality.”



Contemporary Information Philosophy and the Concept of “Objective Non-reality” Critical analysis o f the m odem philosophy from the perspective o f information philosophy

Since the modern Western philosophy, the focus has shifted from ontology to epistemology. Nominalism is extended to empiricism, while realism is extended to rationalism. Both of these have tried to establish true knowledge. There are two conditions. First, the content of knowledge must be able to be continuously expanded, updated, and developed into an open system. Second, knowledge must also have universal necessity. Since Descartes, people mainly focused on subject-object dualism. For Descartes, the mind has no extensión, which is different from the matter. Accordingly, he established his epistemology through “innate ideas.” However, Descartes’ theory appears contradictory in the “body-mind problem” because he could not solve the problem: “how does the mind com­ bine with the body and interact with each other?” Finally, Descartes tried to solve it through the “pineal gland.” Later, Gassendi materialized the mind, claiming that the mind is a finer matter. While Mahler Burroughs spiritualized the matter to establish the theory of “the occasional cause of body and mind,” Spinoza established a prior “attribute dualism,” replacing the “entity dualism” with “body and mind parallelism.” Leibniz’s “Monadism” explained the body and mind problem through the pre-harmony rule. How­ ever, these theories failed to establish the truth of knowledge because rationalism shifts to dogmatism, while empiricism shifts to skepticism, for knowing the world only through sensible things, lacking universal necessity. In fact, the modern philosophy is based on traditional dualism ontology. owever, if the división of ontology is unclear, the building of knowledge m&y have some problems. Although later, Germán philosopher, Kant, critC1zed rationalism and empiricism through the theory of “transcendental with^IekenS^Ve ^u103-128 (2011). TT*• U’ stipulation of the category of evolution, Journal of Harbin 20.

K w umE. (1960) The unreasonable effectiveness of mathematics, Communica^°lpertST) ^ ^ an(* Mathematics, 13, No. 1, pp. 1-14. g ’ and Tumer, K. (2000) An introduction to collective intelliRress’ m Handbook °f A9ent Technology, (Bradshaw, J.M. ed.), AAAI/MIT Pp.?99-124^ ^tructural realism: The best of both worlds? Dialéctica, 43,

Chapter 10

Evolutive Information in the Anthropocene Era Rodolfo A. Fiorini*’t D e p a r tm e n t o f E le c t r o n i c s , I n f o r m a t i o n a n d B i o e n g i n e e r in g P o l it é c n ic o di M i la n o

(D E I B )

U n iv e r s it y

3 2 , P ia z z a L e o n a r d o da V in c i, 2 0 1 3 3 M I , I t a ly r o d o lfo .fio r in [email protected] p o lim i. it

The frequency of the use of the words data, information, knowledge and intelligence is very high in our current daily lives. W e take for granted our understanding of “data” meaning. Then, we have the problem to find adequate relations between data, knowledge, intelligence and information. Horror Vacui and Horror Pleni are two cosmic, fundamental concepts referring to humans’ intellectual operative range which can be used as references. A


dichotomy” permeating all human representations is the elementary base to start with any more refined conceptual description. W e introduce the “evolutive information” concept. Evolutive information is an elusive idea whose specific and contingent understanding involves interdisciplinary, trans-disciplinary, cul­ tural and ontological multi-perspectives, to arrive to Cybersemiotics. To really understand evolutive information, we need to analyze the strong, resonant coupling between processes related to action and perception which emerges in the human brain as a consequence of learning sensorimotor task. To survive successfully the Fourth Industrial Revolution and to achieve an antifragile behavior, next generation human-made system must have a new fundamental component,

^emenT Vi ^ ^>ro^ essor ° f Bioengineering with specialties in Energy Conservation, M aníntelH11 * ' ^ “dimensional Signal Processing, Biology, Neuroscience, Computational ^atio^C 005 an ity and Quantity 32, 119-154 (1998). fornell 11. E. Hornung, Conceptions o f God in Egypt: The One and the ManyUniversity Press, Ithaca (1982). biolog' 12. F. Bailly, G. Longo and M. Montevil, A 2-dimensional geometry ical time, Progress in Biophysics and Molecular Biology /» ( 2 0 0 1 ).

Evolutive Information in the Anthropocene Era


13. R. A. Plutchik, A psychoevolutionary theory of emotions, Social Science Information 21(4 -5 ), 529-533 (1982). 14. P. Ekman, Are there basic emotions? Psychology Review 99(3), 550-553 (1992). 15. J. Vallverdú and D. Casacuberta, A computational, cognitive and situated framework for emotional social simulations, International Journal of Robotics Applications and Technologies 5(2), 1-14 (2017). 16. C. Roeser and T. Cain, Emotion and Valué. Oxford University Press, Oxford, UK (2014). 17. M. Bedke, Ethical intuitions: what they are, what they are not, and how they justify, American Philosophical Quarterly 45(3), 253-270 (2008). 18. A. Cullison, Moral perception, European Journal o f Philosophy 18(2), 159175 (2010). 19. R. C. Roberts, Emotions: An Essay in Aid o f Moral Psychology. Cambridge University Press, Cambridge (2003). 20. S. Roeser, Moral Emotions and Intuitions, Palgrave Macmillan, London ( 2011).

21. R. Barthes, Rhetoric of the image, in ed. C. Handa, Visual Rhetoric in a Visual World: A Critical Sourcebook, pp. 152-163, Bedford/St. Martin’s, New York (1964/2004). 22. R. Barthes, The rhetoric of the image, in ed. S. Heath, Image, Music, Text, pp. 32-51, Hill and Wang, New York (1977). 23. R. Arnheim, Visual Thinking, University of California Press, Berkeley, CA (1969). 24. J. Berger, Ways o f Seeing, Penguin, Harmondsworth (1972). 25. J. Piaget, Le Langage et la Pensée chez VEnfant, Delachaux et Niestlé, Neuchátel (1923). 26. J. Piaget, LTntelligence avant le Langage, Flammarion, Paris (1936). 27. L. S. Vygotsky, Storia dello Sviluppo delle Funzioni Psichiche Superiori, Giunti-Barbéra, Firenze (1931). 28. L. S. Vygotsky, Thought and Language, M IT Press, Cambridge, MA (1962). 29. L. S. Vygotsky, Mind in Society, Harvard University Press, Cambridge, MA (1978). 30. S. Dehaene, The Number Sense: How the Mind Creates Mathematics, Oxford University Press, New York (1997). S. Dehaene, N. Molko, L. Cohén and A. J. Wilson, Arithmetic and the ^ain, Current Opinión in Neurobiology 14, 212-224 (2004). 32. •Piazza, P. Pinel, D. L. Bihan and S. Dehaene, A magnitude code common nun*erosities and number symbols in human intraparietal cortex, Neuron 53, 293-305 (2007). 33. •Dehaene and E. Brannon (eds.), Space, Time and Number in the Brain: earching for the Foundations o f Mathematical Thought. Attention and



^er*es< Academic Press, Amsterdam (2011). Spatiai^aun’ M. Jordán, G. Vallortigara and N. S. Clayton, Origins of ck0jla ’ temPoral, and numerical cognition: Insights from comparative psy°gy, in eds. S. Dehaene and E. Brannon, Space, Time and Number



36. 37.


39. 40.

41. 42. 43. 44. 45.



48. 49. 50.


R. A . Fiorini

in the Brain: Searching fo r the Foundations of Mathematical Thought, pp. 191-206. Attention and Performance Series. Academic Press, Amsterdam (2011). E. L. Kaufman, M. W . Lord, T. W . Reese and J. Volkmann, The discrimination of visual number, The American Journal of Psychology 62 (4), 498-525 (1949). B. Butterworth, The Mathematical Brain, Macmillan, New York (1999). B. Butterworth, M. Cappelletti and M. Kopelman, Category specificity in reading and writing: The case of number words, Nature Neuroscience 4, 784-786 (2001). M. Piazza, A. Mechelli, B. Butterworth and C. J. Price, Are subitizing and counting implemented as sepárate or functionally overlapping processes? Neurolmage 15, 435-446 (2002). B. Butterworth, The development o f arithmetical abilities, Journal of Child Psychology and Psychiatry 46(1), 3-18 (2005). F. Krause, O. Lindemann, I. Toni and H. Bekkering, Different brains process numbers differently: structural bases of individual differences in spatial and nonspatial number representations, Journal of Cognitive Neurosciences 26 (4), 768-776 (2014). D. Sousa, Mind, Brain, and Education: Neuroscience Implications for the Classroom, Solution Tree Press, Bloomington, IN (2010). J. Halberda, Logic in babies, Science 359(6381), 1214-1215 (2018). P. M. V. Hiele, Structure and Insight: A Theory of Mathematics Education, Academic Press Inc., Cambridge, MA (1986). P. M. V. Hiele, Developing geometric thinking through activities that begin with play, Teaching Children Mathematics 5, 310-316 (1999). Y . Wamain, J. Tallet, P.-G. Zanone and M. Longcamp, Biological geometry perception: Visual discrimination of eccentricity is related to individual motor preferences, PLoS ONE 6(1), e l 5995 (2011). M. Riemer, N. Diersch, F. Bublatzky and T. Wolbers, Space, time, and numbers in the right posterior parietal cortex: Differences between response code associations and congruency effects, Neurolmage 129, 72-79 (2016)E. Y. Toomarian and E. M. Hubbard, O n the génesis of spatial-numerical associations: Evolutionary and cultural factors co-construct the men tal number line, Neuroscience and Biohehavioral Reviews 90, 184— (2018). M. L. von Franz, Number and Time, Studies in Jungian Thought, rio Western University Press, Evanston, IL, USA (1974). ^ j,$ Z. Radman (ed.), The Hand, an Organ o f the Mind: What the Manua the Mental, The MIT Press, Cambridge, MA (2013). for Y. Wang, On concept algebra: A denotational mathematical structure knowledge and software modeling, International Journal of Cognitive matics and Natural Intelligence 2(2), 1-19 (2008). ^ knowl' Y. Wang, On cognitive foundations and mathematical theories edge Science, International Journal of Cognitive Informatics a Intelligence 10(2), 1-25 (2016).

Evolutive Information in the Anthropocene Era


52. R. Audi, The sources of knowledge, in ed. P. Moser, The Oxford Handbook of Epistemology, pp. 71-94. Oxford University Press, New York (2002). 53. M. Ignelzi, Meaning-making in the learning and teaching process, New Directions fo r Teaching and Learning 82, 5-14 (2000). 54. T. Deacon, The Symbolic Species, W . Norton and Co., New York (1997). 55. J. Gillies, R. Neimeyer and E. Milman, The meaning o f loss codebook: Construction of a system for analyzing meanings made in bereavement, Death Studies 38(4), 207-216 (2014). 56. J. Habermas, Knowledge and Human Interests, 2nd edition, Heinemann, London (1978). 57. U. Wolf, M. J. Rapoport and T. A. Schweizer, Evaluating the affective component of the cerebellar cognitive affective syndrome, JNP The Journal of Neuropsychiatry and Clinical Neurosciences 21(3), 245-253 (2009). 58. M. Wheatley, Leadership and the New Science: Discovering Order in a Chaotic World, Berret-Koehler Publ. Inc., San Francisco, CA (2006). 59. H. I. Ansoff, Managing strategic surprise by response to weak signáis, Cal­ ifornia Management Review 18(2), 21-33 (1975). 60. R. Poli, Les signaux faibles, une propensión social spontanée, Cahiers de la sécurité 1, 28-32 (2013). 61. N. N. Taleb, Silent Risk, Lectures on Probability, Vol. 1, Des Cartes (2015). 62. R. A. Fiorini and G. Laguteta, Discrete tomography data footprint reduction by information conservation, Fundamenta Informaticae 1 2 5 (3 -4), 261272 (2013). 63. R. A. Fiorini, How random is your tomographic noise? A number theoretic transform (ntt) approach, Fundamenta Informaticae 1 3 5 (1 -2), 135170 (2014). 64. R. A. Fiorini, Computerized tomography noise reduction by cict optimized exponential cyclic sequences (oecs) co-domain, Fundamenta Informaticae 141(2-3), 115-134 (2015). 65- R. A. Fiorini, New cict framework for deep learning and deep thinking Application, International Journal o f Software Science and Computational Intelligence 8(2), 1-21 (2016). 66- Y. Wang, B. Widrow, L. A. Zadeh, H. Newton, S. W ood, V. C. Bhavsar, G. Budin, C. Chan, R. A. Fiorini, M. L. Gavrilova and D. F. Shell, Cognitive intelligence: Deep learning, thinking, and reasoning by brain-inspired Systems, International Journal of Cognitive Informatics and Natural Intel6? Ugence 10(4), 1-21 (2016). •Nicolescu, La transdisciplinarité, manifesté, in ed. J.-P. Bertrand, Col68 'Pransdisciplinarité, pp. 1-98, Édition du Rocher, Monaco (1996). •A. Fiorini. Transdisciplinary education for deep learning, creativity and p n°vation. In Rome Conference Proceedings, pp. 94-107, W AAS, W UC, 69 j ^ a ^ University, Rome, IT (2018). a H K. ^ or*nh GA and CICT for stronger arbitrary multiscale biomedical i°engineering Solutions, in eds. S. X. Descamps, J. P. Serra and R. G. UnVe\ ^ Proceedings of the AGACSE 2015 Conference, pp. 153-162, Versitat Politécnica de Catalunya, Barcelona, SP (2015).

R. A . Fiorini


70. R. A. Fiorini, Computational information conservation theory: An introduction, in eds. N. Mastorakis, M. Demiralp, N. Mukhopadhyay and F. Mainardi, 2 0 1 4 Proceedings of the 8th International Conference on Applied Mathematics, Simulation, Modelling (ASM ’1 4 ) , Vol. 34, Mathematics and Computéis in Science and Engineering Series, pp. 385-394, WSEAS Press, Florence (2014). 71. B. Hommel, Acquisition and control of voluntary action, in eds. S. Maasen, W . Prinz and G. Rothin, Voluntary Action: Brains, Minds, and Sociality, pp. 34-48, Oxford University Press, New York (2003). 72. G. Rizzolatti, L. Fadiga, V. Gállese and L. Fogassi, Premotor cortex and the recognition of motor actions, Cognitive Brain Research 3(2), 131-141 (1996). 73. G. Rizzolatti and L. Craighero, The mirror-neuron system, Annual Review o f NeuroScience 27, 169-192 (2004). 74. G. Rizzolatti and C. Sinigaglia, The functional role of the parieto-frontal mirror circuit: interpretations and misinterpretations, Nature Reviews Neuroscience 11, 264-274 (2010). 75. C. W oods (ed.), Visible Language — Inventions of Writing in the Ancient Middle East and Beyond, Oriental Institute Museum Publications, Vol. 32. The Oriental Institute of the University of Chicago, Chicago, IL, USA ( 2 0 10 ).

76. 77.

78. 79. 80.

81. 82. 83.


G. Deutscher, Syntactic Change in Akkadian: The Evolution of Sentential Complementation, Oxford University Press, New York (2007). C. Woods, Bilingualism, scribal learning, and the death of sumerian, in ed. S. Sanders, Margins o f Writing, Origins o f Culture, pp. 91-120, The Oriental Institute of the University of Chicago, Chicago, IL (2006). A. Cotterell (ed.), Penguin Encyclopedia of Ancient Civilizations. Penguin Books, New York (1980). R. Mattessich, The oldest writings, and inventory tags of egypt, Accounting Historians Journal 29(1), 195-208 (2002). Panini and S. C. Vasu. Asthádyáyi, vedic books, 2 volumes (1993). https. / /w w w . ayi-2-vol-p-1300.html. F. Staal, The Science of language, in ed. G. Flood, The Blackwell Compasión to Hinduism. Blackwell Publishing, Hoboken, NJ (2003). , W . H. Baxter and L. Sagart, Oíd Chinese: A New Reconstruction. Oxfor University Press, New York (2014). R. Lee, P. Jonathan and P. Ziman, Pictish symbols revealed as a language through application of Shannon entropy, Proceedings of the 0 Society A 466, 2545-2560 (2010). ? ^ L. Fortunati, Is body-to-body communication still the prototypeInformation Society 21, 53-61 (2005). https://pdfs.semanticscholar.°

b332/c5f 7b3c09dedf45d485cb2a35e4d42428924.pdf. bergí 85. S. Hall, Ideology and communication theory, in eds. B. Dervin, L. Ur ^ ^ B. O ’Keefe and E. Wartella, Rethinking Communication Theory, 0 * 40-52, Sage, Newbury Park, CA (1989). 86. T. Hall, The Hidden Dimensión. Anchor Books, New York (1966)-

Evolutive Information in the Anthropocene Era


87. B. Wellman, Physical place and cyberplace: The rise of personalized networking, International Journal o f Urban and Regional Research 25(2), 227-252 (2001). 88. P. Watzlawick, J. Beavin and D. Jackson, Pragmática Della Comunicazione umana. Astrolabio, Roma (1971). 89. A. Giddens, Social Theory and M odem Sociology, Polity Press, Cambridge (1987). 90. H. K. Tucker, Anthony Giddens and M odem Social Theory, Thousand Oaks, London (1998). 91. A. Giddens, The Constitution o f Society, Polity Press, Cambridge (1984). 92. L. Corchia, Explicative models of complexity. The reconstructions of social evolution for Jürgen Habermas, in eds. S. Balbi, G. Scepi, G. Russolillo and A. Stawinoga, Book of Short Abstracts, 7th International Conference on Social Science Methodology RC33 Logic and Methodology in Sociology , pp. 76-77, Jovene Editore, Napoli (2008). 93. W. Nagan and A. M. Haddad, Aesthetics and human rights, ExpressO (2012), http://w /w inston_nagan/12/. 94. G. Dorfles, Horror Pleni - La (In)Civilth del Rumore. Castelvecchi, Roma, IT (2008). 95. R. Pfeifer, J. Bongard and S. Grand, How the Body Shapes the Way We Think: A New View o f Intelligence, M IT Press, Cambridge, M A (2007). 96. L. Shapiro, The embodied cognition research programme, Philosophy Compass. 2(2), 338-346 (2007). 97. H. F. Mallgrave, Embodiment and enculturation: the future of architectural design, Frontiers in Psychology 6, 1-5 (2015). 98. R. Stam, Film Theory, Blackwell, Oxford, UK (2000). 99. L. Hjelmslev, Prolegomena to a Theory o f Language, University of Wisconsin-Madison, Wisconsin, W I (1961). 100. J. Deely, Four Ages o f Understanding: The First Postmodern Survey of Philosophy from Ancient Times to the Turn o f the Twenty-First Century , University of Toronto Press, Torontopoli, CAN (2001). líf ^ ^ewis, Counterfactuáis, Blackwell, Oxford, UK (1973). • M. Massimi, Laws of nature, natural properties, and the robustly best sys10

tem’ T h e M o n i s t 1 0 0 >406-421 (2017). Bco> A Theory o f Semiotics, Macmillan, London, UK (1976). Caesar, Umberto Eco: Philosophy, Semiotics and the Work o f Fiction ,



íley’ NeW Y° rk’ NY ( 19" ) ‘ K. Ogden and I. A. Richards, The Meaning o f Meaning: A Study of e Influence of Language upon Thought and o f the Science o f Symbolism , 106. p°^tledSe and Kegan Paul, London (1923). • •M. Seuren, Aristotle and linguistics, in ed. K. Brown, Encyclopedia of oaT a*e Ün^ ^ n 3 u^s ^ c s ^ PP- 469-471, Elsevier, Oxford (2006). 108. y j Holmes> Noble State bank v. haskell. 219 U .S . 104 (1911). tion W* and ^ ewson’ Chomsky’s Universal Grammar: An Introduc* Wlley-Blackwell, Hoboken, NJ, 3rd edition (2007).





111 . 112 .

113. 114. 115.


117. 118. 119.

120. 121. 122.


124. 125. 126.

R. A . Fiorini

R. V. Solé and L. F. Seoane, Ambiguity in language networks, The Linguistic Review 32(1), 5-35 (2015), https://w w w .degruyter.eom /view /j/tlir.20 15.32.issue-l/tlr-2014-0014/tlr-2014-0014.xml. R. V. Solé and L. F. Seoane, Ambiguity in language networks, SFI WORKING PAPER. 2 0 1 4 -0 4 -0 0 7 (2014), sults / working- papers / ambiguity- in- language- networks. B. Partee, A. Meulen and R. Wall, Mathematical Methods in Linguistics, Pallas Paperbacks Springer, The Netherlands (1990). T. K. Landauer and S. T. Dumais, A solution to plato’s problem: The latent semantic analysis theory o f acquisition, induction and representation of knowledge, Psychological Review 104(2), 211-240 (1997). H. Schütze, Automatic word sense discrimination, Computational Linguis­ tics 24(1), 97-123 (1998). D. Crystal, Linguistics, Penguin Books, New York (1990). A. Martinet, Elements of General Linguistics. Studies in General Linguis­ tics, Vol. I, translated by Elisabeth Palmer Rubbert. Faber, London, UK (1960). B. Rens, A New History of the Humanities: The Search fo r Principies and Patterns from Antiquity to the Present, Oxford University Press, Oxford (2014). S. C. Vasu. The Asthadyáyi of Panini, 2 volumes, Vedic Books (1996), h ttps://w w w .vedicbooks.n et/. T. Parson. The traditional square of opposition, Stanford Encyclopedia of Philosophy (1997/2017), B. Inhelder and J. Piaget, De la Logique de VEnfant a la Logique de VAdolescent. Presses Universitaires de France, Paris (1955). M. Seltman, PiageVs Logic. Routledge, New York (2013). S. Robert and J. Brisson, The klein group, squares of opposition and the explanation of fallacies in reasoning, Lógica Universalis 10, 377-392 (2016/ R. A. Fiorini, Would the big government approach increasingly fail to lead to good decisión? a solution proposal, Kybernetes 46(10), 1735-1752 (2017)? http:/ / f u ll/10.110 8 /K - 01- 2017- 0013. R. A. Fiorini, Logic and order: Ontologic effective management for learn ing and creativity, in ed. J. Home, Philosophical Perceptions on Logic a Order, Chapter 11, pp. 283-351, IGI Global, Hershey, PA (2017). R. L. Ackoff, From data to wisdom, Journal o f Applied Systems Ana ys 16, 3-9 (1989). .ñc(¡, M. Burgin, Theory of Information: Fundamentality, Diversity and u^J1 tion, World Scientific, Singapore (2010). C. E. Shannon, A mathematical theory of communication, Bell SysK0

Technical Journal 27(3), 379-423 (1948). iforthe 127. Y . Bar-Hillel and R. Carnap, Semantic information, British Journa Philosophy of Science 4, 147-157 (1958). qqxci128. D. M. MacKay, Information, Mechanism and Meaning, MIT PresS’ 129.

bridge, MA (1969). Wvdawnic^8 M. Mazur, Qualitative Theory of Information, Panstwowe w y Techniczne, Warsaw (1970).

Evolutive Information in the Anthropocene Era


J. Hintikka, On defining information, Ajatus 33, 271-273 (1971). A. V. Chechkin, Mathematical Informatics, Nauka, Moscow (1991). L. Floridi, Open problems in the philosophy of information. In The Herbert A. Simón Lecture on Computing and Philosophy, CAP Meeting, Carnegie Mellon University, PA (August, 2001). 133 L. Floridi, What is the philosophy of information, Metaphilosophy 33, 123145 (2002). 134. K. Wu, Philosophy of Information: Theory, Method and System, The Commercial Press, Beijing (2005). 135. G. Dodig-Crnkovic and M. Burgin, Information and computation: Essays on Scientific and Philosophical Understanding of Foundations of Information and Computation, World Scientific Publishing, Singapore (2011). 136. M. J. Schroeder, Concept of information as a bridge between mind and brain, Information 2(3), 478-509 (2011), 9/2/3/478/. 137. M. Burgin, The general theory of information as a unifying factor for infor­ mation studies, MDPI Sciforum (2017),! S4SI- 2017/paper/4044/download/pdf. 138. L. Seoane and R. V. Solé, Information theory, predictability and the emergence of complex life, Royal Society Open Science 5(172221), (2018), http: / / / royopensci /5 /2 /1 72221 .full. pdf. 139. N. N. Taleb and R. Douady, A Mathematical Formulation of Fragility. PeerReviewed Monographs, Des Cartes (2015). 140. J. Vallverdú, Bayesians Versus Frequentists, Springer, Berlin, (2016). 141. K. Schwab, The Fourth Industrial Revolution: What It Means, How to Respond: Foreign Affairs, Lightning Source, Inc., LaVergne, TN (2015), olution. 142 R. A. Fiorini, Empowering cognition by precisation of numeric words, Inter­ national Journal of Software Science and Computational Intelligence 9(4), 1-18 (2017), numeric- words/197782. 143. R- A. Simón, The Sciences of the Artificial, MIT Press, Cambridge, MA (1981) . 144 R- A. Simón, Models of Bounded Rationality, MIT Press, Cambridge, MA (1982) . 145 S- Russell and P. Norvig, Artificial Intelligence: A Modern Approach, Prentice-Hall, Upper Saddle River, NJ (2010). 146 . ‘ Gao and Q. Cai, Spontaneous creation of the universe from noth147 l^ Physical Review D 89(083510), (2014). •Freitas, Power law expansión of the early universe for a v(a) = kan 148. R E N^’ M°dern PhVsics Letters A 33(1) (2018). Difp0„ Geo9raphy of Thought: How Asians and Westerners Think Pifferen tly and Why. Free Press (Simón and Schuster, Inc.), New York (2003).

130 131 132



an Rethinking extrasensory perception: Toward ,lc model of precognition, S A G E O p e n 5(1), 1-17 (2015).


R. A . Fiorini

150. E. C. May and S. B. Marwaha (eds.), The fundamentáis of psi, in Extrasensory Perception: Support, Skepticism, and Science, Volume I: History, Controversy, and Research, pp. 1-31. Praeger Publications, Santa Barbara, CA (2015). 151. S. B. Marwaha and E. C. May, Precognition: the only form of psi? Journal of Consciousness Studies 23(3-4), 76-100 (2016). 152. T. Deacon, Incompleto Nature: How Mind Emerged from Matter, W. Norton and Company, New York, NY (2011). 153. G. Bateson, Steps to an Ecology of Mind: Collected Essays in Anthropology, Psychiatry, Evolution and Epistemology. University of Chicago Press, Chicago, IL (1972). 154. A. Korzybski, Chapter IV: On structure, in ed. C. Schuchardt Read, Sci­ ence and Sanity: An Introduction to Non-Aristotelian Systems and General Semantics, pp. 55-64, CD rom edition, Brooklyn, NY, USA (1996). 155. E. T. Bell, Numerology: The Magic of Numbers, Williams and Wilkins, Baltimore, ML (1933). 156. K. Koch, J. McLean, R. Segev, M. A. Freed, M. J. B. II, V. Balasubramanian and P. Sterling, How much the eye tells the brain, Current Biology. 16(14), 1428-1434 (2006). 157. T. D. Wilson, Strangers to Ourselves: Discovering the Adaptive Unconscious, Belknap Press, Cambridge, UK (2004). 158. M. Zimmermann, Neurophysiology of sensory Systems, in ed. R. F. Schmidt, Fundamentáis of Sensory Physiology, pp. 68-116. Charlotte, SC (1986). 159. W. J. Freeman and R. Kozma, Scale-free cortical planar networks, in Handbook of Large-Scale Random Networks, Vol. 18, Bolyai Society of Mathematical Studies, pp. 277-324. Springer, Berlin (2009). 160. R. Espejo and A. Reyes, Organizational Systems: Managing Complexity with the Viable System Model, Springer, Heidelberg (May 2011). 161. W. Whewell, The Philosophy of the Inductive Sciences, Founded Upon Their History. John W. Parker, London, (two volumes) (1840). 162. E. O. Wilson, Consilience: The Unity of Knowledge, Alfred A. Knopf, New York (1998). 163. A. N. Whitehead, An Introduction to Mathematics, Williams and Northgate, London (1911). 164. S. Lupasco, Le Principe d’Antagonisme et la Logique de Ténergie, 2nd e i tion, Le Rocher, Paris (1987). 165. R. A. Fiorini, Cict: New eyes on computational competence computational Science, ITM Web of Conferences 16, 01007 (2 ’ amcse2018_01007.pdf. m 166. R. A. Fiorini, Strumentazione Biomedica: Sistemi di Supporto CUSL, Collana Scientifica, Milano (1994). ^6 167. Z. Radman, Towards aesthetics of Science, A e s t h e t ic s 29-3 , (2004/05). dtbe 168. X. Huang and J. P. Saint-Jeannet, Induction of the neural ere opportunities of life on the edge, Development Biology 275, VAX

Evolutive Information in the Anthropocene Era


N. M. L. Douarin, The avian embryo as a model to study the development of the neural crest: a long and still ongoing story, Mechanisms of Development 121, 1089-1102 (2004). 170. S. Hórstadius, The Neural Crest: Its Properties and Derivatives in the Light of Experimental Research, Oxford University Press, London (1950). 171. T. Sauka-Spengler, D. Meulemans, M. Jones and M. Bronner-Fraser, Ancient evolutionary origin of the neural crest gene regulatory network, Developmental Cell 13, 405-420 (2007). 172. R. A. Fiorini, Sanitá 5.0 — La Visione Evolutiva. CUSL, Collana Scientifica, Milano (2010). 173. S. E. Petersen, H. van Mier, J. A. Fiez and M. E. Raichle, The effects of practice on the functional anatomy of task performance, Proceedings of the National Academy of Sciences 95(3), 853-860 (1998). 174. J. A. Bargh, The cognitive monster: The case against the controllability of automatic stereotype effects, In eds. S. Chaiken and Y. Trope, DualProcess Theories in Social Psychology, pp. 361-382. Guilford Press, New York (1999). 175. R. R. Hassin, J. A. Bargh and S. Zimerman, Automatic and flexible: the case of nonconscious goal pursuit, Social Cognition 27(1), 29-36 (2009). 176. M. T. H. Chi, Two approaches to the study of experts characteristics, In eds. K. A. Ericsson, N. Charness, P. J. Feltovich, and R. R. Hoffman, The Cambridge Handbook of Expertise and Expert Performance. Cambridge Uni­ versity Press, Cambridge (2006). 177. S. Lewandowsky and J. L. Thomas, Expertise: Acquisition, limitations, and control, Reviews of Human Factors and Ergonomics 5(1), 140-165 (2009). 178. M. Keestra, Drawing on a sculpted space of actions: Educating for expertise while avoiding a cognitive monster, Journal of Philosophy of Education 51 (3), 620-639 (2017). 179. H. Spemann. The organizer-effect in embryonic development, The Nobel Prize Lecture in Physiology or Medicine 1935 (1935), https://www.vedicb 1300.html. 180. A. G. Gurwitsch, Über die nichtmateriellen factoren embryonaler formgestaltung, Zeitschrift filr Morphologie und Anthropologie 18, 111-142 (1914). 18 1 . H. Fróhlich, The connection between macro- and microphysics, Rivista del Nuovo Cimento 3, 490-534 (1973). 182. R- H. Abraham, Vibrations and the realization of form, In eds. E. Jantsch ^nd C. H. Waddington, Evolution and Consciousness, Addison-Wesley, Reading, MA (1976). 183. •D- Giudice, S. Doglia and M. Milani, A collective dynamics in metabolJ C 184. a[¡/_ active cells, Physica Scripta 26, 232-238 (1982). fyn, T. Y. Kanno, A. Ruzo, E. D. Siggia and A. H. Brivanlou, Selfganization of a human organizer by combined wnt and nodal signalling, 132-135 (2018), (doi:10.1038/s41586-018-0150-y), https://ww

16 9 . /articles/s41586-018-0150-y.


R. A . Fiorini

185. G. West, Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies. Penguin, New York, NY (2017). 186. J. Law and J. Hassard, In eds. J. Law and J. Hassard, Actor Network Theory and After. Oxford and Keele, Blackwell and the Sociological Review, Oxford (1999) . 187. B. Latour, Reassembling the Social: An Introduction to Actor-NetworkTheory. Oxford University Press, Oxford (2005). 188. A. Yaneva, Making the social hold: Towards an actor-network theory of design, Design and Culture 1(3), 273-288 (2009). 189. N. Carroll, Actor-network theory: A bureaucratic view of public Ser­ vice innovation, in Technological Advancements and the Impact of ActorNetwork Theory, pp. 115-144, IGI Global, Hershey, PA (2014). 190. B. Latour, Science in Action: How to Follow Scientists and Engineers Through Society, Open University Press, Milton Keynes (1987). 191. E. Cudworth and S. Hobden, Of parts and wholes: International relations beyond the human, Millennium: Journal of International Studies 41(3), 430-450 (2013). 192. G. Longo, Interfaces of incompleteness, La Matemática 4 (2010), http:// pdf. 193. B. L. Whorf, Language, Thought and Reality, John Wiley & Sons, Hoboken, NJ (1956). 194. P. J. Crutzen and E. F. Stoermer, Anthropocene, IGBP Newsletter 41, 12

( 2000 ) . 195. A. Dawson, Extinction: A Radical History, OR Books, New York (2016). 196. C. S. M. Turney, J. Palmer, M. A. Maslin, A. Hogg, C. J. Fogwill, J. Southon, P. Fenwick, G. Helle, J. M. Wilmshurst, M. McGlone, C. B. Ramsey, Z. Thomas, M. Lipson, B. Beaven, R. T. Jones, O. Andrews and Q. Hua, Global peak in atmospheric radiocarbon provides a potential definition for the onset of the anthropocene epoch in 1965, S c ien tific Reports 8, 3293 (2018), 197. R. A. Fiorini. The wellbeing society, the new economy? In Proc. Agenda 2030: Economies in a Changing World, The First International Scientific Conference on Economies in a Changing World, Experimental Economies Lab, Umag, Croatia (August, 2017). 198. B. Nicolescu, Levels of complexity and levels of reality, in ed. B. The Emergence of Complexity in Mathematics, Physics, Chemistry, ^ Biology. Proceedings of the Plenary Session of the Pontifical Academy^y Sciences, Casina Pió IV. Pontificia Academia Scientiarum, Vatican Vatican (27-31 October 1992). 199. K. Marx, Das Kapital I. Dietz, Berlin (1971). of Work tn 200. H. Braverman, Labor and Monopoly Capital: The Degradation (1974). the Twentieth Century, Monthly Review Press, New York, NY

Evolutive Information in the Anthropocene Era'


201. L. Leydesdorff, Synergy in knowledge-based innovation Systems at national and regional levels: The triple-helix model and the fourth industrial revolution, Journal of Open Innovation: Technology, Market, and Complexity 4 (2) (2018). 202. Y. Wang, On the cognitive and theoretical foundations of big data Science and engineering, New Mathematics and Nature Computation 13(2), 101117 (2017). 203. Y. Wang, Big data algebra: A rigorous approach to big data analytics and engineering, Keynote Speech: 17th Int. Conference on Mathematical

and Computational Methods in Science and Engineering (MACMESE ’15) 204.

205. 206. 207. 208.

(April 23-25, 2015). Y. Wang, Big data algebra (bda): A denotational mathematical structure for big data Science and engineering, Journal of Advanced Mathematics and Applications 5, 3-25 (2016). A. Zucconi, The need for person-centered education, Cadmus 3(1), 1-26 (2016). W. P. Nagan, The concept, basis and implications of human-centered development, Cadmus 3(1), 27-35 (2016). M. Hytten. Instinctively sustainable. white paper on sustainability Commu­ nications (2017), http://w w w .m /hom e. M. C. Bateson, Composing a Further Life: The Age of Active Wisdom, Vintage, New York (2011).

Chapter 11

Computationalism in a Dynamic and Distributed Eco-cognitive Perspective L orenzo M agnani

Department of Humanities, Philosophy Section, and Computational Philosophy Laboratory, University of Pavía Piazza Botta 6, 27100, Pavía, Italy [email protected] it The concepts of information, computation, and cognition are variously interpreted and explained, and still lead to ambiguous results. I will contend that seeing the evolutionary emergence in humans of information, meaning, and of the first kinds of cognition as the outcome of dynamic coevolutionary interactions between brain/m ind internal processes, body itself, and external environment can be extremely useful (1) to clarify the most common misunderstandings and the basic vagueness of the concepts above, and (2) to appropriately describe “computation” as an evolving concept subjected to continuous transformations of meaning. To this aim, I will also take advantage of the dynamic concepts of salience and pregnance derived from T h o m ’s catastrophe theory. When physical computation is seen in the perspective of the ecology of cognition, it is easy to understand Turing’s original ideas concerning the emer­ gence of information, cognition, and computation in organic, inorganic, and artefactual agents, I will also briefly illustrate in this chapter. I will show that seeing computation as dynamically active in distributed physical entities of vartous kinds suitably transformed so that data can be encoded and decoded to ain aPPropriate results further sheds light on what I cali eco-cognitive comdoest*°Ila^Sm’ * k°P e it will become clear that eco-cognitive computationalism 0f • fnot a*m at furnishing an ultimate and static definition of the concepts inst e ^ ma^ on’ cognition, and computation, such as a textbook could provide, pr0pos ^ *ntends, by respecting their historical and dynamical character, to form 0

f^ 11 lnte^ectual framework that depicts how we can understand their emergence” and the modification of their meanings.



1. 1.1.

L. Magnani

Introducing Eco-cognitive Computationalism Eco-cognitive computationalism

What I cali Eco-cognitive Computationalism sees computation as active in physical entities suitably transformed so that they become what I cali cognitive mediators in which data can be encoded and decoded to obtain fruitful results. We have to immediately say that eco-cognitive computa­ tionalism, even if considers cognition as computational, does not reduce computation to digital computation (that is to the processing of strings of digits according to rules).a When physical computation is seen in the perspective of the ecology of cognition it is easy, first of all, to understand the relationships between information, cognition, and computation taking advantage of the dynamic concepts of salience and pregnance derived from Thom ’s catastrophe theory,b but also the deep meaning of Turing’s original ideas concerning the emergence of information, cognition, and computation in organic, inorganic, and artefactual agents, I will illustrate in this article. I hope it will become clear that eco-cognitive computationalism does not aim at furnishing an ultimate and static definition of the concepts of information, cognition, and computation, such as a textbook could provide, instead it intends, by respecting their historical and dynamical character, to propose an intellectual framework that depicts how we can understand their forms of “emergence” and the modification of their meanings. Some preliminary explanations concerning Turing’s concepts I will illus­ trate below in this article have to be provided. First of all, Turing’s speculations on how the so-called “unorganized brains” c are transformed m organized “machineries” are very important. Turing says that brains are continuous systems that can be treated as discrete systems able to perform “discrete” computations, so that we can describe the possible States of these brains as discrete sets, with the motion occurring by jumping from one state

aIt is well known that this view is instead consistent with the classical view of cogn as the manipulation of linguistic/sentential entities. . events b Catastrophe theory is a branch of mathematics that uses topology to exp (such as a volcano eruption) characterized by very sudden changes in behavior ^ ^ from relatively small changes in circumstances. It is part of bifurcation area of research on dynamical systems. at the end cMore details about this concept proposed by Turing are illustrated belo > of this section.

Computationalism in a Dynamic and Distributed Eco-cognitive Perspectiva


to another.d In this perspective we have to observe that brains are complex Systems (organs) with many arbitrary multi-scale levels of description and representation. To avoid ambiguities in my use of the Turing’s concepts of discreteness and continuity it is better to explain the meaning in this context of the adjective “continuous” : Turing himself understands that the nervous system is surely not a Discrete-State Machine (DSM) that is, in modern terminology, the brain rather could be better described as a kind of dynamical system that is sensitive to initial or limit conditions, more com­ plex than any n-body physical system or turbulent stream. Turing calis a system such as this one “continuous” both in his 1950 paper [1] and in his 1952 paper [2] on morphogenesis (see [3, p. 380]).e Moreover, to also better clarify the concept of discreteness, we have to say that since Turing Computer Science suggests a perspective in which phys­ ical artefactual entities are “domesticated” to process the organization of information and knowledge into little boxes, bits and pixels, which present discrete precisión (each datum is well separated and accessible and each measure exact, in contrast to what happens for all — classical — physical processes), exactly, with no fuzziness and no contingency. We know that in chaotic deterministic systems, a fluctuation/variation below the interval of measurement induces radically different evolutions for the system. This, as Turing observed in the 1950s, is theoretically avoidable in the DSM he had invented and as he named it in those years (and such is also the case in practice). We also know that the Turing machine is an abstract

Turing adds that all machines can be also considered as continuous (where the States constitute a continuous manifold and the behavior of the machine is depicted by a curve manifold). He also calis controlling machines the ones that only deal with informa! DJn^ active the machines that aim at generating some macroscopic physical effects: a bulldozer Brain .1S a cont^nuous and active machine, a telephone continuous and controlling. ^ains, Turing says, can be conceived as machines and they are “probably” — continuous “very similar to much discrete machinery” (see [5, p. 5]).

ical s

Ur^ er °bserves: “Note that we are not claiming here that the brain is a dynamsystem F \ a^S° re^ers to the brain as, at least, a dynamical, highly sensitive, Verystable ^ ^is imaSe> take a turbulent system that is at the same time between d ' f F V6r^ unstable, very ordinate and very inordinate; insert it sandwich-style then havp1 Grent *eYels of organization that regúlate it and that it integrates. You will Material ^ °f the cognit' ^

Pbysical image of a biological entity. Am ong these entities, quite an . which is at the origin of the dominant distributed character draUniari C0^n^ orb as I will illustrate in Section 2.4. The emergence of j1Umln^ anc^ writing is certainly related, as Longo [4] maintains, to the an ev°lution to alphabetic natural language.

^^ntage of th ~ * *aic sem^"encaPsu^ateci character of cognition can be found taking ;ii mle e sev< **i°ns, as, illi,e+Lfnf, l^S^s ^ t^ several cultural forces that also transform cognitive ‘ Ulustrated by Nisbett [21].



L. Maguará

Pregnances and paniformationalism

Pregnances, phenomena that can be either biological or physical, are in turn, Thom says, “non-localized entities emitted and received by salient forms” (see [22, p. 16]). Two clear examples can be given. The first one refers to natural phenomena: (1) an infection is a pregnance (mediated by a virus, that is a material/biological médium) that affects healthy subjects, who are the invested saliences that in turn can re-emit that same contagión as a pregnance into the natural niche (in which, in turn, other media such as air or blood are the transmitters). In this first case it seems weird to contend that information is at play, even if in the literature there is even an all-encompassing notion of infor­ mation, a kind of paninformationalism, in which physical (or biological) information is extrapolated to every state of a physical (or biological) Sys­ tem which is delineated as an information-carrying state [23,24]. I am not inclined to follow this perspective in the case of the analysis given in this paper, because I prefer to see information always referred to a biological or artefactual agent that “selects” it as such in the multiplicity of environmental events.n The second example is related to not merely physical but also clear “cognitive” activities, in the case of some animáis: (2) worker honeybees communicate with each other thanks to the signs embedded in the iconic movements expressed by a dance, which represent the pregnance that indicates the site where the insects have found food in order to “inform” the other cospecific individuáis — that is the invested salience — about the location. Here, the médium of the pregnance is the air that carries/transmits the ondulatory sounds and the light signáis to the aim of generating a neurobiological effect at the destination, that is, something similar to what we humans cali a “psychic” event. ^ In this second case we can contend that some transmission information is at play, but also of cognition: after all, in animáis the exis tence of a representation-oriented behavior can be postulated, where non linguistic pseudothoughts drive a plástic model-based “cognitive” activity

____________________________________________ ample í25’ nI am not undervaluing here the many excellent results that physicists (for exa^uantuni 26]) and logicians have reached, providing mathematical frameworks for seeing theory in the perspective of the principies of information processing. My ° n does not concern these results but the possible abuse of the notions of inforrn^^ ¡n [3,^' computation) in physics and biology, a problem extensively illustrated in ® to word orvrrn i+inn roforo ViQ+ are nrP not TlOt neCeSS , °In this case the cognition refers to nrní'nccDc processes + that neceSL .tuations,1 but also fruit of learning and productive activities, appropriate to certain

Computationalism in a Dynamic and Distributed Eco-cognitive Perspective


Obviously, also salient forms rooted in instinctual wired behavior channel “biological significance” (and consequently can be considered carriers of cognition), for example a prey for the aggressive predator, or the predator for its prey: salient forms of this type are called pregnant. In terms of abductive cognition we can say that a pregnant input is cognitively highly diagnostic and a trigger to start abductive production of hypotheses: Charles Sanders Peirce already observed that in the case of a chicken which perceives the hardwired pregnance of food, the instinctual hypothesis concerning its eatability is immediately formed. 2.3.

The emergence o f Information

At this point, a solution to the conundrum of the emergence of information and cognition can be found, taking advantage of our evolutionary and naturalistic perspective, influenced by the semiophysical perspective derived from Thom’s catastrophe theory. It is important to analyze this kind of solution because we will have to compare it to the process of the emergence of computation, I will illustrate in Section 3. Not only, my view of the intertwining between information, cognition, and computation will become clear when in Section 3.1, I will delinéate the concept of mimetic mind. Pregnances, and the information and cognition they embed, can be abductively activated, as I have illustrated in previous sections, but also created for the first time. A simple example is of help: when bell ringing is reiter­ a d often enough together with the exposition of a slice of meat to a dog, Pavlov’s conditioning process explains that the nutritive pregnance of meat ls disseminated in the environment by contiguousness to the salient auditory form. What happens? The salient form, in this case the sound of the bell, which is also an information spread in the environment, is invested with the pregnance of the meat. Now the cognitive endowments of the dog are enriched by a new aspect: the “information” carried by the bell (referring 0 the possibility of eating) now is endowed with a new created meaning for th.e ^°,a S0Unc^ we can course consider a sign, in semiotic terms) animal agent. The information, already salient before, now is also fluid119^11^ ^ meaninS- Thom adopts the exoteric image of an invasive sive flu d^ USe^ clu°t;e: “So we can look on a pregnance as an invaform sPreading through the field of perceived salient forms, the salient cting as a ‘fissure’ in reality through which seeps the infiltrating

°fthe dancp ?1,!Tlamina^s to bacteria — precisely learn and produce, such as in the case 0t the honeybees.


L. Magnani

fluid of pregnance” ([22, p. 7]).p Of course the pregnance can be reinforced through repetition and/or similarity and step after step the bell — in the new formed cognitive features belonging to the “psychism” of the dog — will refer solidly to the meat.q 2.4.

Extem al artifacts, extem al representations and the emergence o f cognition

I have said in Section 2.1 that signs can be externalized in both natural and artefactual environment, for example in drawing and writing, giving rise to that process of externalization of the mind (or disembodiment of the mind), which is at the origins of the dominant distributed character of human cognition. In Section 3 , 1 will show that Turing is perfectly aware of the fact [5] that a big cortex can furnish an evolutionary advantage when is accompanied by a great quantity of relevant information and knowledge already stored in external props; only suíflciently evolved human collectives can have at their disposal these storages, such as data from paleoanthropology seems to teach [29,30]. Indeed, storing in the external environment signs and drawings, and manipulating external entities transforming them in artifacts, is the main process that characterizes the birth of the so-called material culture (related to the construction of the first handaxes, about 1.4 million years ago, the birth of what Mithen also classifies the “technical intelligence” of the primitive human mind). It is important to stress that, already at these early stages of human evolution, cognition is distributed, at the same time it is a process of delegation of “information” to external tools, props, and devices and the starting of an activity of rich semiosis. Not only, Mithen observes that “The clever trick that humans learnt was to disembody their minds into the material world around them: a lingüista utterance might be considered as a disembodied thought. But such utter anees last just for a few seconds. Material culture endures” ([30, P- 29 \r We can conclude saying, according to recent intellectual research in cogn1 tive Science [31], that minds are “extended” and artificial in themselves. e can say that in a certain sense, through the processes I have just ske

pTo describe the emergence of pregnances Thom adopts the Pavlovian P ^ ^ ^ in g Other perspectives take advantage of Hebbian [27] and other more adequate principies and models, cf. for example [28]. related to qO f course, the cognitive aspeets are extremely dynamic because they arJ.gtant frofli pregnances that can also vanish when reinforcement is no more possible, ,s°tedbyan°thef the organism at play, or when, given this absence, the salient form is intere (eventually new) pregnant form.

Computationalism in a Dynamic and Distributed Eco-cognitive Perspective


human primitive brains become a sort of universal “intelligent” machines endowed with a rich activity of conseiousness. It is also important to stress that the reference to the role of external representations and to the disembodiment of the mind is able to account in a very satisfactory way central dynamic aspects of human cognitive processes. So to speak, brains/minds “extend” themselves in the external world to the aim of semiotically representing signs, words, icons, drawings in rocks, boards, sheets of paper, materials of various type, also to the aim of using them as anchors for helping to generate new thoughts, ideas, and concepts that do not have a “natural home” internally, within them. New information and new knowledge are usually produced inside this distributed process of semiotic activity/


The Emergence of Computation


Turing on the emergence o f information, cognition, and computation in organic, inorganic, and artefactual agents

The birth of computation is strictly related — in Turing’s seminal work Intelligent Machinery (1948) — to heuristic cognitive processes that take advantage of the study of the role in the external environment of organic bodies, physical entities, and artefacts. Reflecting upon the possibility of constructing intelligent machines, Turln§ immediately says that human intelligence can be produced only if a suitable education is performed ([5, p. 3]) and indicates an analogy between human brains (that is organic entities) and computational machines (that ls Physical artefactual entities). He proposes the concept of unorganized Machine and provides the example of the infant human cortex, which is a natural” organic entity that can be educated by means of “rewards and Pnnishments” . Together with unorganized machines Turing also lists paper Machines (see Section 3.2) and the two famous new fundamental kinds machineries he invents: the ( Universal) Logical Computing Machines

growth o f ^ f *s b^ther interested in this activity of emergence and subsequent to hypoth y 0rrnat*on and knowledge in this distributed perspective and with reference *xternal re reason*nS can see chapters two and three of my book [9]. The role of ^ifacts is^ ,eSenta^ ons and of the related delegations of cognition to external tools and ^ ropol0gicaj t rated taking advantage of examples coming not only from the paleoan-

ltl *he case of

U 1GS C0ncerning the cognitive processes of the primitive mind but also ^athematical and scientific knowledge.


L. Magnani

(LCMs),s which are considered abstract discrete machines, and the ( Universal) Practical Computing Machines (PCMs), which are machines in so far as they are external physical entities (inorganic and “artefactual” ) that manage their saved information in a form very dissimilar from the tape form, but that reflect the fact that “ [...] given any job which could have be done on an LCM one can also do it on one of these digital computers” ([5, p. S]).1 I contend that the interest of Turing’s discoveries and observations is both historical and epistemological. In the quoted seminal paper he first of all considers unorganized and other kinds of various supports as physical entities of computation, which is consequently regarded as active in physical (of course also biological) entities suitably modified, thanks to “education”, seen as a certain set of transformations. Programming, Turing says, mimics education in the hope that the machine will be capable of presenting certain expected reactions to particular commands. I have illustrated in the previous section that research in distributed cognition contends that humans delegate cognitive (and epistemic, moral, etc.) roles to externalities (artefacts, props, etc.) and then tend to recapit­ úlate what they have checked occurring outside, over there in the external representations, after having manipulated — often with Creative outcomes — the external invented structured model. For example, we know that it is not neurologically easy to perform a trivial multiplication of numbers

SA L C M is a kind of discrete machine Turing introduced in 1937 that has “[■••] an infinite memory capacity obtained in the form of an infinite tape marked out into squares on each of which a Symbol could be printed. A t any moment there is one symbol in machine; it is called the scanned symbol. The machine can alter the scanned sym bol a its behavior is in part described by that symbol, but the symbols on the tape elsewhere do not affect the behavior of the machine. However, the tape can be moved back forth through the machine, this being one of the elementary operations of the mac Any symbol on the tape may therefore eventually have innings” ([32, p. 6]). tP C M s are machines that organize their stored information in a form which


repeat the tape form. In presence of a huge quantity of steps that can be inv computation along the tape P C M s machines can easily solve the problem because, says “ [. . . ] by means of a system that is reminiscent of a telephone exchange it 1S possible to obtain a piece of information almost immediately by ‘dialing’ the


p ^ js

this information in the store” (p. 8). Turing also observes that “nearly’ a^J0^ p Uting under construction have the fundamental properties of the Universal Logical ¡t Machines: “ [. . . ] given any job which could have be done on an LCM one can^ on one of these digital computers” ( ibid.), it is in this perspective that we Universal Practical computing Machines.



Computationalism in a Dynamic and Distributed Eco-cognitive Perspective


by projecting in our mind the standard schema of that multiplication as it is used, with paper and pencil, taking advantage for an example of a blackboard; to solve the small problem we instead need the manipulation of an external device, for example a sheet of paper. Mind puts representations in the environment, so reifying itself in various semiotic structures that are able not only to mimic but also to improve and modify its internal representations. In the perspective of distributed cognition we can say that the (Universal) LCM is added by Turing to the external idealized tools already objectified during the history of Western civilization: it is a new abstract tool/machine that is characterized by very powerful mimetic properties, it is able to mimic a plenty of human cognitive operations, and at the same time clarifies the concept of effective procedure, it is a real mimetic mind. On the basis of this abstract LCM machine, Turing, already in 1950 contends that digital computers (as external physical suitable entities) can be constructed, and can mimic the actions of a human Computer very closely. To express this action of externalization of an abstract and of a concrete tool performed by Turing’s discoveries I called ([6] and [9] chapter three) the (Universal) LCM (the theoretical artifact) and the (Universal) PCM (the practical artifact) mimetic minds: indeed they are able to mime the mind in a real universal way and because they are “minds” externally objectified in the environment, as distinctly describable formal intellectual structures and practical machines. We do not have to refer to a plenty of several machines that do a variety of jobs: it is just necessary to “program” this universal machine to have those jobs done. I think these mimetic minds represent a kind of triumph of that process of externalization of cognitive powers to the external environment at work since our ancestors times I have illustrated ln the previous section. 3.2.

Unorganized and paper machines

pi0Cess leads Turing to the invention of both LCMs and calis S ^ extreme*y interesting. Turing says that there are some entities, he tion”^ ^ 077^26^ mac^ nes'>which are basically random “in their construclSo far ' dcfinit * We ^ave been considering machines which are designed for a tion) ^ PUrp°Se (though the universal machines are in a sense an excep­ to a 6 mi^ instead consider what happens when we make up a machine nents [ P^ratlvely unsystematic way from some kind of standard compo•] Machines which are largely random in their construction in this


L. Magnani

way will be called ‘Unorganized Machines’ . This does not pretend to be an accurate term. It is conceivable that the same machine might be regarded by one man as organized and by another as unorganized” ([5, p. 9]). Many units form machines of such a type. Each unit is characterized by two input termináis and has an output terminal that can be linked to the input ter­ mináis of 0 or more of other units. Turing gives an example of what he calis unorganized A-type machine, in which all units connected to a synchronizing unit from which synchronizing pulses are emitted at more or less equal intervals of times is given in Fig. 1 (Turing calis the times when the pulses arrive “moments” and each unit is capable of having two States at each moment). A-type unorganized machines, Turing adds, are a good and simple model of organic entities such as a nervous system with a random arrangement of neurons.u Furthermore, “It is possible to produce the effect of a computing machine by writing down a set of rules of procedure and asking a man to carry them out. [... ] A man provided with paper, pencil and rubber, and subject to strict discipline, is in effect a universal machine” (p. 9). Turing calis this kind of machine “Paper Machine.” (2)


model of a Fig. 1

An example of the so-called unorganized A -type machine, a simple

nervous system with a random arrangement of neurons.

On the infant cortex as an unorganized machine see below Section 3.3.

Computationalism in a Dynamic and Distributed Eco-cognitive Perspective


It is more than evident than in both cases high level cognitive activities are anticipatorily described as dynamical activities [33], which involve the coordínate intervention of both internal (mental) resources and external material ones, like paper and pencil [33] and other suitable entities, in a situation of agent-environment interaction. Recent approaches in terms of dynamic systems [7] and, as I have already stressed, in terms of dis­ tributed cognition [3l], can be illuminating in interpreting these extraordinary Turing’s ideas. I have to stress that also Turing’s invention of the LCM machine is performed, thanks to a heuristic which takes advantage of a clear attention to the interplay between internal and external resources: when Turing stressed the active role in computation of what he calis “mimicking education” , I will describe in Section 3.3, he strongly pays attention to the central role played by the flux of information that comes from the external environment. The reader perfectly knows that the LCM standardly incarnates the view of the so-called classic computationalism, which refers to the idea that computations are performed by a cognitive system through inter­ nal symbolic transformations depending on purely syntactic rules: we are instead seeing that the emergence of this concept in Turing is completely related to a perspective that takes advantage of the consideration of the interaction between internal and external aspects such as organic agents, paper and pencil, physical electronic artefacts, education, etc. These are not accessories to the new idea of computation, but an essential part of k. After all, just to make a final simple example, how can we grasp the Turing’s concept of infinite tape without referring to a finite material tape *n an external environment? ^•3. The vide

The emergence o f computation in digital physical entities seen as mimicking human education process of education of human beings can be usefully exploited to proa m°del of what Turing calis “education of machinery” .v Indeed, by

^resentli69^ ^ ^ ° es not ^ ave to naisunderstand the actual meaning of this analogy. ^ catión ^f16 COmPuter training can be certainly seen as quite different from the human tral role \ ,°r examP^e because in the latter case the semantic information plays the cen‘mPortant to7635 m

^ormer case, the semantic information plays no role. It is instead

r°k in his discn° te anal°gy adopted by Turing performs a dominant heuristic lhe few and -°Ver^ Process to the new concept of universal logical machine: in this case this p ersp ect^ S*m^ aiat*es are important so far as they produce new insights, and ^ount. C lVG t^le differences between the two cases are obviously not taken into


L. Magnani

“mimicking education, we should hope to modify the machine until it could be relied on to produce definite reactions to certain commands” ([5, p. 14]). The same happened in the case of a gradúate student that took advantage of ínteractions (interferenees we can say) with other human beings for a couple of decades so that “ [...] a large number of standard routines will have been superimposed on the original pattern of his brain” (ibid.) Turing also observes that (1) those interferences are mainly with other men thanks to visual and other kinds of stimuli; (2) a man concentrating simulates a machine without interference even if is conditioned by previous interactions. When an unorganized machine (such as an infant cortex) is subjected to appropriate interferences it starts to behave as an organized (and possibly universal) machine to reach a determínate target. We have to note that in such cases the machines reach stable configurations as States of discrete machineries. The machines described in these sections are discrete machines because their States can be depicted as discrete sets, with the movements of the machines as activities of jumping from one state to another. An example of a B-type unorganized machine is provided: if units are sufficiently numerous and we give it suitable initial conditions, the machine is transformed in a universal machine also able to become a repository of information. The establishment of the appropriate initial conditions has to be seen as a method for “organizing the machine” , as a “modification” of an unorganized machine, as I have illustrated above. I have anticipated that, following Turing, the infant brain can be conceived as an unorganized machine: “The cortex of an infant is an unorga­ nized machinery, which can be organized by suitable interference traimng. The organization might result in the modification of the machine into a universal machine or something like it. [... ] This picture of the cortex as an unorganized machinery is very satisfactory from the point of view o evolution and genetics” ([5, p. 16]). Not only, in this evolutionary peispec tive, which is certainly speculative but anticipatory of contemporary results of cognitive paleanthropology,w the existence of human cortex can be Jus tified only in terms of its organization, in a kind of coevolution betwee . . «r ] tnc human cortex and external information available to organize it: L*,,J


alled “disein'

wOn the related evidence from cognitive paleanthropology about the s °-c

^ beco&e

bodiment of the mind” and on what I called semiotic brains, as brains capable to make up a series of signs and that are engaged in making or man reacting to a series of signs, see ([9, chapter three]).


Computationalism in a Dynamic and Distributed Eco-cognitive Perspective


possession of a human cortex (say) would be virtually useless if no attempt was made to organize it. Thus if a wolf by a mutation acquired a human cortex there is little reason to believe that he would have any selective advantage” (ibid.) Consequently, the use of a big cortex (that is its suitable organization) demands an appropriate environment: “If however the muta­ tion occurred in a milieu where speech had developed (parrot-like wolves), and if the mutation by chance had well permeated a small community, then some selective advantage might be felt. It would then be possible to pass information on from generation to generation” (ibid.)x Speech and Social Background Turing’s image is powerful. To transform the unorganized human cortex in a universal machine it is necessary to have at our disposal that kind of information that is granted by speech (even if very simple as in the case of parrot-like wolves) and at the same time a social background in which various “techniques” are available and learnable: [... ] the isolated man does not develop any intellectual power. It is necessary for him to be immersed in an environment of other men, whose techniques he absorbs during the first twenty years of his life. He may then perhaps do a little research of his own and make a very few discoveries which are passed on to other men. From this point of view the search for new techniques must be regarded as carried out by human community as a whole, rather than by individuáis ([5, p. 23]). We can derive a clear consequence: a big cortex represents an evolutionary advantage only if it is fecundated by a great storage of meaningful informa­ ron also endowed with a cognitive valué (knowledge) carried by external supports and tools that only an already developed collective of humans can have. Rewards and Punishments Tur* ’ lng s argumentation is cióse to the target of demonstrating that proSramming a machine mimics education. To train a child rewards and X 'p u f .


®btes w h ic lT ^ ^ 6^ ^ 011 a^ ou^ “unorganized” brains, considered as kinds of blank 8P©culative ^ S0C*a^ fulfilled through language has to be remarked because, even if demonstrat^* main*y endowed with a dominant heuristic role, as I have already noted, i*1 huina^ an unusual attention to the importance of phylogenetic mechanisms present hy the trad't’

10n’ an a^ en^ on much more extended with respect to the one adopted °nal philosophical Western schools.


L. Magnani

punishments are needed and this fact indicates that organization can happen only through two inputs. At this point Turing presents the example of an unorganized P-type machine, considered as a LCM without a tape and mostly incompletely described, a machine that thanks to suitable stimuli of pleasure and pain (and the provisión of an external memory) can be transformed in a universal machine (p. 20).y

Discipline and Initiative Henee, the infant cortex is transmuted in an intelligent one thanks to dis­ cipline but also thanks to initiative, which Turing considers the two main aspeets of a process that has to be studied as it happens in humans to “copy it in machines” (p. 21). A prototypical situation that commands initiative is for example “Find a number n such that . . . ” , “see if you can find a way of calculating the function which will enable us to obtain the valúes for arguments . . . ” , that is totally equipollent to that of constructing a program to put on the machine at stake. It seems easy for Turing to exploit the idea of human education I have illustrated above to build the new concept of computation.2 Indeed Turing observes that universal machines are usually subjected to two types of interference: screwdriver interference is when components of the machine are eliminated and substituted with others, originating entirely new machines; paper interference is when the insertion of new information in the machine changes its behavior. Of course we have to stress the fact that paper inter­ ference furnishes information that is both external and material. Turing

y One could ask: “given that Turing was wrong on some things — e.g. ‘Brains of t e human infant are what he calis unorganized machines that can be educated to ‘rewards and punishments’” - does falsity affect negatively his argum entations^ this case the answer is, as I have already explained above, that we are fa c in g ^ ^ speculations about phylogenetic/ontogentic aspeets that just play a lucky heuristic1^ at his invention of the logical computing machine, and that this heuristic character is counts, even if the light of current scientific results the concept appears unsatis zA s I have already noted the metaphor of human education adopted by Turing P useful heuristic role in the discovery process that leads to the new idea of univers computing machine. O f course Turing’s picture of human development is specu

^ *n

unsatisfactory in the light of recent cognitive studies. I address the readers *ntel^ e r¡ch the psychological aspeets of evolving cognitive processes from child to a^u^ L i°


handbook [34] and, more oriented to theoretical and cognitive aspeets, to ^ j ^ neries”i consider Turing’s speculations a first insight on what he calis “unorganized ma^cajjy ver.V but researchers in psychology, at least starting from Piaget, have fulfilled emPlU abstract notions such as the Turing’s ones.

Computationalism in a Dynamic and Distributed Eco-cognitive Perspective


also considered possible to build a thinking machine because human beings have been already able to imitate various parts of man (microphone, tele­ visión, etc.) Also the functions of nerves can be copied thanks to suitable electrical models given the fact the electrical circuits of electronic computing machineries show a capacity to carry and store information analogue to the ones of nerves.aa As I have illustrated above, Turing contends that a big cortex represents an evolutionary advantage only if it is fecundated by a great storage of meaningful information and knowledge carried by external supports and tools that only an already developed collective of humans can have. In few words, information, but also cognitive contents expressed, thanks to language, signs, icons, etc., have to be already present. Similarly, Turing for example contends that transforming an external physical artefactual device (such as an electronic machine) paper interference is needed, when the insertion of new information in the machine changes its behavior. In this perspective the digital machine (a discrete state machine) is surely an alphabetic machine, made possible thanks to the human evolution to alphabetic natural language (of course, as we have noted, we know it is also a logical and formal machine, LCM)[4]. Longo thinks, and I agree with him, that this fact is at the root of that enormous “discretization of knowledge” that the birth of computation has generated. The “continuous” natural language is indeed transformed by the alphabet in something divided into undistinguished atoms, forming letters. They are in themselves without any kind of meaning, a meaning that instead emerges by combining them syntactically when competent human agents are able to sense and manipúlate



% exploiting the dynamic concepts of salience and pregnance, derived from . m s catastrophe theory, I have illustrated the emergence in humans of °rmation, meaning, and of the first kinds of cognition as the outcome h* this ^toputatio356 r^Ur*n® ob>viously refers to information carried out by means of digital encodino- ° r ’ at the same time always stresses that there are no digital ways of bkGiven the°dimati0n ^ ° rganÍC agentS' " " they are .1Screteness of digital machines that is at the basis of their imitation power ‘^itation po^ emetÍC mac^ nes’ 35 I have already stressed — Turing contrasted this simple ^themat^g ^ ^° mucb stronger epistemological power of the modeling capacity of


L. Magnani

of dynamic coevolutionary interactions between brain/mind internal processes, body itself, and external environment. Thanks to this analysis I proposed a ciarification of the concepts of information, cognition, and computation stressing that their dynamic character can only be described taking into consideration their conceptual intertwining from both a cognitive and an epistemological perspective. In the second part of the article, seeing physical computation in the light of the ecology of cognition I offered a new analysis of Turing’s original ideas concerning the emergence of information, cognition, and computation in organic, inorganic, and artefactual agents. I especially emphasized Turing’s new ideas on the emergence of computa­ tion in digital physical entities as related to an analogy to the activity of mimicking human education. Considering computation in the perspective of the above cognitive/epistemological analysis and as dynamically active in distributed physical entities of various kind, suitably transformed so that data can be encoded and decoded to obtain appropriate results, sheds first light on what I cali “eco-cognitive computationalism” .

Bibliography1 8 7 6 5 4 3 2 [1] A. M. Turing, Computing machinery and intelligence, Mind 49, 433-460 (1950). [2] A. M. Turing, The Chemical basis of morphogenesis, Philosophical Transactions of the Royal Society B 237, 37-72 (1952). [3] G. Longo, Turing and the “imitation game” impossible geometry. Randomness, determinism and programs in Turing’s test. In (eds.) R. Epstem, G. Roberts, and G. Beber, Parsing the Turing Test. Philosophical and Methodological Issues in the Quest for the Thinking Computer, pp. 377— 411, Springer, Dordrecht (2009). . [4] G. Longo, Critique of computational reason in the natural Sciences. In (eos-) E. Gelenbe and J.-P. Kahane, Fundamental Concepts in Computer Science. Imperial College Press/World Scientific, London (2009). , [5] A. M. Turing, Intelligent machinery [1948]. In (eds.) B. Meltzer an D. Michie, Machine Intelligence, Vol. 5, pp. 3-23, Edinburgh Universa y Press, Edinburgh (1969). . ^ [6] L. Magnani, Mimetic minds. Meaning formation through epistenuc^^^ ators and external representations. In (eds.) A. Loula, RQroUp and J. Queiroz, Artificial Cognition Systems, pp. 327-357, Idea Publishers, Hershey, PA (2006). -n the [7] R. F. Port and T. van Gelder (eds.), Mind, as Motion. Explorations Dynamics of Cognition. The MIT Press, Cambridge, MA (1995)ne\xxor [8] G. Piccinini (ed.), Computation and representation in cognitive^ Science. Special Issue of the Journal M i n d s a n d M a c h i n e s , 28( )

Computationalism in a Dynamic and Distributed Eco-cognitive Perspective



L. Magnani, Abductive Cognition. The Epistemological and Eco-Cognitive Dimensions of Hypothetical Reasoning. Springer, Heidelberg (2009). [10] L. Magnani, The Abductive Structure of Scientific Creativity. An Essay on the Ecology of Cognition. Springer, Cham, Switzerland (2017). [11] N. Fresco, Physical Computation and Cognitive Science. Springer, Cham, Switzerland (2013). [12] G. Piccinini and A. Scarantino, Information processing, computation, and cognition, Journal of Biological Physics 37(1), 1-38 (2011). [13] R. Thom, Stabilité structurelle et morphogénése. Essai d’une théorie générale des modeles. InterEditions, París (1972). Translated by D. H. Fowler, Structural Stability and Morphogenesis: An Outline of a General Theory of Models, W. A. Benjamin, Reading, MA (1975). [14] R. Thom, Modeles mathématiques de la morphogenése. Christian Bourgois, Paris (1980). Translated by W. M. Brookes and D. Rand, Mathematical Models of Morphogenesis. Ellis Horwood, Chichester (1983). [15] V. Raja, A theory of resonance: Towards an ecological cognitive architecture, Minds and Machines 28(1), 29-51 (2018). [16] J. J. Gibson, The Ecological Approach to Visual Perception. Houghton Mifílin, Boston, MA (1979). [17] A. F. Chalmers, What is this Thing Called Science. Hackett, Indianapolis/ Cambridge (1999). [18] A. Raftopoulos, Reentrant pathways and the theory-ladenness of perception, Philosophy of Science Vol. 68(3), Supplement: Proceedings of PSA 2000 Biennal Meeting, pp. S187-S189 ( 2001). [19] A. Raftopoulos, Is perception informationally encapsulated? The issue of theory-ladenness of perception, Cognitive Science 25, 423-451 (2001). [20] J. Fodor, Observation reconsidered, Philosophy of Science 51, 23-43 (1984). [21] R. E. Nisbett, The Geography of Thought: How Asians and Westerners Think Differently... and Why. Free Press, New York (2003). I 2] R. Thom, Esquisse d’une sémiophysique. InterEditions, Paris (1988). Trans­ lated by V. Meyer, Semio Physics: A Sketch. Addison Wesley, Redwood City, CA (1990). 24! ^ Volfram, A New Kind of Science. Wolfram Media, Champaign (2002). ] S. Lloyd, Programming the Universe: A Quantum Computer Scientist Takes [251 °C the Cosmos’ Kn°Pf>New York, NY (2006). •Chiribella, G. M. D’Ariano and P. Perinotti, Quantum theory, namely the [26] pUrQaiU* reversible theory of information, Entropy 14, 1877-1893 (2012). °yal, Information physics — Towards a new conception of physical [27] ^ *ty’ Inf°rmation 3, 567-594 (2011). [28] a L ^he Organization of Behavior. John Wiley, New York (1949). or a°U^a’ ^ ^udwin, C. N. El-Hani and J. Queiroz, Emergence of self£ . ecl symbol-based communication in artificial creatures, Cognitive [29] s Mith ReSearch n (2)> 131-147 (2010). Rdiqi en’ of the Mind. A Search for the Origins of Art, °n’ an x }

and the closure operator MacNeille’s completion:


defined by f ( A ) =

< * a < a ( A) .

This gives us

Let [P, \/y G S : x T cy]. Every weak tolerance which is reflexive (Vx G 5 : x Tx) is called a tolerance relation. Equivalence relations are transitive tolerance relations. Proposition 6.2 ([39]). There is a bijective correspondence between weak tolerance relations on set S which generalize equivalence relations extending them to a general concept of similarity and closed subsets of the closure operator g on the power set of S, i.e. closure space (2s ,g) defined by: VS C 2S : g(B) = { B C S : V®, y G B 3A G B : {x, y} C A}. We can observe that these two closure operators on the power set of 5 are very different. It can be easily shown that families of subsets of S closed with respect to the closure operator g can have non-empty intersection with families of subsets of 5 closed with respect to closure / only in the trivial case [39]. There is a legitimate question in what way this common formalism of closure spaces on the power set of a set S can help us in comparison between conceptualizations of information. First objection can be that we are interested in the formalization of information defined by differences, but thus far we established only the relationship between the set of all forms of similarities (weak tolerance relations) and closure operators. We already identified the relationship between the relations of abstract orthogonality and their Galois closure. We know that lattices of closed sub­ sets for these Galois operators must be orthocomplemented. Actually, the variety of orthocomplementations distinguishes different orthogonality relations corresponding to the same closure operator. This could suggest that abstract orthogonality (as a mathematical expression of abstract difference) Soes further in distinction of different instanees of information. However, e c*ass °f closure spaces whose lattices of closed subsets admits ortho^ ^ ^ ementati°n is very narrow. If the closure operator is finitely additive for ^ WaS ex^ a*ned m Section 5 above it is the case of all closure operators r topological spaces) the lattice of closed subsets admits orthocomple' 10n °nly in the trivial case (closure for which every subset is closed). does °^lca,l finitely additive closure operator is only one of many which erance0? ort^ocomPlementation. On the other hand, every weak toll imilarity) and every general orthogonality (difference) generate a


M . J. Schroeder

non-trivial closure space, and therefore the concept of information defined by a difference can be reconstructed in terms of information defined in terms of closure spaces. However, there are forms of information (e.g. based on topology) which cannot be formulated in terms of difference. 7. Conclusión We presented mathematical formalisms for both conceptualizations of infor­ mation, as difference and as identificaron of a variety. Also, we went further presenting overarching mathematical formalism in which both formalisms are placed. This made it possible to compare theoretical consequences of the two concepts. The most important consequence is that the description of information in terms of a binary relation (for instance difference) applies only to more restricted forms of information than the description in terms of closure spaces (Identification of a variety). It is possible to identify at least one form of information based on topological properties, which cannot be described in terms of difference. Further study is necessary to identify other more specific types of information escaping conceptualization as difference. We know that the class is broad, but more direct classification would be of great interest. Also, the relationship between the two concepts of infor­ mation, that defined by difference and that by closure space (Identification of variety) is non-trivial. To understand it better, it is necessary to study more the concept of meta-closure space [40]. Bibliography [1] M. J. Schroeder, The Difference that Makes a Difference for the Conceptu­ alization of Information. P r o c e e d in g s , 1(3), 221 (2017), http://www.mdpi-c om /2504- 3900/1/3/221. [2] G. Bateson, A Re-examination of ‘ Bateson’s Rule’. J. G e n e t ., )’ 230 (1971). ^ [3] G. Bateson, S t e p s to an E c o lo g y o f M i n d : C o lle c te d E s s a y s in o gy, P s y c h i a t r y , E v o l u t io n , a n d E p i s t e m o l o g y . University of Chicago Chicago (1972). Cam. [4] D. M. MacKay, I n fo r m a t io n , M e c h a n i s m a n d M e a n in g . MIT Press, bridge, MA (1969). ^ jn [5] G. Bateson, Information and Codification: A Philosophical ApPr0 ^ J. Ruesch G. Bateson (eds.), C o m m u n i c a t i o n : T h e S ocia l M a triz o c h ia t r y , Chapter 7, pp. 168-211, Norton, New York (1951)f ¡nfor[6] M. J. Schroeder, An Alternative to Entropy in the Measuremen mation. E n t r o p y , 6(5), 388 (2004).

Theoretical Study of Information as Difference and as Identification of a Variety 313

[7] M. J. Schroeder, Philosophical Foundations for the Concept of Information: Selective and Structural Information. In Proceedings o f Third International Conference on the Foundations o f Information Science , Paris, July 2005, (2005). [8] E. C. Shannon, A Mathematical Theory of Communication. In E. C. Shannon & W. Weaver (eds.), The Mathematical Theory o f Communication , pp. 3-91, University of Illinois Press: Urbana, IL (1949). [9] M. J. Schroeder, Concept of Information as a Bridge between Mind and Brain. Information , 2(3) 478 (2011), https://www.mdpi.eom/2078-2489/2/ 3/478/ [10] M. J. Schroeder, Search for Syllogistic Structure of Semantic Information. J. Appl. Non-Class. Log., 22, 101 (2012). [11] M. J. Schroeder, Structural and Quantitative Characteristics of Complexity in Terms of Information. In M. Burgin & C.S. Calude (eds.), Informa­ tion and Complexity, World Scientific Series in Information Studies, Vol. 6, pp. 117-175. World Scientific, New Jersey (2017). [12] Y. Bar-Hillel and R. Carnap, An Outline of a Theory of Semantic Informa­ tion, Technical Report No. 247, Research Laboratory of Electronics, MIT (1952). In Y. Bar-Hillel (ed.), Language and Information: Selected Essays on Their Theory and Application , pp. 221-274, Addison-Wesley, Reading, MA (1964). [13] M. J. Reddy, The Conduit Metaphor: A Case of Erame Conflict in Our Language About Language. In A. Ortony (ed.), Metaphor and Thought, 2nd edn., pp. 164-201, Cambridge University Press, Cambridge (1993). [14] R. E. Day, The ‘Conduit Metaphor’ and The Nature and Politics of Infor­ mation Studies. J. Amer. Soc. Inf. Sci. 51(9), 805 (2000). [15] G. Bateson, Mind and Nature: A Necessary Unity. E.P. Dutton, New York (1979). [16] Aristotle Selections by Ross W. D. Charles Scribner’s Sons, New York (1955). [17] J. Gleick, The Information: A History, A Theory, A Flood. Pantheon Books, New York (2011). [18] H. Weyl, Symmetry. Princeton University Press, Princeton (1952). i ] L Piaget, Structuralism (Le Structuralisme). Harper 8¿ Row, New York [20] C. Lévi-Strauss, Structural Anthropology. Transí. Claire Jacobson and [211 p100^6Gnmdfest Schoepf. Doubleday Anchor Books, New York (1967). ’ Saussure, Course in General Linguistics. Transí. Wade Baskin. [22] ^0lumbia University Press, New York (2011). • Tarski, Introduction to Logic and to the Methodology o f Deductive

[23] rpC^nces' Transí. O. Helmer. Dover, Mineóla, NY (1995).

• o arbinski, Wyklady z Dziejow Logiki (Lectures in History o f Logic), (in

[24] ü°KSh) PWN- Warszawa (1985) T Critique of Puré Reason. Transí. J.M.D. Meiklejohn, Henr G. Bohn,

telMÍVl 855' ' » 192 Ki,h C roec'er! Ontological Remetas, 43(6), 882 (2014).

Study of Information: Identity and State.


M . J. Schroeder

[26] G. Deleuze, Difference and Repetition. Transí. P. Patton, Columbia University Press, New York (1994). [27] J. Derida, Writing and Difference. Routledge & Kegan, London (1978). [28] L. Wittgenstein, Philosophical Investigations. Transí. G.E.M. Anscombe, Basil Blackwell, London (1986). [29] R. Needham, Polythetic Classification: Convergence and Consequences. Man (.N.S.), 10(3), 349 (1975). [30] F. Nietzsche, Jenseits von Gut und Bose: Vorspiel einer Philosophie der Zukunz. Neumann, Leipzig (1886). [31] R. Bambrough, Uinversals and Family Resemblances. Proc. Aristot. Soc., 60, 207 (1961). [32] R. Wille, Restructuring Lattice Theory: An Approach Based on Hierarchies of Concepts. In I. Rival (ed.), Ordered Sets: Proceedings of the NATO Advanced Study Institute , BanfF, Cañada, August 28 to September 12, 1981. NATO Science Series C, 83, pp. 445-470. Springer, The Netherlands (1982). Reprinted in S. Ferre & S. Rudolph (eds.), Formal Concept Analysis: Proceedings o f 7th International Conference , ICFCA 2009, Darmstadt, Germany, May 21-24, 2009. Springer Science and Business Media (2009). [33] M. J. Schroeder, The Role of Information Integration in Demystification of Holistic Methodology. In P. L. Simeonov, L. S. Smith & A. C. Ehresmann (eds.) Integral Biomathics: Tracing the Road to Reality, pp. 283-296, Springer, Berlin (2012). [34] W. James, The One and the Many. In W. James, Pragmatism: A New Ñame fo r Some Oíd Ways of Thinking, Longman’s Green and Co., New York (1947). [35] G. Birkhoff, Lattice Theory, 3rd edn. American Mathematical Society Colloquium Publications, Providence, RI, Vol 25 (1967). [36] M. J. Schroeder, From Philosophy to Theory of Information. Int. J. InfTheories AppL, 18(1), 56 (2011). [37] M. J. Schroeder, Dependence Systems. Ph.D. Dissertation, Department of Mathematics, Southern Illinois University at Carbondale, Carbondale, IL, USA (1991). [38] E. C. Zeeman, The topology of the brain and visualperception. In M.K. Fort, Jr. (ed.), Topology of 3-manifols and Related Topics, Proceedings of J University of Georgia Institute 1961, pp. 240-256, Prentice-Hall, Englewoo Cliffs, NJ (1962). [39] M. J. Schroeder and M. H. Wright, Tolerance and weak tolerance íelation > J. Combin. Math. Combin. Comput., 11, 123 (1992). ^ [40] M. J. Schroeder, Exploring Meta-Symmetry for Configurations in Spaces. In K. Horiuchi, (ed.), Developments of Language, Logic, ^ system and Computer Science, RIMS Kokyuroku, Kyoto: Resear PP- ó , a tu te f o r M a t h e m a t ic a l S c i e n c e s , K y o t o U n iv e r s ity , No. 2051, PPcontents/j*1

(2017), http:/ / p/~ kyodo/kokyuroku/c f/205 l-07.pdf

Chapter 13

Factors Space and Mechanism-Based Artificial Intelligence Theory Peizhuang Wang College of Intelligence Engineering and Mathematics Liaoning Technical University, Fuxin. 123000. China The mechanism-based artificial intelligence theory extracts the common characteristics in structuralism, functionalism and behaviorism, the three major schools of AI, and promotes it to be a united mechanism of the transformation from information to knowledge. This article aims to introduce factors space, the mathematical basis for the mechanism-based artificial intelligence theory. Factors space is a promotion from fuzzy sets, formal concept analysis and rough sets, which provides a generalized framework for information description, and taking concept-generation, causality inductive under the framework. Factors space can help AI to do rational thinking such as prediction, identification, control, evaluation and decisión making by factorial algorithms easily and fast. The paper will focus on how to describe formal (grammar) information, and how to transform it to be semantic knowledge according to the requirement of utility (pragmatics) information. The paper provides a preliminary mathe­ matical description on the first law of information transformation established by the mechanism-based artificial intelligence theory. It also takes the tic-tact-°e as example, to express how to combine the target factors and the scene factors, which may be helpful for the mathematical description on the second law of information transformation. A brief outline on the history of factors space is also given in the paper.



to be ^ ^ ^ac^or^ By the Chínese dictionary, which is meant what this the ia^n(* ^ a t to be born. The former is about the form of thing, er ls ab°ut causality. The factor is not the cause, but the master

3 15


P. Wang

of cause. Rain-abundant is one reason for a bumper harvest, but it is not a factor. The factor is rainfall, which dominates flood, abundant rainfall, lack of rainfall, drought and so on, which shows its influence by means of its changing. If rainfall changing does not alter the results of the harvest, then the abundance of rainfall will not be the reason for bumper harvest; Rainfall is so important to ancient agriculture, because its changing can make public celebrates its harvest, also can make not a single grain was reaped, it makes people know that rainfall is the most important factor for harvest. From cause to factor is a kind of sublimation of people in cognition. Only master factor can find and see the reason. The factor is something higher than the attribute, which is the head of a bundle of attributes. Things are the unity of quality and quantity, attribute is the qualitative form; while factor is the qualitative root. Attributes are passive description of things, factors that are suggestive. Only by emphasizing the root, we can do cognition in essential. Philosophers have defined attributes earlier, but they still ignore factors. The attributes are like pearls, and the factor is like the string. As soon as the thread is broken, the pearls will be strewn all over the ground, making it particularly difficult to search. The human brain is the optimized structure of information extraction, and the sensory cells of the human brain are organized by features (special fac­ tors). The gene is the root of bio-attributes, and the early English ñame for gene was once the word factor; factor is the broad gene, which is the key to open the door of information Science. Factor space is where information Science and artificial intelligence expect the support from mathematics. The fundamental difference between information Science and mate­ rial Science is the participation of the subject. Object is the existence beyond subject. The subject of cognition combines grammar and pragmatics to form semantic knowledge, and promotes intelligence in the informa­ tion transformation to rebuild the subjective and objective world, this is the main content of the mechanism-based artificial intelligence theory [ J> which unifies structuralism, functionalism and behaviorism, the three ma^ r schools organically [2], runs through the flexible and universal logic [ J> and forms the advanced artificial intelligence theory. This is an impo development of information Science. A new scientific theory must be su^ ported by a new mathematics. Like Newtonian mechanics, using c as a mathematical underpinning, what is the mathematical under^ Qjs t0 of information Science? The wanted mathematics must provide 0 .i framedescribe concepts, reductive and reasoning, especially, proviae work to do rational thinking description. It must be factors space.

Factors Space and Mechanism-Based Artificial Intelligence Theory


This paper is organized as follows. Section 2, outlines the factor space and its function on the first law of the information transformation of mechanism-based artificial intelligence theory. In Section 3, we use factor space to play chess tic-tac-toe, which is potential support for the second law of information transformation. Section 4 is a short conclusión. 2.

Factors Space and Its Relationship with MechanismBased Artificial Intelligence Theory


Mathematical Definition o f Factor and Factor Space

In mathematics, a factor is defined as a mapping that maps things to their attributes. Definition 1 ([4, 5]). Mapping / : U X ( f ) is called a factor, where U is a kind of things, called the universe of discussion, X ( f ) is a set of States or attributes, called the state space of / . There are two types of state spaces: a continuous real interval or hyperinterval, for example, X ( f ) = [10,250] (cm), in this case, the state space is called quantitative. The factor height can also have another form of state space X ( f ) = {High, Middle, Short}, where the attributes are represented by words in natural language. Such kind of state space is called qualitative. The number of elements m in a qualitative state space must be greater than 1. When m = 2, the factor is also called a feature. A feature is a special factor, it has positive and negative poles, forming a pair of contradictions. Things are in the unity of qualitative and quantitative, a factor can done have two kinds of state spaces both. How is transformation in between the tw° kinds of state spaces done? It is the job of fuzzy sets theory. factor f determines an equivalence relation ~ on U: For any u ,v € ! u ^ v if and only if f ( u) = f ( v) . Such equivalence relation determines a división on U: [u] =

penóte that H ( f , JJ) =

[ u] f =

{ [ u\f \u



U\v ~ v}.


e £/}, we cali it the división of U by / .

fban f re are S^m^ e anc^ complex factors, the so-called factor/ is complex u ^ ^.actor 9 if # (/ , JJ) is finer than H(g, U), i.e., for any v G U there is ’ SUck ^ a t [u]f C [v]g. Such relation is denoted as

H{f,U) g(u) = There comes the algorithm of causality. A lg o rith m


(Causality correlation)

Given factorial table with head T = (t¿; / i , ity rules tree.

extracting the causal­

( 1) Calculating deterministic degree of f j with respect to g : ( 2) Select the factor having largest deterministic degree, transfer each deterministic class to a causality rule and delete those classes from U. The new universe U' must be named by the guiding factor. (3) When a deterministic class [s]fj with respect to factor f j is transferred to be an inference, the phrase ‘u G [ s ] j ^ must be written as a conjunction condition in all rest inferences. Repeat the process until U has been deleted to be empty. Correct the set of causality rules and draw the rule tree. Causality rules extraction is a useful inductive method that can be applied into induction, learning, classification, evaluation, prediction, con­ trol and other sénior thinking activity, and which is the mathematical proof for the algorithm decisión tree. Some papers have been published around this subject [14-16]. When we look at the object that we are dealing with, matching its State with each causal rule, we can infer what kind of utility it has, it lS useful for combine form and utility the two sides and promote to semantic information.

E xam ple


Correlation between Service objects status and service ett

tiveness is given in Table 3. / i = Age, A ( / i ) = {Oíd, Middle, Young}, [O] = {1 ,5 .6}> {2 ,4 ,9 }, [Y] = {3 ,7 ,8 }, f i = Occupation, X ( J 2) = {Teacher, Student, Boss}, [Y] [5] = {3 ,8 }, [-B] = {4 ,5 ,6 },

,, _ '

, 7 o}, i ’ ’

Factors Space and Mechanism-Based Artificial Intelligence Theory

Table 3.

Causality analysis. Purchasing




























































Note : From the status of Service objects to the Service effectiveness. Table 4.

Transformation from Table 4.



















/a = loan, X ( f s ) = {Credible, General, N o-good}, [C\ = { 2,6 ,9 }, [G] = {3,4,5}, [N] = { 1, 7, 8}, /4 = Income, X( f ±) = {High, Average, Low}, [H] = {6 ,9 }, [A] = {1,2,4}, [L} = { 3 ,5 ,7 , 8}, g = Purchasing power, X( g ) = {Real, Empty}, [R} = { 2 ,3 ,4 , 6,9 }, [^ = {1 ,5 ,7 ,8 } According to Algorithm 2, we calcúlate deterministic degree of each factors. We can see that Age : [M] = { 2,4 ,9 } C { 2, 3,4 , 6, 9} = [R], ci = h/m = 3/9; Occupation: [T], [S] and [B] are not the subsets of [R] and [E], no deterministic class, c>Purchasing; Rule 4: Loan G and Age M —> Purchasing; Rule 5: Loan G and Age O —> Empty. Be careful again, the intensión of Uf is that loan is G, it must be written in the first part of reasoning in the any one of successive steps! Since the U' has been deleted to be empty, the running of the algorithm is stop. We can correct all rules as a rules set, or draw a rule tree (omitted). So far, we have known that factors space is the mathematical base for information Science and the mechanism-based artificial intelligence theory. More papers have been published along this way. [17-35]. 3.

Using Factor Space to Play Tic-Tac-Toe

In the transformation of information to knowledge, better search tools are needed. Factors are the key words that inspire the search. This section describes how to use factor thinking to achieve the search of target and scene factors, which can be useful for describing the second^w ^ information transformation. The traditional artificial intelligence te uses tic-tac-toe to describe the search strategy. In this section we ^ ^ same chess to illustrate how to do factorial analysis. It is necessary ^ ^ such questions always: What is my goal? What is the scene? most critical factor to make these two sides unión?


Factors Space and Mechanism-Based Artificial Intelligence Theory


( 1) Set goals and select target factors: Intelligence is a goal-driven activity, and so is chess. In any game, the goal of the player is to win the game. Winning is the goal factor of the chess player. (2) Focus on chess and determine chess ’ describing factors: The realization of winning cannot be separated from the description on chess, it depends on two factors: Board: A chess board drawn by three horizontal Unes and three vertical lines. Game rules: Two players alternately place a piece on a grid point where the place has not been occupied. Starting from the black player. If same color pieces occupy three successive points on a line (horizontal, vertical or diagonal), then that color player wins; If there is no winner to the end (all grid points have been occupied), then it is a draw. The whole process until end is called a chess game. At any time the state of the distribution of black and white pieces in the board can be described by a matrix Bsxs(t), the element bij describes the state at the grid point (i, j ) (white, black, or empty), B(t) is called a composition at t. The universe is the set of all compositions at different time t in all games of tic-tac-toe. U = { { £ ( £ ) } 11 = 1, 2, . . . , T } |in all games}, T is the steps of a chess game, there are T < 9. (3) The combination of target factors and scene factors: When does the factor space occur? Factor space appears in the process of the target factors and chess factors are considered together. Let O be the target factor, it has the state space X ( 0 ) = {White, Black, Draw, Game}. What are the scene factors? In order to win, the black player needs to find where the most important position to be occupied is. Let us set up a factor / = Position with state space X ( f ) = {Center, Edge, Vertex} for black player. The center is the intersection of four lines. A vertex is Íntersected by o mes. A point on an edge (not the endpoint) is intersected by two lines. ose situations will be brought in scope by the factor. In the beginning, Up so

P^ er must defend himself. We set up another factor g = Defense ^ {Oooupy-Center, Stop-at-Vertex, Stop-at-Edge, Indulge}. Set ^actors standing for the two factors specifying at the time £,

° } The^ ° ne ° f ^ m° St simple factor sPace ( ^ ’ X f ) ’ F /i> 92, h , Tabl k n’ We Can orSanize databases from reality of the tic-tac-toe as in


P. Wang

Table 5.

Causality analysis in tic-tac-toe.
























































Ot fr e q


According to the causality analysis Algorithm 2, we can get some rules in the game. We omit the concrete rule extraction at here, readers can do it by yourselves. Comparing with the searching strategy of tic-tac-toe in public textbooks, those rules guided by factorial analysis are smart. If / i = C, i.e., the black player occupies the center, then the frequency of black win will be very high. Why does black win when it occupies center in the first? Why does not black win with 100%? To distinguish situation, we need to have some refinements. (4) Refinement and chess spectrum: When the black piece occupies the center point, the next black piece, wherever it is, will be connected to the center and constitute a threat of victory. At this point, the white piece must be blocked at the point of symmetry. This is why black win usually. To make sure the blacks win, we need to add a factor h = Keyline define on the all edges when there is a black piece occupying the center and there is a white piece has been set. X(Keyline) = {Yes, N o}, an edge is a Keyline if it un-parallel to the edge contain white pieces (see the two red edges in the third square in Fig. 3). Chess spectrum 1: Suppose that f i = C and a white piece occupies a point on an edge (not end point). If black fz = V and the occupied vertex is on the Keyline (Marke red), then black wins absolutely; else, a draw occurs. How to help white player to defend the black’s win? If the white pla3^ does not put the first white piece on an edge, but on a vertex, then ^ black player could not win (see a draw occurs in the last square in FigChess spectrum 2: , i laCk will Suppose that f i = C and a white piece occupies a vertex, then not win, a draw occurs.

Factors Space and Mechanism-Based Artificial Intelligence Theory




t -Q

Fig. 3.

Chess spectrum 1.

O— I — 1 >—


Fig. 4.


O— I — 9 — — é


Chess spectrum 2 .


Factor is the keyword of information Science. Factor space provides a uni­ versal coordinate framework for things description and cognition, which Puts data into a visual sampling space and cultivates them to form the background distribution R . Then, concept generation and causality analySls ^ased R, and all rational thinking processes such as learning, prediction, evaluation, decisión making and control can be described mathematically. Factor space promotes the comprehensive semantic information from for^ al ^nformation and utility information, provides the mathematical base or the first and second laws of information transformation established in e mechanism-based artificial intelligence theory.


This lUOl^íT^ WaS pai^ a^ supported by the grants (Grant Nos. 61350003, 70621001, 70531040) from the Natural Science Foundation of


P. Wang

China and the project of preeminent youth of Shanxi University of Finance and Economics (No. QN-2017007), Shanxi High Educational Innovation Subject (No. J2014059, J2014055), The Educational Innovation Subject of Shanxi University of Finance and Economics (No. 2012110, 2014109).

Bibliography [1] Y. X. Zhong, T h e P r in c i p i e o f H i g h e r A r tific ia l I n t e l li g e n c e : Id ea , M eth od a n d M o d e , Beijing: Science Press, 2014. [2] Y. X. Zhong, P r in c i p i e o f M a c h i n e C o g m a t i c s : U n iv e r s a l T h e o r y o f Transform a t i o n B e t w e e n I n fo r m a t io n , K n o w l e d g e a n d I n t e l li g e n c e , Beijing: Science Press, 2007. [3] H. C. He, P r in c i p i e s o f U n iv e r s a l L o g ic , Science Press, 2001. [4] P. Z. Wang, Y. X. Zhong, H. C. He and H. Ouyan, Cognition Math Based on and factors space, A n n a l s o f D a ta S c i e n c e , 2016, 3(3): 281-303. [5] P. Z. Wang and H. X. Li, M a t h e m a t ic a l T h e o r y o f K n o w l e d g e R ep resen ta tion , Tianjin: Tianjin Science and Technology Press, 1994. [6] Z. L. Liu, T h e o r y o f F a c to r ia l N e u r a l N e t w o r k s , Beijing: Beijing Normal University, 1990. [7] C. Huang, Principie of internet of intelligences and development of its core technology, J o u r n a l o f R is k A n a l y s i s a n d C r i s i s R e s p o n s e , 2017, 7(3): 146-155. [8] R. Wille, Restructuring Lattice Theory: An Approach Based on Hierarchies of Concepts. In I. Rival (ed.), O rd e re d S e t s , Vol. 83 (pp. 445-470). Springer Netherlands, 1982. ISBN: 978-94-009-7800-3. [9] Z. Pawlak, Rough sets, I n t e r n a t i o n a l J o u r n a l o f C o m p u t e r a nd Information S c i e n c e s , 1982, 11: 341-356. [10] G. Y. Wang and Y. Wang, 3DM domain-oriented data driven data mining, F o u n d a m e n t a I n fo r m á t ic a , 2009, 90(4): 395-426. [11] J. Liang, L., Bai, C. Dang and F. Cao, The /c-mean-type algorithm versus imbalanced data distributions, I E E E T r a n s la tio n s o n F u z z y S y s te m s , 2012, 20(4): 728-745. f [12] P. X. Wang and M. Sugeno, Factors field and the background structure o fuzzy sets, F u z z y M a t h e m a t i c s , 1982, 02: 45-54. [13] P. Z. Wang e t al. Factors space and factorial databases, J ou rn a l o f Liaoning T ech n ica l U n i v e r s it y (N a tu r a l), 2013, 32(10): 1-8. , on [14] P. Z. Wang, Rules detecting and rules-data mutual enhancement bas ^ factors space theory, I n t e r n a t i o n a l J o u r n a l o f I n fo r m a t io n íecrin D e c i s i ó n M a k in g , 2002, 1(1): 73-90. . -s [15] P. Z. Wang, S. Z. Guo, Y. K. Bao and H. T. Liu, Causality factors space,

J o u r n a l o f L ia o n in g

2015, 34(2): 273-280.

T ec h n ic a l U n iv e r s ity ( N atura


Factors Space and Mechanism-Based Artificial Intelligence Theory


[16] H. D. Wang, P. Z. Wang and S. Z. Guo, The improving algorithm of causality analysis in factor space, Journal of Liaoning Technical University (Natural Science), 2015, 34(4):539-544. [17] Y. K. Bao, H. Y. Ru and S. J. Jin, A new algorithm for knowledge mining in factors space, Journal of Liaoning Technical University (Natural Science), 2014, 33(8): 1141-1144. [18] F. H. Zeng and L. Zheng, The sample cultivation in factors space, Journal of Liaoning Technical University (Natural Science), 2017, 36(3): 320-323. [19] H. Ouyang, Universal theory of uncertainty: The mathematical base of fac­ tors space in (Special speech), In Oriental Thinking — Int. Conf. 50th Anniversary of the Fuzzy Set, Dalian, China, 2015. [20] Y. Shi, Big data and new technology challenges of scientific, Science & Tech­ nology for Developments, 2014, 1: 25-30. [21] X. H. Yuan, P. Z. Wang and F. S. Lee, Factor space and its algebraic repre­ sentaron theory, Journal of Mathematical Analysis and Applications, 1992, 17(1): 256-276. [22] X. T. Peng, A. Kandel and P. Z. Wang, Concepts, rules and fuzzy reasoning: A factors space approach, IEEE Transactions on Systems, Man and Cybernetics, 1991, 21( 1): 194-205. [23] P. Z. Wang, A factors space approach to knowledge representaron, Fuzzy Sets and Systems, 1990, 36: 113-124. [24] P. Z. Wang and K. F. Loe, Between Mind and Computer: Fuzzy Science and Engineering. Singapore: World Scientific Publishing, 1994. [25] P. Z. Wang, Z. L. Liu, Y. Shi and S. C. Guo, Factor space, the theoretical base of data Science, Annals of Data Science, 2014, 1(2): 233-251. [26] Q. F. Cheng, T. T. Wang, S. C. Guo, D. Y. Zhang, K. Jing, L. Feng, Z. F. Zhaoa and P. Z. Wang, The logistic, regression from the viewpoint of the factor space theory, International Journal of Computers Communications & Control, 2017, 12(4): 492-502. [27] F. S. Yu and C. F. Huang, A framework for building intelligent informationprocessing systems based on granular factors space, Data Mining, Rough Sets and Granular Computing, pp. 414-444, Physica-Verlag GmbH Heidelberg, Germany, 2002. I ] W. Y. Zeng and S. Feng, An improved comprehensive evaluation model and its application, International Journal of Computational Intelligence Systems, 2014, 7(4): 706-714. ] D- Q. Li, H. M. Cui and H. X. Li, Múltiple factorial decisión making based on multi-level variable weights, Journal of Systems Engineering, 2004, 19(3): [30] ~263. Q. Li, W. Y. Zeng and J. Li, New distance and similarity measures n esitant fuzzy sets and their applications in múltiple criteria decill-lt^ k i11^’ ^nJ^neer^n9 Applications of Artificial Intelligence, 2015, 40:


P. Wang

[31] G. F. Yu, W. Q. Liu and D. F. Li, Intuitive language decisión method based on intuitive language with compromised variable weights, Journal of Control and Decisión Making, 2015, 30(12): 2233-2240. [32] He and Z. M. Dong, Concept generation based on factor space and fuzzy clustering, Journal of Systems Engineering Theory and Practice, 1999, 19(8): 99-104. [33] H. H. Mi, G. X. Yan, X. K. Yu and J. X. Hou, Multi-level diagnostic recognition model based on factors space, Journal of Hebei Technical University, 2003, 32: 77-80. [34] T. J. Cui and Y. D. Ma, Definition and cognition of the important distribution of factors in continuous spatial fault tree, Journal of China Security Science, 2015, 25(3): 24-28. [35] T. J. Cui and Y. D. Ma, Research on the method of coal mine safety based on factor space, System Engineering Theory and Practice, 2015, 35(11): 2891-2897.

Chapter 14

Beyond Metaphorization: A Blochian View onto Chaos and Fractality Rainer E. Zimmermann*’* and Zhang X iaom eng^’H *Department of Lehrgebiet Philosophie FK 13 SG, Hochschule München, Clare Hall, Cambridge, UK tDepartment of Liberal Arts, Renmin University, Beijing, China ^rainer. [email protected] edu §[email protected] 63. com With the view to the ongoing project of re-interpreting the Blochian concept of the “darkness of lived immediacy” , possible relationships between philosophy and the Sciences on the one hand, and in particular, between Blochian concepts and modern chaos theory and fractality on the other, are discussed in some formal detail. The objective is to demónstrate that scientific categories can be helpful when applying them to categories of the humane Sciences (and /or phi­ losophy proper) and might lead beyond the mere metaphorization of concepts as it is fashionable today in many fields. Though metaphorization is certainly a hermeneutic technique in its own right, the foundation of applications within a wide range of research topics can be improved when looking more closely at the precise and formally correct aspects involved. Such an approach, which is taking care on what ground the concepts, formal or hermeneutic, are actually U1lt, is not only suitable as to the relationship of philosophy and the Sci­ ences, but also with a view to the arts. A s it turns out, the aesthetical attitude towards the world is somewhat complementary to the conceptual attitude after a Henee, in principie, do both of them serve the same objectives of orientation Wlthm a complex world.

presently on leave of absence to the Ernst Bloch Centre, Ludwigshafen.


R. E. Zimmermann & X . Zhang

3 38



Recently, one of us (Zh. X.) has put forward a new conception to approach one of the basic concepts of Blochian philosophy, namely to what is called the “darkness of the lived moment” , referring to that initial and individual immediacy of subjective existence which serves as a starting point for reflex­ ión in the first place. The philosophical details have been discussed already elsewhere at other occasions.1 The important point is that we have here the rare opportunity to demónstrate the direct interaction of philosophy on the one hand, and the Sciences on the other hand, beyond an exclusively heuristic context. Clearly, this conception is also useful for reconciling Blochian philosophy with the recent insight gained into the modern theory of emergent (evolutionary) systems.2 Moreover: As the concept of emergence also points to processes that produce actually new objects or processes within an essentially self-organizing context, all of this gains also its relevance with a view to the production of aesthetics. The motivation for this project had been originally triggered by the very interesting 2012 PhD thesis of Hammond.3 The objective of this work was to deal with the Blochian notion of abstract, compensatory, utopia linked to modern aspects of chaos theory and complexity.4Because of the possible applications of this approach to cinematographic questions, this work was also especially interesting to one of us (R. E. Z.) who had dealt with a similar work before in some detail.5 But despite the many illuminating passages of

1 Cf.

for fundamental issues on Bloch’s concept R. E. Zimmermann, Z. Xiaomeng,

Sayable and Unsayable within Lived Immediacy. In press for Bloch Jahrbuch 2017. See also Z. Xiaomeng, Information and Meaning in Deterministic Chaos: A Blochian Perspective. Proceedings 2017, 1(3), 247; doi: 10.3390/IS4SI-2017-04090. (Essentially, this has been based on a talk delivered at IS4SI-2017 Conference at Chalmers University, Góteborg, in June 2017, which was an extended versión of another talk delivered earie in April 2017 at the Bertalanffy Centre, Vienna.) 2 Cf. R. E. Zimmermann, Topoi of Systems: On the Onto-Epistemic Foundations o

, .

ter and Information. Chapter 6 in M . Burgin, W . Hofkirchner (eds.), Inform ation tu 191-214. and the Quest for Transdisciplinarity, World Scientific, Singapore (2017), PP and Cine" 3 C. A . Hammond, Towards a Neo-Blochian Theory of Complexity, Hope, , matic uzopia. Utopia. rPhD mane n u thesis, rnesis, Lancaster uancaster University university (2012), J^ Towards_a_Neo_Blochian_Theory_of_Complexity_Hope_and_Cinematic_Utopia/ (2017-20-08).

ibid., 15 sq., n. 1 (par.) Tautegorical Mythopoesis, Aesthetics, and Artistic Creation. Towaras a ^ ^gpain), Interpretation of the Cinematic Image. PhD thesis, University of S a la m a J ic a ^ ^ .^ 4 Cf.

5 M . Rasmi,

2015. (This work refers to Schelling’s mythology rather than to the Blochian ^ but it is important to note that both are closely related to each other.


Beyond Metaphorization: A Blochian View onto Chaos and Fractality


this work6, there remains one crucial problem after all: When talking about mind, consciousness, or any field of the humane Sciences altogether, usually, concepts from the field of chaos theory are utilized exclusively in more or less metaphorical terms. In fact, there has been a long discussion about the legitimacy of doing so for some time, especially when introducing mathematical concepts within structuralistic or post-modern French philosophy. As to chaos theory and fractality, it is for instance quite obvious that the property of self-similarity7 is most attractive when talking about aspects of consciousness for instance. Metaphorization in this sense can probably help to unfold a variety of meanings that are relevant to a given topic in their own right. So far, so good. However, as it turns out, there is much more to this than mere metaphorization. And this is the central point we would like to stress here: Indeed, what we would like to show here is that the mathematical context of chaotic systems (as the notion of system itself) is not arbitrary or cannot be accepted or dismissed at random, but that instead, it is a precise and correct representation of what actually goes on within human consciousness. The reason for this is twofold: First of all, consciousness is an emergent phenomenon with respect to actual brain processes, the brain being a composite biochemical structure. And in turn, the latter is based on physical foundations. Henee, there is a physical modality at the bottom of consciousness that can be described in mathematical terms. On the other hand, there is, and this is the second point, a generic relationship between philosophy and the Sciences chiefly derived from the viewpoint that philosophy is a Science itself, though one that is dealing with what all the other Sciences are not dealing with: namely with the mediated totality of what there is. Henee, philosophy is not doing once-more what all the Sciences are doing, but by unifying their various perspectives onto the world, it is nevertheless depending on their results. So what we have t° do is to go back to the original definitions of the mathematical concepts ^volved (Section 2), then to re-trace their applications into the topic in gestión, namely by referring to the brain, the mind, and consciousness ‘mmediac Place ) t Í- m tíle sense ° f Bloch is directly coupled to mythological aspects in the first Chapter 17 S

a^SO Been discussed in R. E. Zimmermann, Hoffnung gegen den Tod. (Klassiker Auslegen 56), de Gruyter, n’ B°ston (2017), pp. 325-335 °n e of them is the particularly instructive discussion of Disney’s Hunchback of Notre



^ och (ed.), Das Prinzip Hoffnung

V' ’ lbld-


1S essen'tially a set which is self-similar under magnification. (See

ibid., 37)


R. E. Zimmermann & X. Zhang

altogether (Section 3), and finally to note what the practical consequences are (Section 4).


Chaotic Dynamical Systems

For practical reasons we start from a more conventional definition of chaotic dynamical systems according to earlier work of Devaney.8 We refer here explicitly to his Definition 8.5: “Let V be a set. Then / : V —> V is said to be chaotic on V, if ( 1) / has sensitive dependence on initial (boundary) conditions, (2) / is topologically transitive, (3) periodic points are dense in W ’9 Henee, the idea is to visualize a chaotic map as something that is essentially unpredictable, in-decomposable, and possesses nevertheless an aspect of regularity. Note by the way that in-decomposability reminds us of quantum physics when discussing de-coherence, because of the permanent inseparable coupling between system and environment. It is useful to shortly recall the basic definitions which are entailed by Definition 8.5 above: So a map / : J —» J has sensitive dependence on initial conditions, if there exists some 5 > 0 such that, for any x € J and any neighborhood N of x, there is some y £ N and some n > 0 such that the absolute amount |f n(x) — f n(y) \> S.10 Henee, at least one such point in every neighborhood of x separates from x by at least 5 under self-folding (iteration) of f . 111 2 Also, / : J —» J is said to be topologically transitive, if for any pair of open sets U ,V C J, there exists some k > 0 such that f k(U) n V ^ 0. This means that there are points that can move under iteration from one arbitrarily small neighborhood to any other. Henee, the system cannot be decomposed into two disjoint open sets which are invariant under the map. If a map possesses a dense orbit, then it is clearly topologically transitive. Recall that a subset U of S is dense in 5, if Ü = S, where Ü is the closure of U. This consists of all points in U together with all limit points of U. (A point x e R is a limit point of 5, if there is a sequence of points

8 R. L. Devaney, A n Introduction to C haotic D yn a m ical S y s te m s , 2 nd edn.,

Wesley, Redwood City (1989). 9 Ibid., 50. (par.) 1 0 Cf. ibid., 8 . 2 , 49. 11 Iteration is nothing but self-composition: Instead of / o g (x )

— j(9\x R'

f ( x ) = / ( / ( x ) ) , and this n-times: f n (x) = / o •••o (n -t i m e s ) o f ( x ) . 12 Cf. op. cit ., 8 . 1 , 49.

w e h a v e /°

B eyond Metaphorization: A Blochian View onto Chaos and Practality


xn 6 5 converging to x. Then S is a closed set, if it contains all of its limit points. The point x is a periodic point of period n, if f n(x) = x.) The system terminology here is the original one (actually introduced in mathematics); the more recent concept of “system” being introduced somewhat later, as it is used now within the field of “emergent systems” and so forth, is derived from this.13 Intuitively, we think of a dynamical system as a differential equation of the type dx/dt = f ( x ) , where x can be a vector with many entries. Obviously, the points for which f ( x ) = 0, characterize the critical behavior of the system and are thus called critical points. Although differential equations in their traditional form have not remained in the center of mathematical discussion, because they depend on concepts of continuity and differentiability which are rarely met in concrete natu­ ral processes, they nevertheless serve as a suitable approximation to the description of processes altogether. This is mainly due to the (coordinate) time variable t showing up here in this form of a dynamical system. So,

13It is in order here to shortly refer to a definition of system introduced recently by one of us (R .E.Z.): “W e cali system a network of interacting agents producing a space with a well-defined boundary that is open in the sense of thermodynamics.” (Metaphysics of Emergence, Part 1 , 2015, 27, reference quoted below, n. 28 in this present text.) By carefully inspecting this definition, it is clearly seen that a system is thus always self-

organized, because it is produced by its agents that are constituents of the system. In fact, it is even possible to apply game theory to the interaction of these agents. The only

necessary assumption is the validity of thermodynamics. This clarifies two points at once: One is the fact that henee, Computer systems are not actually systems in the sense of the definition, because they are not produced by agents that constitute themselves. At hest, they are system simulations, and this is something else. The second point is that the system definition can be extended in a straightforward manner to the Universe itself. n Principle, the Universe is the maximal system, and henee, it is self-organized, and ^ence, it processes information : This is mainly, because the definition of an agent refers ^

uart Kauffman who couples this definition to thermodynamics again. (Essentially

Work an a^6ní *S a system that is able to perform at least one thermodynamic r eyele.) It can be shown that this is already true for spin networks which are the ^

est constituents of space and time in the sense of (quantum) physics. The agents

cell ^ anííim l°°Ps here, such that six of them co-operate in order to form one hexagonal info°

network- W h at this network is doing is the processing of (quantum)

is notV 10n ^ ence’ we could argüe that the Universe on its most fundamental level inform a ciuanturri Computer. Therefore, what is immediately evident is that, Present f ^ ^ ° eS n°^ actua^y emerge very late in the biological domain, but instead, is Pr°cessed0ni ^ keginning (of the Universe) on. And more than that: This information (their “goal” meaningful, because the objective of these fundamental systems fourth lavu f°T PurPose” ) is to maximize complexity , according to Stuart Kauffman’s Possible•that . ^ ermoc^/nam¿cs (which States that evolution happens into the adjacent to those no

•k -5

transition from an actual State to a new possible State leads always

SS1 1^t*es which are exactly one reaction step away).


R. E. Zimmermann & X . Zhang

the above expression gives essentially a rate of change for States a system can eventually access. Such a State can be visualized as some pair (x, f(x)) in fairly general terms. Henee, dx/dt characterizes the law of the unfolding history of a system observable by means of a sequence of States representing a curve in an appropriate State space.14 For classical (everyday) Systems in physics, it suffices to treat the variable t as the usual coordínate time which can be identified with dock time. If dealing with the field of consciousness, we can keep this classical viewpoint when visualizing consciousness as emergent with respect to the brain processes involved that are basically quantum processes.15


Chaos and Fractals in Consciousness

Now, we come to the important point: The idea we discussed in view of Zhang Xiaomeng’s paper quoted above was based on a new relationship of fractal patterns to the immediacy of the lived moment in the sense of Bloch. This is mainly, because Bloch’s whole categorical theory actually starts from a point which is located before starting to unfold the complete hierarchy of transformations of this initial State of immediacy that eventually produce the main categories in question. Or, in other words, this is where reflex­ ión actually emerges from pre-reflexive immediacy. It is important to shed some light onto this initial moment, before starting to visualize any possible applications of the concepts involved. The idea was then that the initial pattern of conscious processes when represented in a suitable abstract state space would turn out to be an associative composition of bright and dark spots, where the first clear (i.e. conceptual) thoughts would show up as brighter spots arranged according to a fractal pattern within an essentially dark background including some shading in between indicating “zones of

14Note that this state space is not necessarily observable. Very often, it is n o t h in g ^ j an abstract mathematical construction that turns out to be useful. Everyday ^ ^ ^ g observation of physical phenomena usually relate to a special four-dimension space which we cali space-time. identify 15 Henee, we diverge here from the approach of Penrose and Hameroff who consciousness directly with quantum processes. Instead, we point to the fact t h ^ ^ beings do not possess physical senses capable of cognition in the quantum what we observe by means of human modality is only a classical average { approximation to what there really is.


^ ue)

Beyond Metaphorization: A Blochian View onto Chaos and Fractality


transition” . (In fact, any fractal pattern of a similar kind will do for our purposes here.16) Recall the following: In principie, the characteristics of the Blochian darkness of the lived moment can be equated to a State of complete contrastlessness. In other words: When coming out of this darkness by gaining distance, applying Bloch’s elevations-rotations one after the other, then what is gained by this is essentially that the original uniformity of the mentioned darkness is more and more replaced by what we can cali contrast (Fig. 14.1). Usually, contrast is a property of an optical display system, defined as the ratio of the luminance of the brightest color (white) to that of the darkest color (black) which the system is capable of producing. In display Sys­ tems, the objective is to produce a contrast ratio which is as high as possible.

Fig. 14.1

theadd ° ^ ow*nS



Early constraint formation.










^ t i o n ^ 8 ^ P S:/ / /video/clip-27822082-stock-footage-abstractk-html? Sround-in-fiery-orange-with-slow-moving-loop-pattern-and-strong-contrastthem 0 nSr^ T re^/-*-^fi^ : 8 (21-08-2017) In fact, these diagrams are moving, if you access structu

' 1S We^ Pa^e’ ^ n D- Saupe, Bausteine des Chaos. Fraktale. Rowohlt, Reinbek ¡y Sa r^inally in English, Springer, New York, 1992.) And H .-O . Peitgen, H. Jürgens,

34p s ^ Q k ^ a° S’ ^ aus^ n^ der Ordnung. (Rowohlt, Reinbek, (19 9 8/1 9 92 .) (Masq ^ t Urc^ anch T . J. Sejnowski, The Computational Brain. M IT Press, Cambridge 35/6id;, ¿

3 n^

g^1992) (5th printing, 1999).


R. E. Zimmermann & X . Zhang

Yet, this ability to respond rapidly comes at a price of continued activity, requiring a constant expenditure of metabolic energy.” 36 We notice that the connection between activity patterns and corresponding representations hints clearly towards a possible association of mental (conscious) processes ( “thinking” ) and underlying physical processes in the brain. In the even more recent volume of collected essays edited by Tuszynski in 200637 this becomes more and more obvious after all: Although the book assembles many contributions that are clearly following the path of Penrose and Hameroíf, in his own contribution, Scott States bluntly: “Quantum theory is not needed.” 38 This is actually what we would also subscribe to. The contribution of King goes two steps further when, referring to Walter Freeman again, two of his headings read: “Chaos and Fractal Dynamics as a Source of Sensitivity, Unpredictability, and Uncertainty” 39 and “Chaotic Excitability and Quantum Sensitivity as a Founding Eucaryote Characteristic” .40 The details of these sections display material that might turn out to be illuminating with a view to other recent work on general principies of thermodynamics-based form stability and information transfer in biological Systems.41


Preliminary Conclusions

Although Ernst Bloch is not dealing with psycho-analysis in detail, different from Sartre who in his early philosophy bases his concept of “pre-reflexive cogito” on an explicit Freud critique,42 the notion of “darkness of the lived moment” is one of two fundamental concepts that relate both philosophies:

36C. Koch, Biophysics of Computation. Information Processing in Single Neurons. Oxford University Press, Oxford (1999), 369. —

The author refers here to C. Van

Vreeswijk, H. Sompolinsky, Chaos in neuronal networks with balanced excitatory inhibitory activity. Science, 274 1724-1726, (1996). . 37J. A . Tuszynski (ed.), The Emerging Physics of Consciousness. Springer, Beilin, delberg, New York (2006). 71-191 38A . Scott, Physicalism, Chaos, and Reductionism, in: Tuszynski (ed.), op■ c i t 1 here: 171. 39 C. King, Quantum Cosmology and the Hard Problem of the Conscious

. jn; rain

Tuszynski (ed.), op. cit., 4 07 -4 5 6 , here: 13.8, 428. 40 Ibid., 13.11, 437. ,2017, 41 Cf. A . Grathoff, An Evolutionary View on Function-Based Stability. Procer' in^ c &Jl¿ 1 (3), 54; doi: 10.3390/IS 4S I-2017-03920. Also id.: Stonier’s Definition for Structural Information. Proceedings 2017, 1 (3), 51; doi: 10.3390/IS4SI-2017 42J-P Sartre: L ’Etre et le néant. Gallimard, Paris (1943).

Beyond Metaphorization: A Blochian View onto Chaos and Fractality


this is the emergence of reflexión out of something which is essentially nonreflexive. The second concept is that of the project which in Sartre as well as in Bloch directs existential action into the future. These two concepts are at the root of a possible identification of both Bloch’s and Sartre’s approaches with respect to characterizing them as “existential philosophies” ,43 In fact, with the scientific discussion partly presented here, we have the possibility to start with a modern re-construction of psycho-analysis: On the one hand, this is an ancient project of Freud himself which did not eventually emerge properly due to the scientific revolutions around 1900.44 On the other hand, in his 2010 book on psycho-analysis it is Gfáller who has pointed to the necessity to reform the ontological and epistemological foundations of this discipline, based on an explicitly scientific ground.45 Again, this entails consequences for the aesthetical discussion of the arts. In particular, the modern cinematographic arts display many of the philosophical as well as scientific aspects mentioned above. In principie, this should be the case for all of the arts, but some of them obstruct a simple approach to their formal nucleus.46 Essentially, the idea is that all these arts are subject to a specific form of hermeneutic when trying to interpret the meaning of their products and their contexts. But the formal nucleus of each hermeneutic is an appropriate logic. Or in other words: Mathematics is at the bottom of philosophy and art on the one hand, as it is at the bottom of all the Sciences (including the humane and social Sciences, respectively) on the other. Henee, hermeneutic shows up as a logic with incomplete information, while logic is a hermeneutic with (almost) complete information. Note, however that this is actually a euphemism: This is mainly, because the (almost) complete information in physics is due to the comparatively simple structure of the Systems involved in the first place. And then, completeness is quite a relative concept. Nevertheless, the methodological frame that defines 3This aspect has been discussed ¿at aa cuiiiereiice conference un on both in i» 1999 at the ~ uccii uiscusseu ai ¿ uum philosophies pniiusupines ni

t ,.

St , ^ Un^ ' ^f- R- E. Zimmermann, K .-J . Grün (eds.), Existenz & Utopie. System & 44A1 1 & 2, Junghans, Cuxhaven, Dartford (1999). ^ook'of ^ ^ us^ra^ ve compilation of this somewhat apocryphal project is given in the Fres °n ^ ^ ^ c^er’ Freud’s Dream. A Complete Interdisciplinary Science of Mind. M IT 45GSR ¿ lt>rÍdge (M ass0 , London (1992). tivpr p a er’ Fie Wirkung des Verborgenen. Unbewufite Hintergründe kommunikaCí rrozesse \ Untemehmen ~~ ibp , in und Institutionen. K lett-C otta, Stuttgart (2010). might n ^ CaSe m u s ^c 5 a new approach towards mathematical formalization Logic o/cJ6 qu*te Promising after all. Cf. G. Mazzola, The Topos of Music. Geometric oncepts, Theory, and Performance. Birkháuser, Basel, Boston, Berlin (2002).


R. E. Zimmermann & X . Zhang

a space of free play for theories and their applications within the scientific field is quite a strict and precise network of rules, while this network is comparatively released and slackened in the case of the arts. This is a necessary step in order to support the free play of innovative experimentation. So after all, human beings are permanently dealing with hermeneutic methodology when exploring and interpreting the world (or even ask speculatively for the ground of this world), but in any case they have to rely on the mathematical nucleus. This is a kind of true everyday interdisciplinarity after all.


Philosophy of the Study of Information

Chapter 15

The Situated Nature of Informational Ontologies Jordi Vallverdú Philosophy Department, Universitat Autónoma de Barcelona 08190, Bellaterra, Barcelona, Catalonia jordi. [email protected] cat Information is a complex and evasive concept, whose resolution or clarification involves different disciplinary, cultural, and above all, ontological perspectives. Even defending here a non-naive realist approach to information, we can infer from cultural psychology/anthropology, as well as from other branches of cognitive Sciences, a fundamental bias or pattern: the situated nature of ontology. This explains why information is not a fact to be captured but a relational interaction between some sets of data and a cognitive entity. These sets of data are system-related and can only be understood as partial captures of structural meanings. There is no holistic, comprehensive understanding of an information event (the failure of Leibnizian monads). Instead of this, we find some heuristic approaches to reality, which are flavored by cultural-oriented ontologies. There is also a fundamental role of morphological cognitive aspects to be taken into account. A deep analysis of this fact can help us understand not °nly how informational events are created (like the recent stunning Google’s AI System AlphaGoZero strategy) but also how non-human informational reasoning approaches are possible and increase the horizon of the ontological ways °f dealing with information.

Revisiting “Information” of the most fundamental and elusive concepts of 20th Century is that of Physic* a 10n ^ ^aS keen w^ ely explored by mathematicians, engineers, Pliers^T^ C0mputer scientists, sociologists and, finally, philosoWas fk 6 Starting P°int of the contemporary notion of such a concept Was the classic Paper by Shannon in 1948 [1]. In his paper, Shannon laid 353


J. Vallverdú

out the basic elements of communication: (a) an information source (the message), (b) the transmitter (which turns the information as a signal), (c) the channel (through which the signal is sent), (d) the receiver (which transforms the signal to a message), and (f) the destination (which reads or receives the message). Anyhow, without the previous or related ideas of semiotics [2] or cybernetics [3], as well as with the birth of Computer Sciences [4,5], such a concept would not have acquired its rich and current meaning. This seminal analysis of information processing for communication purposes was extremely useful in the new area of Computer processing and telecommunications management. The fundamental importance of such a concept as information was quickly marked as the fundamental aspect of contemporary societies, as sociologist Manuel Castells has perfectly explained in his superb trilogy on Information Age [6-8]. The philosophical aspects of such obvious technological, epistemological, and social changes were explored by Floridi [9-11]. From my previous and short historical analysis, two things can at least be inferred: (a) the “information” concept does not belong to (and cannot exclusively be explained by) a unique research field, and (b) it describes a process, not a fact. Of course, this process can be discretized in order to analyze it, as well as some syntactic rules can be found among these parts, which help us to explain the final reconstruction (which, in turn, is the result of contextual system mechanisms that can run at different action levels). 2.

How does Ontology Information Emerge?

The first important aspect to be taken into account is that (beyond any tautological naive approach to the next statement) information is made of information. When we talk about any object in the world, it can be reduced to some set(s) of informational valúes, which can or cannot combined, connected, or analyzed. But when we talk about the very notion of “information” , it is nothing like more than information, even at its tin^ est scales. Thus, the informational nature of information is nothing is obtained through a neutral process of data acquisition: Conseque is a concept, but never a property. It makes us affirm that the not^ £ ne information is ontologically situated, in the sense that you need to ^ what we cali “information” as a framework for the extraction o ^ ^ ing. For this reason, “being” or “nothingness” can be one,


The Situated Nature of Informational Ontologies


one ontological elicitors [12] and the informational valué of zero cannot be reduced to its naive ontological valué [13,14] ( “nothing” , as an avoided concept by Greek mathematicians and philosophers), but to its functional and situated valué [15-17]. Secondly, it is a corollary of the previous statement, Information is not captured, but it is created by an agent. The process of generating data, even from common sense is not an automated-passivecopy process, but a multidimensional one. Such an informational creation (or, more precisely, binding) is achieved using multidimensional data. The data must also be encoded according to temporal variables [18] which can differ in their design according cultural or conceptual valúes. Anyhow, we can consider two main information generators: bodies and (symbolic) minds, as we will analyze in Sections 2.1 and 2.2.


Bodies & information

Despite the long, intense, and detailed attempts of Western philosophers on capturing the reality through unbiased subjects, the most recent advances made by cognitive Sciences have provided a completely opposite scenario: mind is an active and transitory mechanism that reconstructs some aspects of the reality. A classic oíd koan history from Eastern though, explains it better: “Two monks were arguing about a flag. One said: ‘The flag is moving.’ The other said: ‘The wind is moving.’ The sixth patriarch happened to be passing by. He told them: ‘Not the wind, not the flag; mind is movmg.’ ” (from Mumon Ekai — ÍEKFIHUif] (1228) The Gateless Gate, §29). The lesson we can learn from classic Buddhist approaches to mind is that the “I” is an illusion [19]. The whole process of mapping the own body, and m&king an experience of ourselves and our surrounding areas and related characteristics is a brain reconstruction [20-22]. Beyond any other sense, visión can be considered our main innate aPproach to the surrounding reality. But once we study the morphologiCal conditions, we discover a long set of processes that are present in our suPposed automated process of seeing the “real” external things: inverted (like in any dark chamber), the stereoscopic reconstruction, the real spot in the fovea for each eye which is solved by the brain making vis S(¡ann^n£ reconstructions, the Gestalt selection and integration of data, ÜW Para(*oxes (Phi effect, Heider & Simmel’s apparent behavior, Lips not ^ ^°^ner fu sión , Müller-Lyer Illusion, color Identification,...) as a (^^a^>re^lerisive long list of mechanisms that are happening, making pos­ 8ible the visual perception. Thus, it is obvious, the necessity of affirming

J. Vallverdú

3 56

that morphological constraints determine the basic or grounding steps of cognition, directly related to the bodily aspects [23-27]. This can be easily checked in minimal cognitive systems, like slime mold [28]. The emotional mechanisms are wired into these cognitive systems and provide heuristicoriented ways to deal with information selected by the body [29-33].


Languages & information

As a second level of information complexity, minds created symbolic contents to deal with the events of the world. Symbolic communication can be scarcely found in natural kingdom, often called “signs” (with an obvious anthropocentric bias), and it is a fundamental aspect of modern human nature [34-36]. Languages can be considered extended tools of our minds and through them we understand the world. Obviously, cultural aspects of how these languages are structured (syntactically and semantically) become a fundamental perspective for the informational understanding and Process­ ing [12,37]. Think for example, Brazilian indigenous people of Pirahá who have a special and unique language without numbers [14,38,39], something that determines their sense of time, history, economy, and social structure. It is obvious that other animáis have numerosity skills [40], but humans have reached a completely new level of complexity thanks to their mathematical and quantitative informational symbolic techniques. Another example is regarding the philosophical question of the Selfa: the Western philosopher who thinks “I (am)” uses an Indo-European particle of “I” which makes reference only to the numerical identity of the subject (as first-person sin­ gular); on the other hand, Japanese speaker, can express “I” in several ways: Watashi/Atashi/Ore (the formal/informal/very informal styles), taking into account the social level of communication between agents in which the reference to the self is produced. So, the question about the concept of “I” is not a basic question which has a direct semantic meaning, but it directs us to several linguistic questions at the same time. ^ Finally, the fundamental importance of language is obvious because^ is the only tool that makes us think about ourselves and the world. classic experiment of chimpanzee Washoe, taught to use ASL (American

aI must thank my Ph.D. student Yosuke Nakano, who is doing his researc^^ have topic, for the long debates we have about the Self and Japanese culture w made possible this example.

The Situated Nature of Informational Ontologies


Sign Language), shows us how this tool is the only thing that make us different [41]. 3.

The Logics of Ontological Information

Once achieved the symbolic level, humans created ways of linguistic uses. Beyond the debates about the ways by which the language acquires its meaning (revelation, supranaturalism, induction, deduction, observation, abduction, common-sense,...) , very soon the own complexity of language required a meta-analysis about its correctness. But despite any formal reconstruction of justification, some causal explanations and feelings about the true nature of reality were basically based on some morphologically oriented cognitive skills [42-44]. As the result of the first symbolic elaborations from naive causal cognition, emerged magical thinking [45,46]. And once the theories about argumentation were born, great differences between Western and Eastern both argumentative and logics traditions could be observed [37]. At this level of analysis, and departing from some funda­ mental morphological brain constraints, different cultures selected different ontological origins or valúes. The great bias here is to consider that the ontological fundament is not a real fundament, but only our belief about the consistency of it as the ontological fundament. Western thinkers, still at the beginning of 21st Century, are talking about “Being” as the fundament of reality, completely blind to oíd ideas from Eastern philosophies (which defend Nothingness as the fundamental State) or new ideas from contemporary physics (like quantum field theory and the possibility of emergence from nothingness [47,48]). Here, the symbolic language pushes towards the limits of the own language trying to explain with information the nature °f an intrinsic empty informational thing: nothingness. Beyond the mere existence of that word, nothing can explain nothingness. The paradox is obvious, but it has not blocked theorists of all cultures, historical periods or disciplines to defend fiercely their own visions about such topic. It would e crazy to suppose that a well-trained AI or AGI will reach clear consions from similar data and cióse limitations because there is not a neural framework from which to interpret information. Due to the coli­ ja v antla^ incompleteness of data about reality and the system’s diverse or according to the level in which we devote our study of such reality ;n,

m’ atom^c5genetic, molecular, bodily, neural, conscious, intersocial,

^ ic lS O c i f ll



* eC0l0^lca ’•■•) a single definition of information is not possible. ’ any ontological claim about information is not a result of the


J. Vallverdú

reality expressing itself, but an interpretation of a cognitive entity with several cognitive characteristics, most of them biases. Let us consider them in Section 4.


T he Fundamental Role o f Bias & Incom pleteness

A careful analysis of any cognitive system produced by evolution offers us a terrific result: all these systems are deeply biased. It is not a mistake of evolution but a set of mechanisms useful for using short sets of (probably bad) sets of data with the máximum optimization, according to some local and temporal constraints [49]. Dealing with too much information, or not enough meaning, the necessity of acting fast or selecting about possible memories are basic constraints that orient possible subsets of reasoning strategies. In fact, the modern humans are not really rational, in the true sense of the word, but follow wrong or bounded heuristics [50-53]. Take for example, the results from recent neurological studies on moral behavior: the language with which we think can shape our decisions [54] Neuroethics offers us several examples of such brain reasoning processes, one of the most famous is the trolley problem [55]. We can define the problem with the following possible sources: the information processor or the quality and amount of information are possible variables that modify or condition the whole informational processing activity. 4 .1.

Biasing inform ation by human processors

My argument here follows previous explained ideas about the positive heuristic valué of cognitive biases [56], something that has been reinforced at the beginning of this section. The idea is quite simple: information is nothing that is out there, but the result of our skills and several available heuristics to process and re-create it. As a consequence, there is not one privileged way of dealing with information, but múltiple choices that enable different ranges of satisficing outcomes exist. Placing the emphasis on some method or other, gives us pragmatic advantages, even at scientific or concep­ tual level, as statistical opportunism has shown [40], although the ímpi agents would not have defined their actions or choices as “opportunis tic” , but mostly “rational” . A sincere look at evolutionary and naturalisti approaches to epistemology makes it very clear and obvious [57-59]. Ther fore, biases have some utility according to the valué correlation betwee information processing and utility outcome. It is true that at s o m e ^ ^ these biases can turn into mistakes or show a lack of accuracy

The Situated Nature of Informational Ontologies


better argumentative methods can improve the results ... although limitations are always present because of the locality of the valué of the rules that guide the information for the understanding of a section (or Sys­ tem) of the universe. Even the intentionality that guides the search for that kind of information cannot be the result of the own information, but of the subject’s interests who search within it. As a last but not least factor, we should inelude the ways by which local conditions affect morphological processing of data: weather situation, social conditions, food or drugs intakes,... [60-64]. Convergent or divergent thinking, for example is related to such dynamic and changing variables, and affect definitively the informational processing. 4.2.

Incom plete inform ation

Another fundamental aspect of the problematic nature of information is that we never have enough information about one event. It is always necessary to make some assumptions (that is, “filling the gap” ) which will mark the rest of our cognitive processes. This fundamental fact about the limitations of informational resources affected even the elassie frequentist statistical paradigm, theoretically supported by long series of data, but also modified to run with small amounts of data, as achieved with Student’s t-test [65,66]. As a second related problem to the size and quality of the information, we find another problem: our formal ways to deal with information are necessarily incomplete [67,68], as well as there are several formal paradoxes [69] that defy the soundness of the whole argumentative process. At the end, most of informational statements about the world are based on axioms accepted without previous or continuous revisión. As a third and final problem, we have the dynamical change of the environment, the temporal side of informational valúes. The crucial importance of such cognitive and argumentative aspeets of information required a ^eeP revolution in non-monotonic logics in order to inelude temporal variables [13,70,71].

Deep Learning about N othing, Som ething or W hatever (It M atters)

As gíes8^C° nse Beijing, August 2010. ( 1 9 2 3 - 1 Qfí a trom Pee Kuan Yew, The Singapore Story: M em oirs of Lee Kuan Yew

dAbstr ^ Poreisn Language Press, Beijing, 1998. JiT 6 k°m ^ na^ec^s ° f Confucius, The Great Leaming, and The Doctrine

of the

Shanxi Ancient Book Press, Taiyuan, 2003.


J. Liu

Finally, at the practical level, the core of Confucianism is education, which manifests itself in attaining social harmony that is based on human nature by means of learning of classics and rituals.e Zhu X i’s political ideal is “to correct King’s wrong thinking” , and in his view, people can change their temperament and achieve unity of “one’s heart” and the “moral heart” through learning from Confucianism, personal cultivation and pursuit of truth. The philosophy of harmony between man and nature has to some extent already shown the emerging feature of the totality. In the history of China, Confucianism did undertake the function of edu­ cation for a long time. For example, Xin’an scholarsf in the later study of Zhu Xi, through individual cultivation, inheritance of family study, college teaching, social and governmental influence played a very important role in the local community, economy, culture, politics and other aspects, especially the local folk customs of Huizhou [3], from the early Southern Song Dynasty (1127C.E.-1279C.E.) to the Qing Dynasty. Wang Kekuan writes in the “ Wanchuan Jiashu Ji” (Record of Teaching in Wanchuan Private School): “Since the modern times, Confucianists like Zhou Dunyi, between Cheng Yi, Cheng Hao and Zhu Xi all formed their thoughts here in Huizhou, while Zhu Xi became the epitome of them all, whose great learning, like the light of the sun, swept the thousand-year foolishness among people so that everyone was reading his books and studying his thoughts. While in our neighborhood, known as the Zou (where Mencius was born) and Lu (where Confucius was born) in Southeast China, Confucianism thrived with generations of talents and attracted scholars to follow from near and far.”g This shows that the rise of Xin’an neo-Confucianism has contributed to purifying the local culture and spreading neo-Confucianism.

eJ. Li, The future development in the view of education and confucianism, Journa o

Humanities, 2009(1), 16, 18-25.

^ f Huizhou scholars devoted themselves in study of Zhu X i Neo-Confucianism fiom ^ Song to Qing dynasty, therefore this school is known as the “X in ’An neo-Confucianism^ The main book they researched is Cheng Tong’s Record of X in’an neo~^on! UCl^ ^ x\. that collected more than one hundred scholars’ literature, who made outstanding co ^ butions to the academic field from the Song to the mid-Ming Dynasty ever. In research, the were showing features of following Zhu X i ’s thoughts. In the Qing scholars opposed the empty talks in Confucianism of the Song and Ming



paid more attention to textual explanation of ancient books. Teaching in s Abstracted from KeKuan W ang, Wanchuan Jiashu Ji (Record o Wanchuan Private School), X in ’an Wenxian Zhi (Record of X in ’an Literatuie

Research on the M od em ity of Confucianism


B. Right Attitude towards Confucianism Since the Revolution of 1911, however, Confucianism rapidly declined due to the rapid changes in society. Nowadays we are at a new stage, and it is a subject for us to think how to treat traditional culture correctly and let it continué to play an active role. Indeed, we have to admit that with the development of our times, some thoughts in Chinese traditional culture are outdated, such as the shackles for women in the feudal society, and the foolish loyalty of “one has to die if the King asks so” , which are all from the feudal era.h In the Qing dynasty, Dai Zhen criticized the “Lz (the heavenly principies)” which were admired by Cheng and Zhu and others in the Song and Ming dynasties. He judged it as “killing by Lz” , as well as that “killing by Lz” is even worse than “killing by law” Nevertheless, some elements of traditional culture are still with abundant vitality, giving a positive Ímpetus to our social development, such as kindness, righteousness, propriety, wisdom and trust advocated by Confucianism, and the moral cultivation and education with Confucianism, which are key factors why it is still active on the stage today. At this level, instead of advocating utilitarianism, Confucianism as a theory cannot bet locked up high and reduced to arty tools. Instead, we put our efforts into turning it into the spiritual food in our hearts and injecting new vitality into the development of our society, integrating it with the mainstream ideology so that it can really play the role of cultivating people’s temperament and transforming social traditions. The object of the study of Confucianism is a world of meaning and valué based on the inherent spirit of man and supported by cultural traditions. As a scholar, how to deal with our researching areas? Should we stay conservative, stand still and make no progress, or change the way of thinking and be innovative in the developing society? The answer is clear. First of all, we must recognize that the traditional Chinese culture is an nnportant spiritual wealth of mankind. It is the result of our long-standing culture of 5,000 years, that embodies the courage and the wisdom of the ^ mese nation. In our study of the traditional culture, we must go with essence and the truth revealed by the philosophers, and remove the jabono] parts from the ancient times so that we show the world the essence ese traditional culture. In addition, we must also make our people hReferred to Rongjin Ge, Stu d y on G eneral Normal Unive rsity Press, Beijing, 2001.

C o n cep ts o f C h in ese P h ilosop h y ,



J. Liu

have better understanding of the outstanding achievements of Chinese academics since ancient times, so that everyone can feel national pride in their hearts. In addition, family is the basic unit in the cultural heritage. In some ways, we can say, it cannot be ignored in comparison to school education, therefore, we should allow children to come into contact with traditional culture through the subtle influence of the family, which will arouse their interest in Confucianism and influence them, and will be undoubtedly a fortune in their future life. There is also a growing number of academics in the “enlightenment study” (study of pre-school education), especially in Taiwan, it is very common for pre-school children to learn the “Disciples Rules” , “Three Character Classic” , and “Thousand Character Classic” . 4.

The Practical Significarme of Confucianism

It is the consistent practice of ancient Chinese philosophers to pay attention to the structural nature of things, to focus on the way in which parts are unified, and to explain the nature of things through the partial and overall relationship. At the moment, we should also understand Confucianism in its entirety when we discuss its practical significance. The Chinese nation, standing in the east of the world, has created a brilliant Chinese culture and made tremendous contributions to the world civilization. This culture, at the same time, has played a decisive role in the valué construction of the nation. Today, with the rapid development of social economy and material desires, the author firmly believes that Confucianism still has its own valué. The great concern to scholars today is the question about the role of Chinese traditional culture both in theory and practice, and its significance to us in the real world. Nowadays, people are living in a society that seems to lack meanmg. People’s spiritual world is like an oíd oak tree crushed by a thunderstorm. Suicide and homicide are happening more often because of sharp decline in valúes due to spiritual emptiness and living a boring life. On this point, the Chinese traditional culture can play an important role in containing this. Confucianism is the valué system of the Chinese nation and its r in morality can never be underestimated. Some people cannot reS*S^ jng temptation of money, fame and fortune, and social status, which is no more than the distortion of valúes and views of life caused by the pursuit of material desires. The author personally prefers Mencius s

Research on the M od em ity of Confucianism


of “original goodness of human nature” to the Christian “original sin” . Mencius believes that everyone has a puré heart. But due to the different growing environments and education, as well as differences in emotions and cognition, people go gradually away from the original goodness with slight mistakes of contamination from bad atmospheres. If we teach Confucianism in families and schools and form sets of strict valúes in our minds, the author believes that at least social morality will be somewhat improved, and ethics will stop falling, even though social crimes cannot be fundamentally eliminated. Due to the length of the chapter, it adds only a little bit of light on the study of the reality of Confucianism. Ultimately, the study is to discuss how to revive Confucianism represented by Confucius and Mencius, and how to make it play a positive role at the level of moral cultivation in our society. After all, this subject is put forward to attract enough attention so that the related problems can be effectively solved, which of course is not something that can be done through our simple discussion here. In today’s society, it is a very important topic of how to keep modern life fresh and vital. Some people choose to splurge on a life of luxuries and others enjoy spiritual pursuit, and this involves the moral cultivation and education of Confucianism. In the future path of ideological development, this issue also has its unique significance of enlightenment, doesn’t it?


This project is funded by Financial Grant from Shaanxi Provincial Postdoc­ toral Foundation (2017BSHEDZZ134), Shaanxi Provincial Social Science Fund (2017C006), and specially supported by the 2018 China Postdoctoral Science Foundation (2018T111084).

Bibliography 1 ] Wu, K.

In fo r m a tio n , S y s t e m a n d C o m p l e x i t y P r o b le m s o f th e A n c i e n t P h i l o s -

m y. Commercial Press, 2010. [3j Liu^ ^ ^r^ (lue ° f P u r é R e a s o n . People’s Publishing House, Beijing, 2004. q1U’- A enlightenment of regional Confucian in Xin’an area, [4] '1S c« n t i s t , 2014, 5, 28. tech i^ U’ ^ u x i’s investing things to obtain knowledge: One possible aological rationality. S tu d . D ia le c t. N a t. 2013, 3, 79-83.


J. Liu

[5] Wu, K. Segmentation of existence field and the “whole new revolutional” significance of the philosophy of information. J. Humanit. 2013, 5, 1-6. [6] Steup, M. Epistemology. In Stanford University Encyclopedia of Philosophy, Zalta, E. N., (ed.) Metaphysics Research Lab, Stanford University: Stanford, CA, 2017.


Methodology of Information Studies

Chapter 18

Can Cybersemiotics Solve the Problem of Informational Transdisciplinarity? S0ren Brier Department of Management, Society and Communication Copenhagen Business School, Denmark sbr. [email protected] In this chapter, I discuss the ontological presumptions necessary to produce a transdisciplinary information philosophy and information Science that go beyond mechanicism, dualism, as well as first- and second-order cybernetics. It is found necessary to intégrate the qualitative philosophies of phenomenology and hermeneutics in order to encompass the area of human’s and all living Sys­ tems’ meaningful cognition and communication. However, the conceptualizing of cognition and communication through phenomenology, hermeneutics, and semiotics seem incompatible with an info-computational framework. A nondual pragmaticist semiotic-processes-based philosophical framework named Cybersemiotics, built on the philosophical basis of C.S. Peirce’s triadic semiotic pragmaticist philosophy, is suggested by integrating cybernetic, autopoietics and informational systems with Peircean semiotics to make true transdisci­ plinary models of cognition and communication, Crossing the physical, the biological, the psychological, and the social aspects of reality.



Ever since most of the Sciences left the logical positivist reductionist visión a umty of Science that excluded the qualitative Sciences of experience and meaning in favor of behaviorism [Neurath, 1983], philosophy of Science has Se&rched for an alternative that could encompass the qualitative Science of experiential awareness and meaning in cognition and communication. These 411


S. Brier

days, it is the integration of the brain Sciences and information Sciences that are trying hardest to overeóme the difficulties of transdisciplinarity without integrating phenomenological and hermeneutical elements in the ontological foundation. For instance, you can see the brain Sciences working hard to find a way to intégrate feeling and motivation in either their materialistic or dualistic models, sometimes by a cybernetic view of the brain’s development [Damasio, 2018]. However, other brain researchers such as Fuchs

[2018] are criticizing the prevailing neurobiological reductionism, and neurophysiologists like Damasio [1999, 2003] are discussing the mystery of how it comes that we do not find any mental contentment inside our brains with our physiologically based methods. I am not sure whether the inside/outside brain metaphor we use so much in our scientific culture is productive for the advancement of transdisciplinary knowledge of cognition and communication. The sad fact is that “the brain” is only our physiological model of the central nervous Sys­ tem as a mechanistic or cybernetic model; it does not provide us with a philosophical framework, a theory, of experiential mind.

Though I am originally rooted in biology, Systems, and cybernetics, I do not think that even Bateson [1956,1972,1980], Bateson and Bateson [2005], von Foerster [2003], von Foerster et al. [1974], Maturana and Varela [1980, 1986] and Luhmann’s [1995] models and frameworks are radical enough to inelude a phenomenological aspect. The radicalism of the phenomenological paradigm is that it does not — even in the form of cybernetics and Sys­ tems of second order, like for instance Luhmann’s [1995] system theory and Spencer-Brown [1979] — start by distinguishing between inner and outer. There is no dualism. The experiential universe is prior to any culturally developed scientific explanations of an outside world with “things in themselves” . HusseiTs method was to put any disturbing influences of the “puré experience” in parenthesis or bracketing (Epoché) to try to get to the puré phenomena or the “thing in itself” [Husserl, 1970, 1997, 1999] by peeling away of the symbolic layers of meanings until only the original undisturbed experience remained. 18.2.

The Phenom enological Limits o f Cybernetic Inform ation

Phenomenological philosophy that takes its departure from the unity o experience and world would not look for something outside expeiience the cause of experience. As such, phenomenology is the anti-thesis to o

Can Cybersemiotics Solve the Problem of Informational Transdisciplinarity?


positivism’s empiricism [Husserl, 1970] as its philosophical system does not really allow establishing independent worlds of things or subjects outside experience. This is causing problems for a realist theory of cognition and communication that, as a mínimum, demands something which is there no matter what we think about it. On the other hand, from physicalist monism, there is nothing from the level of reality of our scientific physiological knowledge that seems to be able to help us make a model of how mental qualia or social and cultural meaning emerges or is produced [McGinn, 2000]. This problem does not change just because we go to the quantum level [Brier, 2017a,b], because that is still only a physical theory in most of its versions.a We lack a transdisciplinary model encompassing the quantitative, the qualitative, and the formal to get to a more fruitful formulation of the problem. Now, the question is can we produce a concept of information that can cut across the natural, technical, social, and human Sciences? Would such a concept and model of information help us to grasp the dynamics of knowing, not only for humans but also for plants and animáis and robots? The concept also has to have a significant existential aspect that can encompass our — unscientific? — existential and cultural reflections on being an embodied human with a self-conscious awareness of the facts that — at least the body — has to die and ask why. How can we encompass Descartes’ distinction between res cogitans and res extensa as two different realities into a philosophical framework that relativizes this — from the view of Descartes’ philosophical framing — absolute duality in ontology and epistemology? It is here that Shannon and Wiener’s ideas to measure uncertainty in bits of information enters the stage. The invention of Shannon was to operationalize Descartes’ cogitans and measure it statistically, digitalized in dimensionless bits, and cali that information, though the concept is dimensionless and meaningless. Therefore, it does not really solve the dualism problem, as meaning can now only be provided through a system of reference to the res cogitans of an observer or a group of observers in communicative discourse. Thus, meaning has to be embedded in the interaction of embodied conscious subjects, which is a concept not entailed by the theory. ls so say outside the ontology the theory is based on.

---- -------------------------else°,n ^ rcb*bald W heeler’s interactive universe and “it from bit theory” is something kgic 11 S° me ways cióse to C. S. Peirce’s semiotic philosophy but lacking in phenomenoa y grounded triadic semiotics [Cobley, 2018; Brier, 2 0 17a,b; Davies, 2004].


S. Brier

Bateson’s type of information, as a difference that makes a difference, is an attempt to inelude a subjective as well as a cultural, evolutionary, and ecological dimensión of meaning. It is a great progress that Bateson develops Wiener’s cybernetics and its thermodynamic grounding into biology, bio-psychology, and general cybernetic communication in this way [Brier, 1992]. However, cybernet­ ics has only been able to become transdisciplinary through ignoring the experiential and existential meaning aspect of living systems, even in its development into second-order cybernetics meta-biological constructivism. It elevates the observer to be the creator of res externa, but it never discusses what qualities in the observer makes this possible. What kind of ontology allows a subject to really change its world around it, not only its perception, into an Umwelt or a cognitive domain? It is obvious for most researchers that, for a transdisciplinary cognition and communication Science, the common denominator cannot be Shannon and Wiener’s statistically based information concept, since we have to deal with phenomenologically meaning-generating bodies in a linguistic culturedetermined context. 18.3.

T he Limitations o f the Use o f the Inform ation Concept in Biology

Although the informational concept is heavily used in genetics and biochemical Sciences, the statistical bit-aspect of communication as well as the logical aspect are only parts of what goes on when modern cells organize into multicellular organisms and start to communicate as individuáis within the constraints of being a member of a biological species and a social group in a life world meaning context. Therefore, a biosemiotics has been developed [Hoffmeyer, 1996, 2008; Hoffmeyer and Emmeche, 1991], where the new data about plant awareness, minimal cognitive activities of slime molds, and bacterial creativity can be explained. All these three faets were, till very recently, beyond the knowledge of any expert on information integration and analysis. The journal Biosemiotics and a book-series, both on Springer, go deep into explaining the findings. In 1999, Nobelfórsamlingen Karolinska Institutet awarded Günter Blobel the Nobel Prize in Physiology or Medicine for the discovery that proteins have intrinsic signáis that govern their transport and localization in the cell, thereby acknowledging that a signal has causal powers in biological cellsThe question is, of course, if he by a signal actually just meant information transfer or meant a triadic sign process.

Can Cybersemiotics Solve the Problem o f Informational Transdisciplinarity?


Can one use the term “recognition of protein sorting signáis” without meaning actual semiosis happening in protein subcellular localization? Because recognition is a concept used in embodied minds not in matter or machines, or when it is done, then only metaphorically. The problem nonseems to be if we can go from a mechanistic physicalistic ontology’s energy-based efficient causality view, and to see it as an Aristotelian formal cause without changing paradigm. Can a protein, functioning in the proper compartment of the cell, be viewed as the corresponding final cause? Is this indeed a semiotic interpretive function in the context of the living organism [Petersen et a l, 2011; Almagro Armenteros et al, 2017] or is it a sort of proto-semiosis [Sharov and Vehkavaara, 2015]? Ellis and Newton [1998] recently attempted to intégrate phenomenology with biology: It is the organism’s emotions that motivate it to act on its environment rather than merely react; the phenomenal aspect of conscious experience requires the organismos emotionally motivated act ion in relation to the perceived world, particularly in its interest in selecting for attentional focus. If the organism’s knowledge of its environment is to involve a “felt” dimensión, in the sense that there is “something it feels like” to have a State of consciousness, the conscious processing must first flow from an emotional process within the organism, which pre-exists to any particular input, and puts its qualitative stamp on each selected input. We are suggesting that the “felt” aspect of experiencing is tied in with the fact that organisms are emotionally motivated to “look for” elements of the environment that are significant with respect to the organism’s motivational purposes; that the organism “anticipates” experience in terms of motivational categories which preselect for attention; and that the emotions that guide this anticipation and selection process are a major contributor to the conscious feeling of “what the consciousness of such-and-such an object is like. The point again is that if biology is to encompass the felt experience of animals, its foundation has to differ from that of physics and chemistry as Well as statistically based information concepts. The present mechanistic biological paradigm is therefore not enough. We need a transdisciplinary Science including a theory of signification and meaning, which is exactly what biosemiotics attempts to do. Emmeche [2004] wrote: The semiotic approach means that cells and organisms are not primarily seen as complex assembles of molecules, as far as these


S. Brier

molecules — rightly described by chemistry and molecular biology — are sign vehicles for informational and interpretation processes, briefly, sign processes or semiosis.


Peirce’s U se and Developm ent o f His Own Phenom enology

The difference between a signal and a sign clearly becomes the handling of the necessary difference between the knowledge of the sender and of the receiver, which is what determines which part of a message will be considered information and what information will be imbedded in meaning on many levels, as Luhmann [1995] also saw it. This relativizes the concept of information from being a part of the utmost and fundamental reality in a physicalist worldview — a kind of ‘itfrom-bit’ view — into being something depending on meaning contexts that cannot be described adequately by physics. This is where the hermeneutical aspect enters the problem [Gadamer, 1989]. Here, the need of a theory of cognition that ineludes a theory of experience and meaning horizon must deal with the phenomenological aspect of meaningful communication and the problem of qualia. Then we are out of the realm of both standard physics and logics. Transdisciplinary philosophical frameworks are challenging for the worldview of the special Sciences, especially for such a successful and powerful Science as physics and information Science has developed to be. Peirce [1931-1958; cp 5.40]b wrote that: Phenomenology, which does not depend on any other positive Science, nevertheless must, if it is to be probably grounded, be made to depend upon the Conditional or Hypothetical Science of Puré Mathematics, whose only aim is to discover not how things are but how they might be supposed to be, if not in our universe, then in some other. A Phenomenology which does not reckon with puré mathematics, a Science hardly come to

bI uphold the tradition of referring to Peirce’s work with the abbreviation: C P ° r^ e> lected paper, Citations give volume and paragraph number, separated by a pe CP 5.89. Collected papers. E P for Essential Peirce (see Houser, Nathan &


Kloesel (eds.) [1992]. The Essential Peirce. Selected Philosophical Writings,


(1867-1893) and Peirce Edition Project (ed.) [1998]. The Essential Peirce. Philosophical Writings, Volume 2 [1893-1913], W for Writings (see ^ e*rC1gg7__i892 Project (1982-2009) Writings of Charles S. Peirce: A Chronological Editi°n pejrCe Volumes 1 -8 . M

for unpublished manuscripts that can often be found on

Gateway home page Arisbe: h ttp ://w w w .iu p u i.e d u /~ a risb e /.

Can Cybersem iotics Solve the Problem of Informational Transdisciplinarity?


years of discretion when Hegel wrote, will be the same pitiful club-footed affair that Hegel produced. The qualitative aspects of awareness such as qualia and the narrative and existential meaning of communication are aspects of a reality that is bigger than what we can grasp under the realm of the physical Science. Although our break with tradition, animism, and magical thinking through physics has been very successful, we have to realize that reality is probably bigger than what we can grasp with physical Science [Nicolescu, 2015]. Quantitative forms of information measurements can be useful in many ways, but they are not sufñcient for transdisciplinary theory of cognition and communication. Transdisciplinarily seen, we have to inelude meaning. In what framework can that be done? Nicolescu [2000, 2008] has worked with the metaphysical changes necessary for a transdisciplinary philosophy going beyond materialism, idealism, and dualism. The problem is that natural Sciences do not have models of the qualia of experience and meaning in their conceptual foundations. We can try to develop a logical approach as Burgin [2012], and as Peirce [1931­ 1958] did. Where Burgin stays — as far as I can see — in the structural dimensión, Peirce keeps working with the metaphysical stipulations until he reaches a framework that can intégrate experience, meaning, and logic in one theory, namely his triadic pragmaticist semiotics [Turisi, 1997] , which stands apart from information Science, cybernetics and semiotics in having phenomenology as its basis. Peirce [1931-1958] wrote: Philosophy has three grand divisions. The first is Phenomenol­ ogy, which simply contemplates the Universal Phenomenon, and discerns its ubiquitous elements, Firstness, Secondness, and Thirdness, together perhaps with other series of categories. The second grand división is Normative Science, which investigates the universal and necessary laws of the relation of Phenomena to Ends, that is, perhaps, to Truth, Right, and Beauty. The third grand división is Metaphysics, which endeavors to comprehend the Reality of Phenomena ... For Phenomenology treats of the universal Qualities of Phenomena in their immediate phenomenal character, in themselves as phenomena. It, thus, treats of Phenomena in their Firstness. Normative Science treats of the laws of the relation of phenomena to ends, that is, treats of Phenomena in their Secondness. Metaphysics ..., treats of Phenomena in their Thirdness ... For normative Sci­ ence in general being the Science of the laws of conformity of things to ends, esthetics considers those things whose ends are


S. Brier

to embody qualities of feeling, ethics those things whose ends lie in action, and logic those things whose end is to represent something. (CP 5.121-124 and 129) That is very much the essence of his pragmaticist philosophy. His three phenomenological categories created his unique dynamical phenomenology, which he called phaneroscopy, analyzing the phaneron. It is integrating phenomenology and logic in his view of representation and his revolutionary idea of logic being semiotic. 18.5.

Peirce’s U se o f Logic as a Non-m etaphysical Analysis Tool

The advantage of having logic as the core or rationality of philosophy is that Logic should not — by being truly transdisciplinary — presuppose a particular metaphysics. It should not take any ontological stance towards any phenomena. Peirce went far beyond formal logic, viewing logic as the normative Science of right reasoning in praxis. Thus, his concepts of retroduction (or abduction), deduction, and induction all fall within the purview of logic as a normative Science, which means that metaphysics and the special Sciences employ them in investigating the Reality of phenomena. Peirce wrote: The logician is not concerned with any metaphysical theory; still less, if possible, is the mathematician. But it is highly convenient to express ourselves in terms of a metaphysical theory; and we no more bind ourselves to an acceptance of it than we do when we use substantives such as “humanity,” “variety,” etc., and speak of them as if they were substances, in the metaphys­ ical sense. (EP 2:304; 1904) Consequently, logic can and should furnish the principies that are applied to metaphysics. Peirce wrote: Metaphysics consists in the results of the absolute acceptance of logical principies not merely as regulatively valid, but as truths of being. (CP 1.487; c. 1896) In his fundamental theory of semiosis, going beyond any linguistics int° analyzing the significant character of triadic signs, in the wider sense,^ also based on his categorical distinction between Firstness, Secondness Thirdness as an irreducible triadic relational structure, which is neCpSS. ^ for modeling signification in language, thought and nature itself- el wrote “Everybody recognizes that it is no inconsiderable art, this u

Can Cybersemiotics Solve the Problem of Informational Transdisciplinarity?


of “phaneroscopie” analysis by which one frames a scientific definition.” (EP2:403) It is not that Peirce is not aware of the cultural and linguistic influences on perception and interpretation, but, contrary to most present day humanities and cultural Science analysis, Peirce was interested in the prin­ cipie logical relations behind all kinds of perception (the phaneron) and all kinds of communication through his semiotic analysis. In short, an empirical and logically based Science of signification and communication: It seems to me that one of the first useful steps toward a Science of semiotic (ariiJieiümKrí), or the cenoscopic Science of signs, must be the accurate definition, or logical analysis, of the concepts of the Science. I define a Sign as anything which on the one hand is so determined by an Object and on the other hand so determines an idea in a person’s mind, that this latter determination, which I term the Interpretant of the sign, is thereby mediately determined by that Object. A sign, therefore, has a triadic relation to its Object and to its Interpretant. But it is necessary to distinguish the Immediate Object, or the Object as the Sign represents it, from the Dynamical Object, or really efficient but not immediately present Object. It is likewise requisite to distinguish the Immediate Interpretant, i.e. the Interpretant represented or signified in the Sign, from the Dynamic Interpretant, or effect actually produced on the mind by the Sign; and both of these from the Normal Interpretant, or effect that would be produced on the mind by the Sign after sufficient development of thought. On these considerations I base a recognition of ten respeets in which Signs may be divided. (CP 8.343) Peirce is a pragmatic realist far beyond postmodern radical constructivism. For Peirce, minds are sign systems. Thought is sign action. Cognition is produced by an integration of thoughts and the processes °f producing habitual connection between thoughts. Peirce [1931-1958] wrote: •■■ in what does the reality of mind consist? We have seen that the content of consciousness, the entire phenomenal manifestation of mind, is a sign resulting from inference. Upon our prin­ cipie, therefore, that the absolute incognizable does not exist, so that the phenomenal manifestation of substance is the substance, we must conclude that the mind is a sign developing e^cording to the laws of inference. ls ls fescinating and unique. It changes the metaphysics of Science by Plrig a non-dualist process view beyond Descartes’ dualism. Prigogine


S. Brier

developed a non-equilibrium thermodynamic foundation [Prigogine, 1996; Prigogine and Stengers, 1984] for modern evolutionary Science that was in need of exchanging the reversible time in classical mechanics for an irre­ versible concept of time. However, that in itself did not solve the transdisciplinary problem of including the qualitative Sciences concepts of experience and meaning. This is the question that leads to information philosophy. Is the information concept, as it was defined by Shannon and Wiener, a better level of reality to produce a transdisciplinary view of nature, mind, and culture than the logical positivista behaviorism [Nafría and Alemany, 2011]? Furthermore, Nicolescu [2015] points out that the problem of being transdisci­ plinary is to decide on a view on non-reductionist reality. Peirce wants to place humans in a universe of sign systems processes that connect mind and matter, inside and outside, transcendence and immanence in order to make an experiential realistic and empirically based theory of fallibilist knowing of logic and meaning, uniting all Science and all spirituality in a common basis for peace. Is information that connects level of reality on which we should build our endeavor of a philosophical, scientific, and a practical integration of reality in out postmodern communicative reality with its ecological crisis where the globe is warming up and the insects — most notably the honey bee — are disappearing? Already many years ago, Latour [1988] claimed that “we have never been modern” meaning that we have never been able to sepárate nature and culture into two different spheres. So, maybe the info computational paradigm [Dodig-Crnkovic and Mueller, 2011] is the answer. Here, informational computation is used as the level that connects nature and culture as well as the inside and the outside of experiential awareness. As such, it competes with classical physic’s claim to be able to model the deepest level of reality, which continúes into the development of quantum physics, and then J.A. Wheeler’s integration of them in his “It-from-bit philosophy [Wheeler, 1994]. This leads, in Wolfram’s analysis, to a new kind of Science [Wolfram, 2002], the most fundamental and transdisciplinary info computational Science, based on the view that nature is discrete rather than continuous. The view is inspired by the formal Turing Computer. But it same time — realizes that this concept of computation is too narrow, order to carry out the transdisciplinary project it envisions. A new 0 ^ tion for “natural computing” must be found to make this transdisciplh^ ^ visión possible. Wolfram believes that he has found it. But most


Can Cybersemiotics Solve the Problem of Informational Transáisciplinarity?


Intelligence is constructed on Turing computer-based algorithmic work, in concurrence with the soul of our cultural rationality, not only through the mega-businesses of Google and Facebook but also by the info-computational development of finance in general and in all sorts of governments rationalizations of administration like national security, health care, criminal justice, transportation, and smart cities. These days, AI works with machine learning and data analytics, which analyze data for underlying patterns, which can then be used to design new algorithms for control and profit. It is an economical productivity rationalization that here merges with the AI rationality [West and Alian, 2018]. Maybe it is this technological and financial Ímpetus that is making info-computationalism so interesting for many researchers, while others are crying for a more holistic culture bearing visions [Nicolescu, 2015]. How can we propose an appropriate symbolic representation and interpretation of the role of information in the knowledge acquisition and communication process? A major problem today in modernity is the inference, after Descartes’ dualism; that we are looking for two different worlds. This has probably given rise to the metaphor “inside and outside the brain” as if the mind was inside the brain. If this is so, then nobody has seen it. The question is rather: if there are two or more different levels or aspects of reality, how do we then make a model that shows how they are integrated? In Fig. 1, I have outlined the two worlds of nature and culture and their associated natural Sciences (most often with physics as the model Science dealing with “the basic reality” and a belief in the existence of transcendental laws of nature) and social Sciences (qualitative social Sci­ ence and humanities, most often with a foundation in phenomenological

and hermeneutical philosophies that have experience and meaning as basic reality). In the natural Sciences, we work with a reality of matter, energy, forces, and mathematical laws, but have no concepts of experience and meaning. In the social Sciences and humanities, we work with a reality signs of experience and meaning, and the problem is how to deal with discourse, beliefs, and valúes.

l8 -6.

D escartes and Snow

have been fascinated by the idea of emergence and face shift, but I have ncluded that it has not produced a scientific model of causality in a 0r C anis^c °ntology. However, Bertalanñy was a biologist and did have an ls ontology, where matter is not dead but self-organizing. I have


S. Brier


The worldview of Snows two cultures are not compatible. Technology is m g®k based in physics, logic and mathematics and not in embodied experiential mBr meaning communicating systems. It gives interface problems. But is also a deep philosophical problem about what scientifie knowledge is!! 2 Fig. 1.

The worldview of Snows two cultures are not compatible. Technology is mostly

based in physics, logic and mathematics and not in embodied experiential and meaning communicating systems. It gives interface problems. But is also a deep philosophical problem about what scientific knowledge isü

therefore chosen to go back and broaden our metaphysical foundation, in order for us to be able to intégrate the qualitative and quantitative Sciences in a non-dual and non-reductionists framework. Of course, this meant that I had to step outside the natural and technical Sciences to a philosophical meta-level. As Luhmann [1995] says about his systems theory, it is a full system, but only one of many possible. Therefore, I do think we should try to work out several different transdisciplinary systems in order to compare how well they do in explaining what we know, and to give explanations to those areas where we have none. Here, my critique is that I do not think Luhmann manages to intégrate the qualitative philosophies of phenomenology and hermeneutics into his framework very well and neither do other attempts to naturalized phenomenology like [Petitot et a/., 2000]. I therefore choose to intégrate him with Peirce’s pragmaticist semiotics, which actually does. Figure 2 illustrates a few of them.

Can Cybersemiotics Solve the Problem o f Infomnational Transdisciplinarity?


1. Informationalism, 2. Constructivisms, 3. Systems, 4. Semiotics, 5. biosemiotics 2 Constructivism (subjective or social) '¡'lio * >!;■• ilíiny. liiai ¡vall\

Experiential consciousness

1S 1:K‘ l lll¡\ PcllllKl

Emergente of linguistic selfconsciousness? Emergen ce of language? Emergence of sentient life?

3. Systems. Cybernet ics. information ' and emergence Fig. 2.

¡¡K' ! )uaiii> '.'I' S a h u v i .

HUM ^NITIES ---- w I. :va>

< )b|cci rolniionsíiipv ¡v C 'o n sc u u i- a iá ss . K in t w m mí


p r i o r ¡o a:nl ¡n

lim e

a n d li;o- a i . v n c \ .



A Reductive explanations

PH' fsic s^ * Matter, Energy or information? 1. (Info)mechanicism

Eternal cause andTavv mechanical reduction

The hierarchy problem of the Sciences in evolutionary worldview. Start with (1)

Here the idea of fundamental reality is search for in physical matter, develop into energy through Einstein, these days ending in objective information through W heeler’s ‘ It from bit’ ontology and the info-computational paradigm. (2) Opposite direction is to start in a phenomenological philosophy and combine it with constructivism. (3) Another view is the general systems theory’s emergence theory, which combined with cybernetics, leads to the theory of the self-organized universe often drawing on the non-equilibrium irre­ versible thermodynamics. (4) Is semiology’s structuralist semiotic constructivism, where language as a semiotic system creates culture and the worldview that springs from that. (5) Finally, Peircean biosemiotics is a part of his overall pragmaticist semiotic realism that transdisciplinarily starts in the middle, but now on a semiotic process ontology, where the laws emerge as the universe develops.

As illustrated in Fig. 2, we have various attempts o f transdisciplinary descriptions of cognition and communication in a physical-informational materiality:







objective information as basic stuff o f the world to which all cognition and communication is to be reduced. It is usually a realistic paradigm [Dodig-Crnkovic, 2013; Chaitin, 2006]. This view is based on an ontology that leaves out the conscious observer and an epistemology that leaves out the observer as the cause o f experiences o f differences and can decide to make some differences more important than others. Communication is seen as meaning-free transfer of objectively measured bits information. View no. (2) is constructivisms that are based in experiential human


S. Brier

beings’ co-constructing meaning and reality models, who because of no clear respect for empirical falsification are giving up realism for relativism. Thus, paradigms 1 and 2 are not compatible. View no. 3 in Fig. 2 is a general Systems and cybernetic view with emergence theory. It attempts to solve a materialistic revolutionary theory’s problem with the causal manifestation of consciousness through a holistic theory of systems as being more than the sum of their parts and therefore producing emergent nonreducible qualities like conscious awareness with qualia. Still, Science knows of no theory of quality emergence from matter, energy, and information to experience [Kim, 1998]. But, Luhmann’s [1995] autopoietic second-order cybernetic and systems theory makes the individuality of systems — on both the biological, the psychological, and the social level of autopoiesis — a function of their self-limiting beliefs, through the internal negative feedback systems that establish autopoiesis. This creates a sort of individual and cultural agency or horizon making objective information transfer alone impossible, without the system having developed structural couplings first and through its own structure determined an Umwelt, to which it can assign practical meaning and informational valué to observed differences. However, even structural couplings are not interpretations as there is no experiential cognition theoretically established in the theory. It is simply not possible in cybernetics, be it Bateson, Maturana, or Luhmann. A Peircean semiotic view [Peirce, 1931-1958] starts on a phenomenological ground for meaningfully interpreted cognition and communication combined with puré qualitative mathematics. Through his pragmaticism, he has developed a theory of determining the meaning of a concept or a model [Kauffman, 2012]. As Joyce [2000] wrote, “Pragmatism is really a very considerable thing. It reforms logic, it shows the absurdity of puré thought, it establishes an ethical basis for metaphysic, makes practical usefulness the criterion of truth, and pensions of the Absolute once and for all. In other words, pragmatism is common sense.” In systems and semiotics, information has to be part of a meaningful message whose information contents are determined by the difference in knowledge between sender and receiver/interpreten Semiotics is missing a systems and cybernetic theory of the dynamism of self-organizing embodied systems. This is one of the reasons why I have chosen to intégrate the two in cybersemiotics, with Peircean semiotic as the overall philosophical transdisciplinary framework. Contrary to Husserl, Peirce defines his philosophy as objective idealism indicating his phenomenological foundation and claiming that only appears in experience can be called real. His realism is similar to w

Can Cybersem iotics Solve the Problem of Informational Transáisciplinarity?


Putnam calis ‘internal realism’ [Burch, 2017]. This is because he posits that what appears in experience is what it is regardless of the experience. Thus, he claims a realism where reality is independent of thought in general. It is a special from of semiotic empiricism where our experiences are determined by that which we experience. Peirce developed a non-dualist, non-foundationalist transdisciplinary semiotic process philosophy, which has the potential of integrating animal and human evolution, plus history and language development, in a consistent theory of the development of human consciousness. That is where modern biosemiotics has developed from. Peirce shares the organicist view with Bertalanffy, but he also has a phenomenological and qualitative grounding. Peirce was an accomplished logician, educated as a chemist, had done empirical physical work and developed measurement methods. With this a as starting point, he made the first true interdisciplinary semiotics, including theory of information that goes further into the qualitative Sciences than the prevailing view of information. So, what is his background for doing this? Everybody knows Karl Popper [1972, 1974, 1976; Popper and Eccles, 1977] and his critical rationalism, who share fallibilism with Peirce and Roger Penrose [1997, 1990 and 1995], but who is Peirce? One of the best introductions are given by the interdisciplinary psychologist and philosopher Johnson-Laird [2002]c The American philosopher Charles Sanders Peirce (1839-1914) was a great logician. He discovered the central branch of logic known as the predicate calculus independently from Frege. Frege published in 1879; Peirce published in 1883 (3.328). Peirce also invented truth tables, higher-order predicate calculi, and Systems of modal logic .[..]. He developed an algebraic notation for logic similar to modern Systems. He improved Venn’s logic diagrams. [... ] But he also devised two diagrammatic Sys­ tems for logic, which were powerful enough to deal with sentential connectives such as “if” and “or” , and quantifiers such as “all” and “some” . That is, they corresponded to the predicate calculus. [...]. His work anticipated the semantic networks of artificial intelligence .[..] discourse representation theory in linguistics.[..] and the theory of mental models in psychology .[..] . It has inspired Sowa’s theory of conceptual graphs (Sowa, 1984, 1997), a text book on logic [...], and the work of Jon Barwise

T have deleted all the specific references to literature from the quote because they d'sturb and prolong the message.


S. Brier

and his students on diagrammatic Systems of reasoning [...]. The diagram systems, or “logic graphs” as Peirce called them, have a reputation for being obscure and hard to understand. They are not mentioned in the standard histories of logic [..] Yet they make possible proofs of all and only the valid theorems of the predicate calculus, and they are no more difficult to understand than the calculus itself. And, as Peirce himself realised, they are highly pertinent to the operations of the mind. Peirce’s existential graphs are as such beyond any statistical analysis or information-based concepts and we shall therefore not expect the development of a biosemiotic concept of information or dualist code concept [argued in Brier, 2015b]. Many researchers consider information to be physical [Landauer, 1991], others consider it to be a form and abstract aspect of the reality. It depends on the ontology chosen. Somehow, a Science of information must be linked to a broader philosophy of the possibility and methods of finding scientific truth, as well as a general epistemology and theory of meaning and communication. My discussion focuses on how we can find such a common philosophical and scientific platform. Here, I find it interesting that Popper, Peirce, and Penrose, in their search for such a transdisciplinary frame, all have chosen a dynamic triadic ontology as a way to get out of the dualist dilemma, but they do it in different ways. See Fig. 3. They all agree on a physical and a mental world, but it is the connections between them, they have different ideas off. Penrose, the mathematician, suggests that the third world is a Platonic ideal formal world of logical and mathematical forms [Penrose, 1997]. However, for Popper, the third world is intersubjective knowledge, which he calis objective knowledge [1972]. It is the content of all these theories we have worked with and believe to be true. Like Peirce, Popper is a fallibilist, meaning that we can never prove that our theories are true. New empirical knowledge can always alter or improve them. As such, Penrose as closer to a rationalist stance than Popper, and Peirce is closer to an empiricist stance, but both see data as theory impregnated [Wilson, 2016]. For both Popper and Peirce, the third world is intersubjective fallibilist ever-evolving knowledge. Not universal Platonic forms like Penrose as a mathematician presumes. However, Penrose shows that the area of mathematics is vaster than merely the computational. For Peirce, the third world or Thirdness is connecting the two other worlds, which he defines as Firstness and Secondness in this field continuity that is reality. This produces an organicist field worldview

Can Cybersemiotics Solve the Problem of Informational Transáisciplinarity?


R. Penrose, K. Popper and C.S. Peirce’s Three category philosophies

Peirce World 1 is a phenomenological experiential world. For Peirce it is a part of Firstness. World 2 is a world of Secondness full of concrete actualities of material, as well as mental and social nature

Penrose works with a mental, a physical and a platonic mathematical world

Fig. 3.

World 3 is Thirdness consisting of habits and would-bes, scientific theories, hermeneutical understanding, communication and meaning.

Graphically illustrates three versions of three world philosophies encompassing

an ontology, and epistemology as well as a theory of Science from Popper, Penrose, and Peirce.

inspired by Aristotle’s hylozoist plenum of a living matter. It is an antithesis to Democritus atomic view, where the world is built from indivisible ‘Ding-an-sich’ entities. But such impenetrable limit to knowledge does not exist in synechism because it also connects what dualist ñame “the inside” and “the outside” . The world is not qualitative and separated in two unconnected realms like in Descartes’ dualism, they are aspects of a phenomenologically defined ‘world’ . For Peirce, we start with feeling experience and the general qualitative mathematical forms of experience. The basic categories that Peirce calis Firstness, Secondness, and Thirdness are after his revisión of Aristotle’s, Hegel’s, and Kant’s categories. Aristotle produced 10 categories, Kant 12, and Hegel and Peirce only 3. Peirce [1931-1958] writes ln his application to the Carnegie foundation on the uniqueness of his list °f categories compared to its prerunners: •••this list of categories differs from the lists of Aristotle, Kant, and Hegel in attempting much more than they. They merely took conceptions which they found at hand, already worked out. Their labor was limited to selecting the conceptions, slightly

4 28

S. Brier

developing some of them, arranging them, and in Hegel’s case, separating one or two that had been confused with others. But what I undertook to do was to go back to experience, in the sense of whatever we find to have been forced upon our minds, and by examining it to form clear conceptions of its radically different classes of elements, without relying upon any previous philosophizing, at all. [L75: 3-4] However, it is also this accomplishment, which makes Peirce’s view so differ­ ent from all others. This original way of founding epistemology and ontology in a process view gives us hope that his way of understanding Science and knowing can solve some of the problems we have been stuck with for centuries. At least that is the hope I build much of my work on. Contrary to the statistical information theories with their cybernetic foundations, Peirce [1931-1958] founded his theory on a phenomenological view and wrote about the three categories of experiences he found: An analysis and description of three irreducibly different kinds of elements found in experience and even in the abstract world of puré mathematics. This memoir rests upon observation of the experience of every day and hour, this observation being systematized by thought. It is proved, beyond doubt, that there are no more than the three categories. The list was first published by me in May 1867, but has since been repeatedly subjected to the severest criticism I could bring to bear upon it, with the result of making it far more evidently correct. The categories were originally called “quality” , “relation” , and “representation” . The question of ñames and other terminology for them still somewhat perplexes me. I am inclined to cali them “flavor” , “reaction” , and “mediation” . [L75: 3-8] However, he ended up with the general ñames of Firstness, Secondness, and Thirdness and the definition that all three aspects have to be present in order to produce a genuine sign. Shannon and Wiener’s information is therefore not signs in a Peircean framework. In Peirce’s philosophy of know­ ing, you need to be a sign to carry information! That is very different from most natural and technical-scientific founded ideas of information science. In Peirce’s semiotics, we meet an almost endless triadic dynamism of representation, meaning, and explaining of which information is only a little part. This also means that “the real thing” is not the data, the facts, but the signs. Peirce [1931-1958] wrote: The word Sign will be used to denote an Object perceptible, or only imaginable, or even unimaginable in one sense — for the

Can Cybersemiotics Solve the Problem of Informational Transáisciplinarity?


word “fast,” which is a Sign, is not imaginable, since it is not this word itself that can be set down on paper or pronounced, but only an instance of it, and since it is the very same word when it is written as it is when it is pronounced, but is one word when it means “rapidly” and quite another when it means “immovable,” and a third when it refers to abstinence. But in order that anything should be a Sign, it must “represent,” as we say, something else, called its Object, although the condition that a Sign must be other than its Object.[... ]. If a Sign is other than its Object, there must exist, either in thought or in expression, some explanation or argument or other context, showing how — upon what system or for what reason the Sign represents the Object or set of Objects that it does. [CP 2.230-31] Signs are basic in his worldview where he does not accept an objective information-mechanical world of information as more “basic” or “real” . Peirce’s visión is to create a triadic process philosophy, where semiosis is the primary logical process producing a knowable world. Brought up to date, it means that the world is not only a big mechanical Computer. I want to underline that computers are mechanical in opposition to living systems. Peirce does not accept the primacy of physics when it comes to representing reality. For him, signs are as real as atoms. With Popper, he shares a propensity view of probability and chance accepting evolution as the primary big process in reality. Chance is real and is produced spontaneously all the time, just as quantum field physics sees the quantum fields including the vacuum as spontaneously producing virtual particles. Pierce [1893-1913] calis his view “Tychistic” and, integrated with his synechism, it creates a new look on reality. Though he is a realist, it is in a semiotic realísm we access the world through signs. That goes for perception, thinking, memory, what we cali cognition, and for communication, and he develops a se*niotic communication theory with three interpretants: There is the Intentional Interpretant, which is a determination of the mind of the utterer; the Effectual Interpretant, which is a determination of the mind of the interpreter; and the Communicational Interpretant, or say the Cominterpretant, which is a determination of that mind into which the minds of utterer and interpreter have to be fused in order that any communication should take place. This mind may be called The commens’. It consists of all that is, and must be, well understood between utterer and interpreter, at the outset, in order that the sign in question should fulfill its function. [EP 2:478]


S. Brier

This means that Peirce’s [1931-1958] semiotics changes this worldview qualitatively through his redefining categories and idea of semiotic processes as fundamental in natural and social reality, without being a constructivism. Like information, he sees logic as part of the semiotic process [CP 2.227­ 231]: Logic is the normative Science of the right way to reason and all reasoning is semiotic processes: So, .. I extend logic to embrace all the necessary principies of semiotic, and I recognize a logic of icons, and a logic of indices, as well as a logic of symbols.” In his evolutionary philosophy’s ontology, the dynamics of symbolic expression and growth are at the root, not only of our culture and language but also of the processes of nature. This thus makes biosemiotics fundamental and not just a mere supplement to anthropo-semiotics (the study of human semiotics with most emphasis on language). Actually, in the last decade — not least thanks to the work of John Deely [Cobley, 2009] and Stjernfelt [2014] — the idea of the semi­ otic dynamic reasoning process as fundamental to nature, thus including physics and information Science — has been more consequently developed [Brier, 2015a] . In Peircean cosmogony, the Cosmos emerges into existence from emptiness (as in quantum field theory), along with a tendency to take habits. As such, Peirce models the universe as an almost empty, vague symbol, developing because it is in need of manifesting interpretation in the form of tokens in its development. This metaphysics is a powerful motif for a transdisciplinary understanding of reality, proceeding from logic as semiotic, through philosophy into philosophy of Science [Kauffmann, 2012], culture, art, politics, and religión. Important have also been the works of Lee Smolin, who has accepted Peirce’s idea that the laws themselves develop with the unfolding of the universe in space. Though Prigogine develops physics from the absolute law and time foundation to a thermodynamically irreversible evolutionary view, he did not create a full transdisciplinary alternative to the mechanical materialist physicalist worldview. Still, the development of physical philosophy continued, and in 2013, the famous physicist Smolin wrote the book Time Reborn: From the Crisis in Physics to the Future oj the Universe, where he acknowledged Peirce’s process philosophy [Smolin, 2014]. In particular, he emphasized Peirce’s suggestion that physical laws are not eternal but manifest successively in the cosmogony of the univeis Interestingly, the quantum physicist philosopher J. A. Wheeler also ques tioned absolute eternal laws as vital for the explanation of existence [ On the one hand, Peirce is not a part of traditional humanistic t m ^ ^ that posits humans as unique beings outside nature, because he sees

Can Cybersemiotics Solve the Problem of Informational TYansdisciplinarity?


part of the natural semiotic reasoning process though not from the view of traditional mechanistic and informational biology of the selfish gene. What Peirce calis the principie of synechism or continuity is not an ultimate and absolute metaphysical doctrine. It is rather a regulative principie of logic, which, integrated with his fallibilism, is prescribing what sorts of hypotheses are fit to be scientifically examined. This is because continuity is the absence of ultimate parts in that which is divisible. In Peircean semiotics there is no Kantian “thing in itself” because there can be no limits to knowledge. Considering Peirce’s fallibilism that no belief is ever ultimately proven fixed, he is pointing to the process character of both logic and scientific knowing as an almost endless striving for truth. It is never the end-result we have. Therefore, we must never stop the process of Science. We cannot block the path of enquiry based on things we believe we know now. This also means that we are bound to follow the truth-searching process to the results of our inquiry, no matter what social, economic, political, or religious consequences we may envision that it may have. This is a very powerful antifundamentalist philosophy. No form of fundamentalism, be it religious, scientific, artistic or political, can be accepted as scientific explanation. To this he adds Tychism, because, since reality is not a machine it has its own spontaneity, like the quantum vacuum fields. This is objective chance with the tendency to take habits in the form of symbolic processes. Peirce sees the Cosmos developing through a form of semiotic reasoning process. As soon as we stop, we become fundamentalists. Thus,









computational paradigms search for a foundation for natural computation that goes beyond the limitations of the Turing Computer, and it believes it to be semiotic processes, where logic is semiotic and logic is considered a normative Science because it deais with the norms of the knowledge generating process or correct way of thinking. Peirce [1935-1958] wrote:

Logic, in its general sense, is, as I believe I have shown, only another ñame for semiotic (aruxeiooiLKrí), the quasi-necessary, or formal, doctrine of signs. By describing the doctrine as “quasinecessary” , or formal, I mean that we observe the characters of such signs as we know, and from such an observation, by a Process which I will not object to naming Abstraction, we are led to statements, eminently fallible, and therefore in one sense by no means necessary, as to what must be the characters of all signs used by a “scientific” intelligence, that is to say, by an mtelligence capable of learning by experience. As to that Process of abstraction, it is itself a sort of observation.


S. Brier

Therefore, Logic is not mechanical information strings, but a developing relational reasoning process in nature and culture. In Peircean cosmogony, the Cosmos emerges into existence from emptiness spontaneously — very similarly to the quantum field theory view, which understands the vacuum field as a spontaneously active virtuality on the brink of becoming material in space-time, guided by a tendency to take habits. As such, Peirce models the universe as an almost empty, vague Symbol, developing because it is in need of manifesting interpretation in the form of tokens in its development. This metaphysics provides the grounding for a transdisciplinary understanding of reality, proceeding from logic as semiotic, through semiotic processes [Brier, 2017a,b] into modern biosemiotics scientific understanding as we see it develop in Stuart Kauffmann’s work (2012). For Peirce, everything is open for inquiry and all forms of knowledge are fallible, be it Science, art, religión, or politics. They are all seen as different aspects of a developing collective communicative reality. This philosophy is not a radical constructivism because the semiotic systems of meaning and habits we develop are not isolated from the rest of reality and therefore never finished or perfect in their synechist fallibilism. Every theory with empirical consequences can be tested, which is happening constantly against praxis. Semiotic rationality traverses nature and culture. Our culture is a fallible theory that will be tested against the rest of nature to ascertain whether our thinking is consistent with the development of the rest of the universe. If it is not, we will have to change or die. The process of global warming, therefore, may be an ultimate one. In my understanding, the important dynamics in Peirce’s pragmaticist semiotics is that symbols grow and create habits in a web of signs in nature as well as in culture viewing the central dynamic process in the cosmos as well as man to be of symbolic nature that through evolution and history develop reasoning in many interlocking dimensions. I understand his three categories as his qualitative mathematical analysis of the least amount of aspects necessary to give a phenomenological model of cognition. From there develops a model of communication and by connecting that to his fallibilist non-foundationalist empiricism he produced a philosophy of science as well as a grand evolutionary kind of objective idealist philosophy. His process philosophy was inspired by Schelling and Hegel, as well as Aristotle and Kant. The essence of his process is the complete semiotic process where Firstness provides possibilities of form and qualia, Secondness makes difife1' enees, and Thirdness is mediating between the two. Thus, the Interpretad

Can Cybersemiotics Solve the Problem of Informational Transáis ciplinarity?


provides connection and chooses what difference should make a difference for an embodied consciousness in an evolution of reasoning and learning across nature and culture, individual and group. Therefore, Peirce’s Infor­ mation is embedded in all these aspects of meaning. What is it then? 18.7.

Peirce’s Concept o f Inform ation

Peirce’s concept of information generalizes Shannon’s to the degree that triadic sign relations generalize dyadic cause-effect notions of information transmission. Peircean information is not substantially different from Shannon and Wiener in that it makes sense only in a context of prior uncertainty, the “irritation of doubt” . This is Peirce’s point of departure in his work with developing his semiotically based pragmaticism through making the logical structure of the semiotic process explicitly as Peirce [CP 2.227] conceives logic as semiotic as synonyms. Peirce’s measure of information is based on the power of signs in a given sign relation to reduce the uncertainty of an interpreter about an object. Signs are information vehicles through their place in a specified sign relation, be it a picture, a proposition, a term, or something else entirely. In what sense and to what degree can this ‘information’ be measured, when Peirce’s fallibilism holds that what a given sign will come to mean to us in the end cannot be decided in advance of scientific inquiry? Semiotically viewed, scientific terms can hold a great deal of implicit information as well as the explicit information that scientists are working with at a given time. The information to be quantified is not that of what a given term will come to mean to us in some distant future after a lot of research, but rather what it means to us right now or what we conceive now to be its practical bearing in general on conduct. Peirce [1866] writes: Let us now return to the information. The information of a term is the measure of its superfluous comprehension. That is to say that the proper office of the comprehension is to determine the extensión of the term. For instance, you and I are men because we possess those at tributes — having two legs, being rational, etc. — which make up the comprehension of man. Every addition to the comprehension of a term lessens its extensión up to a certain point, after that further additions increase the infor­ mation instead. Thus, let us commence with the term color; add to the com­ prehension of this term, that of red. Red color has considerably less extensión than color; add to this the comprehension of dark;


S. Brier

dark red color has still less [extensión]. Add to this the comprehension of non-blue — non-blue dark red color has the same extensión as dark red color, so that the non-blue here performs a work of supererogation; it tells us that no dark red color is blue, but does none of the proper business of connotation, that of diminishing the extensión at all. Thus information measures the superfluous comprehension. And, henee, whenever we make a Symbol to express anything or any attribute we cannot make it so empty that it shall have no superfluous comprehension. I am going, next, to show that inference is symbolization and that the puzzle of the validity of scientific inference lies merely in this superfluous comprehension and is therefore entirely removed by a consideration of the laws of information. Peirce’s information theory is built on meaningful signs. Furthermore, he connects information to the growth of symbols. Still, his information theory is empirically based on his pragmaticist realistic worldview, leading to the development to modern biosemiotics including all living systems. Peirce’s concept of information is Breadth x Depth = k implies: the larger the extensión (breadth), the smaller the intensión (depth). Peirce explained further: What are thus referred to, so far as they are known, are:lst, The informed breadth of the Symbol; 2d, The informed depth of the Symbol; 3d, The sum of synthetical propositions in which the Sym­ bol is subject or predicate, or the information concerning the Symbol.

By breadth and depth, without an adjective, I shall hereafter mean the informed breadth and depth. It is plain that the breadth and depth of a Symbol, so far as they are not essential, measure the information concerning it, that is, the synthetical propositions of which it is subject or predicate. This follows directly from the definitions of breadth, depth, and information. Henee, it follows:lst, That, as long as the information remains constant, the greater the breadth, the less the depth; 2d, That every increase of information is accompanied by an increase in depth or breadth, independent of the other quantities; 3d, That, when there is no information, there is either no depth or no breadth, and conversely.

Can Cybersemiotics Solve the Problem o f Informational Transáisciplinarity?


These are the true and obvious relations of breadth and depth. They will be naturally suggested if we term the information the area, and writeBreadth x Depth = Area.15 Peirce’s framework is not quantitative objective bit transference between sender and receiver, but logical inference processes governing perception, cognition and communication. Peirce sees the proposition as a basic analysis of meaning, because logic is semiotic and logic is a normative Science for the correct way of reasoning. He makes the proposition a kind of multiplication of two sepárate functionalities. The extensión (the subject) functions indexically, and the intensión (the predicate) functions iconically. So Breadth x Depth gives a measure of the amount of information inherent in a propo­ sition [Stjernfelt, 2014]. Peirce retained this idea 25 years later in article Kaina Stoicheia. Central to the definition of a Symbol, with it indexes and icons, is that what it communicates is a conditional future. What Peirce calis a ‘would-be’ and a part of Thirdness, habitual stretching from the past over the present into the future. Much information theory only encompasses the past and the present in their probabilistic models. The symbolic function has logical Ínterpretants, which not all signs have. Peirce [1931-1958] wrote: To this may be added the consideration that it is not all signs that have logical interpretants, but only intellectual concepts and the like; and these are all either general or intimately connected with generáis, as it seems to me. This shows that the species of future tense of the logical interpretant is that of the conditional mood, the ‘would-be’. Thus, with Peirce, I suggest measuring the amount of information that symbols acquire — its growth — through its individual and cultural history °f use; or what Peirce calis the “growth of symbols” . This is a pragmaticist semiotic interpretaron of Gregory Bateson’s cybernetic information that is a difference that makes a difference in that it, as in Niklas Luhmann’s triple autopoietic theory of social-communication systems, develops the relation e ween utterance, information and interpretation, because Peirce adds a enomenological grounding to these cybernetic views that they did not have before.



S. Brier

Cybersem iotics Transdisciplinarily Framework Extending Info-com putationalism

Cybersemiotics attempts to intégrate a system theoretical, second-order cybernetic and a semiotic view trying to amend the shortcoming of the above described transdisciplinary models. The point is to construct a model that on the one hand is not totalitarian, mechanistic, algorithmic, or physicalistic reductionist, and on the other hand is not a constructivist relativism giving up any scientific truth claims. Cybernetics and Systems Science attempt to overeóme these problems through their dynamics theory of emergence. Like in dialectical materialism, new qualities are supposed to arise in systems development or when two types of systems are integrated. The basis in Maturana and Varela’s [1980, 1986] second-order cybernetic autopoiesis theory as well as in Luhmann’s [1995] triple autopoietic system theory is an organicist meta-biology. Here, we are out of a physicalist mechanicism, and Luhmann has a social theory of the social reality as communication. In meaningful embodied semiotic and linguistic interaction, we create culture as hypothesis of the how the world is structured and how its processes function. I suggest that our cognition and communication is a meaningful embodied semiotic and linguistic interac­ tion. In these processes, we create our culture as a hypothesis/hypotheses of how the world is structured and how its processes function. I suggest that in our embodied cognition and communication, we are forced to cultivate knowledge in at least four main different areas. The first one about the outer world often called nature, but distinguished in a dead physical and Chemical aspect as well as a living part. Our view of the living part takes its departure in our own experiencing body and empathy with other embodied beings and their ability to have bodily experience of pleasure and pain and communicate these. The third aspect is our experiences and mental imagination’s meaningful storytelling and phantasies. This leads into the fourth area consisting of communication and culture, the narrative aspect of reality where many of these stories are created, conserved, and sometimes even lived out. Cybersemiotics suggests a semiotic pragmati cist theory departing from the social communication from which we create Science in itself as the given. The abductively gained theories and mo ^ flow from the center towards specific aspeets of reality where they can falsified. This falsification empiricism is common to Popper and ^eir^ ve their philosophies of Science. Popper unfortunately does not seem to developed a theory of the qualitative Sciences as Peirce has with his 11

Can Cybersem iotics Solve the Problem of Informational Transdisciplinarity?


semiotics and view of logic as semiotic. Peirce can therefore use falsification theory in all four aspects. The model does support belief in any simple reductionist explanations be they from physics, biology, phenomenology, or social constructivism (any o f the spikes of the star). It is a process philosophy of irreversible time in nature, life, mind, and culture and as such also considers the habits of nature (often called the laws) as manifesting as the universe develops [Peirce, 1931-1958; Smolin, 2014; Wheeler, 1994]. As Nicolescu [2015] — inspired by bootstrapping theory — points out, none of the levels of reality can be more fundamental than the others. They can rather be seen as mutual supplementing aspects or as Latour [1958] points out: “Nothing can be reduced to anything else, nothing can be deduced from anything else, everything may be allied to everything else.” I agree with Latour when he claims that the modernist distinction between nature and culture was never really carried through in praxis. We therefore have to rework our thinking to a view of conception o f the parliament o f things where natural phenomena, social phenomena, and the discourse about them are not seen as sepárate objects to be studied by specialists, which is very cióse to Pierce’s view. Latour’s hybrids are dynamic, self-organized signs produced by the public interaction of people, things, and concepts. Peirce [1893-1913] would say trough forms:

That which is communicated from the Object through the Sign to the Interpretant is a Form. It is not a singular thing; for if a singular thing were first in the Object and afterward in the Interpretant outside the Object, it must thereby cease to be in the Object. The Form that is communicated does not necessarily cease to be in one thing when it comes to be in a different thing, because its being is a being of the predicate. The Being of a Form consists in the truth of a conditional proposition. Under given circumstanees, something would be true. The Form is in the Object, tentatively we may say, meaning that that condi­ tional relation, or following of consequent upon reason, which constitutes the Form, is literally true of the Object. [EP 2:544] As

a consequence of combining Peirce’s pragmaticist realist semiotic ontol-

feel'Witk shared perspective that human beings are embodied, and11^ kn° W^n^’ and culturally formed beings participating in semiosis 11 ^an&uage processes, our analysis so far points to the fact that, it is the that°^C rnean^n^~^ase Amsterdam. .. Peirce, C. S. (1992). The Essential Peirce: Selected Philosophical Writvngs^ Volume 1 (1867-1893), eds. Nathan H. and Christian K., Indiana Unive sity Press.

Can Cybersemiotics Solve the Problem of Informational Transáisciplinarity?


Peirce, C. S. (1992-2009). Writings o f Charles S. Peirce: A Chronological Edition 1857-1892, Volumes 1-8. W for Writings (see Peirce Edition Project (1982­ 2009). Penrose, R. (1997). The Large, the Small and the Human Mind, Cambridge University Press, Cambridge. Penrose, R. (1990). The Emperor’s New Mind, Oxford University Press, Oxford. Penrose, R. (1995). Shadows o f the Mind: A Search fo r the Missing Science of Consciousness, Oxford University Press, London. Petersen, T. N., Brunak, S., von Heijne, G. and Nielsen, H. (2011). SignalP 4.0: Discriminating signal peptides from transmembrane regions, Nature Methods, 8, pp. 785-786. Petitot, J., Varela, F. J., Pachoud, B. and Roy, J.-M. (eds.) (2000). Naturalizing Phenomenology: The Issues in Contemporary Phenomenology and Cognitive Science, Stanford University Press, Stanford. Popper, K. R. (1972). Objective Knowledge: An Evolutionary Approach , Clarendon Press, Oxford. Popper, K. R. (1974). Studies in the Philosophy of Biology, eds. Ayola, F.J. and Dobzhansky, T., On the Problem of Reduction in the Sciences, Macmillan, London. Popper, K. R. (1976). The Abduction of Philosophy: Philosophy and the Public Good, The Myth o f the Framework, Open Court, London, pp. 23-48. Popper, K. R. and Eccles, J. C. (1977). The Self and Rs Brain, Springer, Berlin. Prigogine, I. (1996). The End o f Certainty. Time, Chaos, and the New Laws of Nature, The Free Press, New York. Prigogine, I. and Stengers, I. (1984). Order Out o f Chaos: Man’s New Dialogue with Nature, Bantam Books, New York. Sharov, A. A. and Vehkavaara, T. (2014). Protosemiosis: Agency with reduced representation capacity. Biosemiotics, 8(1), 103-123. Smolin, L. (2014). Time Rebom: From the Crisis in Physics to the Future o f the Universe, Mariner Books, New York. Spencer-Brown, G. (1979). Laws o f Form, Dutton, New York. Stjernfelt, F. (2014). Natural Propositions: The Actuality o f P eirce’s Doctrine of Dici-signs, Docent Press, Boston. ^risi5 P. A. (1997). Pragmatism as a Principie and Method o f Right Thinking: The 1905 Harward Lectures on Pragmaticism by Charles Sanders Peirce, The University of New York Press, New York. VOn ^oerster, H. (2003). Understanding Understanding: Essays on Cybernetics and Cognition, Springer, New York. v°n Foerster, H. et al. (eds.) (1974). Cybernetics o f Cybernetics, BCL Report 73.38, Biological Computer laboratory, Department of Electrical Engineering, ^ niversity of Illinois, Urbana. esL D. M. and Alien, J. R. (2018). How Artificial Intelligence is Transforming e World, Brookings Report, The Brookings Instituí ion, Washington, DC,


S. B rier

https: / / / research/how- artificial- intelligence- is-transfor ming-the-world/ (accessed 24-04-2018). Wheeler J. A. (1994). At Home in the Universe, AIP, Woodbury. Wilson, A. B. (2016). P eirce’s Empiricism: Its Roots and Originality, Lexington Books, London. Wolfram, S. (2002). A New Kind of Science, Wolfram Media, Champaign, IL.

Chapter 19

Ten Principies of Information Science Pedro C. Marijuán* and Jorge Navarro^ Bioinform ation and S ystem s Biology Group Aragón Institute o f Health Sciences (IA C S ) Zaragoza 50009. Spain *[email protected] es i[[email protected] es

The transition from a fragmented landscape of information fields towards a consistent disciplinary body or unified “information Science” is discussed. Arguably, this transition from múltiple scarcely interconnected fields, unrelated if not contradictory with each other, cannot be achieved by simply extrapolating from one of these fields. The possibility of a previous change in the “mode of thinking” about information has to be reckoned with. Herein, we try to advance ten basic principies, understood not in a strict axiomatic way, but taken as crucial interconnecting points that may contribute to establish both a new direction of advancement and a central goal for the cohesión of the new information Science. Basically, what these principies attempt is to establish an essential connection with the humanities: the life cycle emerges as the crucial pillar of that tentative conceptual bridge.

Introduction: W hat Is to Be Done in Information Science? Th ^ e present contribution does not pretend to add anything substantial many existing compilations around information, to the study of s historical-epochal changes, or to the present multiplicity o f socialnoiogical approaches and the ongoing formal unification attempts. o£ ein’ goal is akln to establishing the layout o f a future articulation connective elements. Rather than starting from a very important or a 443


P. C. Marijuán & J. Navarro

very rigorous domain of knowledge, say from Shannon’s theory, dynamic systems theory, thermodynamics, set theory, or formal symmetries, we are attempting a new “mode of thought” about information so that it may naturally connect with the nucleus of the humanities. Philosophically, this contribution is inspired by the unfinished work of philosopher Ortega y Gasset: “The idea of principie in Leibniz and the evolution of deductive theory” (posthumously published in 1958); see his Complete Works [Ortega y Gasset, 2004-2010]. Tw o particular concerns of Ortega’s work are seminal in the present attempt: the “mode of thought” and the very “idea of principie” . On a personal basis, an important stimulus to develop these insights was the last IS4SI & FIS Conference in Stockholm (2017), specifically a round table devoted to the “ecology of knowledge.” Later on, an intense discussion devoted to these ten principies in the foundations of information Science (FIS) list has provided a series o f valuable comments and criticisms — some of them are included herein. One of the advantages of a new discipline is the simplification of discourse, the creation of a new conceptual space where one can easily build new knowledge without copious management o f other unnecessary, circumstantial ideas that might have been important to arrive at the starting point, but thereafter have becom e unnecessary and even a mental burden. We may consider the famous quotation from Whitehead [1911, pp. 41-42] about the “mental liberation” that implied the use of zero in arithmetics. “ Civilization advances by extending the number o f important operations which we can perform without thinking about them . Operations o f thought are like cavalry charges in a battle — they are strictly limited in number, they require fresh horses, and must only be made at decisive m o m en ts”.

Something similar to the arithmetic invention of zero may be needed nowadays concerning the inconsistent wide-reaching domains of informa­ tion. Ideally, a new way of thinking starting from specific information prin­ cipies could libérate our limited intellects to more Creative endeavors. But information Science looks very different from other conventional Sciences, indeed far from the consistency of mathematics (geometry, arithmetic, alge­ bra) or from physics; it is too multifarious in its appearance, elements, concepts, and theories — and even worse, it can cavalierly jump from scale to scale.

Taking the idea of information principies seriously would demand some previous discussion on principies. W hy do we need “principies at all? Responding factically and immediately: because of our cognitive

Ten Principies of Information Science


limitations. An infinite intellect would traverse all spans of knowledge without any discontinuity — presumably. In our collective scientific enterprise, however, we have to create specialized disciplines in order to share understandable discourses amongst the individuáis of each thought-collective [Marijuán et al., 2012]. As knowledge accumulates and adds more and more complexity within each discipline, particularly in the encounter with unexplained facts and in the cross-fertilization with other disciplinary discourses, the inner epistemic distances grow and grow, so that in due time the original discipline will get fragmented and a new subdiscipline will emerge tended by a specific community of practitioners [Kuhn, 1962]. That new discipline will start, then, a fresh new discourse, with its own set o f principies, its own specific theories and empirical facts, notwithstanding the essential implicit or explicit loans from its parent branch. In the scientific discourse, principies are essential ingredients to give logical consistency to new directions of thought and to explain new achievements. Often, they are established postfacto , in order to reconstruct the path towards the new stuff which has been found, so as to explain it with more logical rigor or to justify the novel formal expressions utilized. This is the instinctive reasoning in Science. Towering “principled” scientific works of utmost historical importance were developed by Euclid, Archimedes, and Newton. They constituted the definite paradigm o f classical Science. In m ód­ em Science, principies have been understood as akin to the “axiomatic” approach, giving raise to seminal discussions in the philosophy of Science, and empowering the development of numerous branches in logical, computational, mathematical, and physico-m athem atical domains, really the heart of deductive Science [Suppe, 2002]. Nowadays, with disciplines and subdisciplines numbered in the thousands [Klein, 2004], the reliance on principies may be found anywhere. In Ortega’s views, a principie is just a beginning, the first element of a conceptual series. In order to be established, usually accompanying or consolidating some new mode of thought, they should be evident (intuitive) and fertile — useful for guiding further construction, for verification, or for Proof. But principies championing a new mode o f thought would not automatically equate with principies of a new Science [Goranson, 2017; Brenner, 2017], and this is a nuclear question. Precisely, Ortega accuses Leibnitz that bekig the Champion of principies in Science, he becomes fragmentary and ^ystematic in his meta-scientific “mode o f thought” : the hypersystematic expresses himself fragmentarily (Ortega dixit). It is curious that along the


P. C. Marijuán & J. Navarro

survey of principies in Ortega’s book, the most frequent interlocutor is not Leibnitz, but Aristotle. Although Husserl, Heidegger, Descartes, Pappus, Plato, Suarez, Spinoza, and other big ñames o f philosophy also appear, his main concern is discussing Aristotle’s view o f specialized disciplines starting from their respective principies, empirically-sensuously obtained and “uncommunicated” in between the different fields. En passant, let us remark the meta-scientific term used by Ortega. If the principies o f different disciplines are factually uncommunicated, the information science’s view o f a new b ody o f knowledge running across vast scales is caught into a difficult “principled” position. W hat could be the role of informational principies — or better meta-principies — in the formidable variety o f domains that runs from the microphysics and the quantum to the cosmological, from the biomolecular to the organismic, from the neuronal to the behavioral and psychological, and from the indi­ vidual to the social in all its manifestations o f the economic, politic, and communicational? We postúlate the existence of a singular element — the life cycle — that has the capability to organize the new scientific discourse on information and nucleates the new mode o f thought. It becomes central per se in the biological, and also in all manifestations of the social. It has remarkable philosophical depth; and it is also physically explorable. In the set of prin­ cipies that will follow herein, the life cycle allows the Progressive entrance o f other essential concepts that accompany information — communication, meaning, knowledge, intelligence. . . The present set o f principies is suscep­ tible of a double reading, downwards and upwards; and in the middle, the life cycle would stand as the fundamental source/sink, emitter/receptor, and essential organizer of the informational way o f being in the world [Marijuán et al., 2015]. These principies also are parsimonious, for very few new terms — if any — are introduced. Notwithstanding that, ampie parts o f the conceptual spectrum related to information are covered. As can be expected, the development o f this informational thinking resonates with fundamental philosophical discussions — actually disentangling information Science from information philosophy would be a hard enterpnse in the present stage [Wu, 2012]. However, the principies herein presented are slanted towards scientific practice — to justify it, to stimulate it, and to bring it together cohesively [Yan, 2017]. Rather than targeting specific realms for ad hoc discussion and sepárate conceptual development, these information principies should be taken as “portáis” that try to interconnect essential topics in between disciplines o f different existential layers usually


Ten Principies of Information Science

considered in mutual isolation. At the same time, they try to be consistent with each other and provide a coherent visión of the information world.

2. Ten Principies of Information Science 1. Information is information, not matter or energy. 2. Information is comprehended into structures patterns, messages, or flows. 3. Information can be recognized, can be measured, and can be processed (either computationally or non-computationally). 4. Information flows are essential organizers of life’s self-production process — the life cycle — anticipating, shaping, and mixing up with the accompanying energy flows. 5. Communication/information





underlie the complexity of biological organization at all scales. 6. It is symbolic language that conveys the essential communication exchanges of the human species — and constitutes the core of its “social nature.” 7. Human information may be regularly converted into efñcient knowledge, by following the “knowledge instinct” , to be further buttressed by applying rigorous methodologies.

8. Human cognitive limitations are partially overeóme via “knowledge ecologies” ; where knowledge circulates and recombines socially, in a continuous actualization that involves “Creative destruction” o f fields and disciplines. 9. Narratives emerge as encapsulated forms of human communication, underlying the intricacies of social relationships, of economic organi­ zation, and the very structures of political power.

10. Information Science proposes a new, radical visión on how information and knowledge surround individual Uves, with profound consequences for scientific-philosophical practice and for social governance.

Discussion There is some symmetry in the distribuí ion of the above principies, with half of them devoted to natural Sciences and the other half devoted to social Sciences and humanities. Each one contains different thematic blocks °f interrelated principies. These blocks will be very briefly discussed in what follows — indeed they deserve far more extensión, but it is beyond the possibilities of these brief, preliminary considerations.


P. C. Marijuán & J. Navarro

The first block, with three principies devoted to information Processing, starts with a tautology, a famous one by Norbert Wiener [1948]. W hy do we start with a tautology? Although it has been stated that

“th e d efin itio n of

i n f o r m a t i o n is th e real fo u n d a t i o n o f in f o r m a t i o n S c i e n c e ”

[Zhong, 2011],

the definition task supposes a long controversy that has been unwinding from the very beginning of modern information conceptualizations. Something, like a cottage industry, has been developing around the definition of information during the intervening decades — A. M. Schrader [1984] found seven hundred definitions of “information Science” between 1900 and 1981, and described the general State of affairs as one o f “conceptual chaos” [Hustvedt, 2016]. Things have not much improved afterwards, although the burden has been displaced to try to define information itself, again done differently in several hundred attempts [Lenski, 2010]. Struggling to define information universally is akin to looking for the “red herring.” Nevertheless, the factual undefinability of this

rela tiv e

term, describing a p oten tia lity

and not a substance, does not mean that we must condemn it to obscurity or to the ineffable — for useful working notions can be crafted to be applied in different domains [Marijuán


a/., 2015]; in particular, the

not ion of “distinction on the adj acent” has been proposed by this author. Actually, the first three principies try to sidestep that definition obstacle by repeating W iener’s tautological statement and by establishing that in spite of the lack of a universal definition of information, one can see its manifestations under different forms or regimes, so that it can be detected, checked, altered, counted, processed, copied, etc. It is like in the case of time in physics; we cannot define time, but we can properly measure it and can use it as a fundamental variable of physical equations. One of the main differences in the present case is the towering importance of the subject attached to information, which has been left in the shadow, unmentioned, although it is essential to establish information processes in general nonanthropomorphic settings. The subject will reappear in later points related to the life cycle. Further directions of thought are open in connection with this first block: information physics, involving the particular case of physical entropy, and the relationship of information with computing [Rosenbloom, 2013; Dodig-Crnkovic, 2017]. At stake is whether information could be the most fundamental constituent of physical existence — with matter/waves, forces, and physical laws being but different manifestations of a fundamen­ tal information “stuff” that is somehow com puted [Davis, 2010]. About the relationship of information and entropy, the confusión is not so entrenched nowadays [Arieh, 2012]: a Shannon’s type o f expression achieves higher physical generality than the M axwell-Boltzm an’s classical approach.


Ten Principies of Information Science

The next block, which comprises just two points, relates to the emergence of the

Ufe c y c le

and the occurrence of information flows as well as

the communication exchanges. Once the life cycle is evolutionarily effective, we may properly speak about an “informational way of existence” ensconced on the singularity of living beings. These genuine informational entities, the existence of which depends on a special relationship with the environment, are able to continuously distinguish — say — energy flows from information flows, intertwining both kinds o f flows along their own survival and maintenance processes. An excellent parallel could be made with Harold M orowitz’s [1968] study on the energy flow in the biosphere — unfortunately the corresponding study o f the information flow is a blatant absence. Geoffrey W est’s [2016] work on the arrangement o f scaling entities provides an interesting macro-perspect on the organizational similarities of cells, organisms, enterprises, cities___ Although the work is highly integrative, it does not consider the information background o f the different classes of organization and how they rely on signaling exchanges, massive communication, and the generalized intertwining o f energy flows and infor­ mation flows. The

cellu la r

life-cycle becomes the true information paradigm, for it

is the closest organizational realm the dynamics o f which we can fully acknowledge at the molecular scale — almost completely. Also, it is the most strategic theater where we can establish a series o f essential concepts that provide full explanatory power to information: first the flow



then the genomic stock of molecular m eaning

k n o w le d g e ,

the molecular fabrication of

(via gene expression and translation), the arrangement of cell-cell

co m m u n ica tio n ,

the full deployment of cellular

2015], the true multicellular cell cycles, the % and

in fo r m a tio n

a/., 2017a] as detected by the cellular signaling system,

c o o p e r a tio n

c o m p l e x it y g ro w th

e v o lv a b ility ,

in te llig e n c e




via synchronization o f individual

and the enhanced epigenetic

a d a p ta bil-

and so on. In comparison with inanimate matter, this

aiultiplication of capabilities is astonishing. It results from a unique inforraational arrangement: a population of active elements which are coded mto the múltiple variations of a permanent repository that gets continu°usly translated and copied by those active elements themselves, becoming finally selected by the environment — recursivity at its best. Because of this information-based arrangement, which is grounded on the specificity °f m olecu la r

r e c o g n itio n

and on the interplay of heterogeneous

in fo r m a tio n a l

arch itectu res ,

the self-producing entity remains open to tiny signáis from the environment and can change adaptively its ongoing life-cycle processes i anjuán


a/., 2015; 2017a]. Thus, when a cellular agent communicates


P. C. Marijuán & J. Navarro

with some other cellular agents, the available tools are signáis that are conveying meaning to the receivers: what these signáis actually mean are “missing portions” or functional voids of the emitter life-cycles which have to be solved and fulfilled cooperatively — i.e., as multicellular functions to be performed by specialized tissular populations. Formalizing the individual life cycle is quite problematic, but signaling the ongoing “absences” so that collective responses/solutions may be regularly obtained, dissipates eons of com plexity effectively. Thereafter, those individual life cycles became the general sources and sinks o f the massive information flows associated with problem-solving within the aggregate entity. Presumably, something funda­ mental could be learnt about this bio-informational way o f existence to be extended towards the social realm and perhaps also to physical quarters. There is a com mon informational philosophy o f organization based on distributed self-production which is activated by information propagation. As Michael Conrad [1998, p. 108] put it: “when we look at a biological system, we are looking at the face o f the underlying physics o f the universe”.

Going to the further block, after the incredible complexification of life, the emergence o f central nervous Systems, the massive brain corticalization processes, and so on and so forth, and we, the improbable, the unexpected, have arrived. Like our humble bacterial ancestors, we have to confront the world for our individual living, being regular ly immersed into the quasiinfinite information flows o f the natural environment and o f the social environment. Again, life — human life — has to be incor por ated as the starting point of communication. It does not mean “biology,” rather it is each one’s biography — culturally, historically, and evolutionarily situated — which becomes the fundamental background of interpersonal communication. At the end, all humans have similar sensorimotor apparatuses that provide the com mon ground for communication, for pointing out those missing portions or absences or needs in the advancement o f their own life courses. But this time, by means o f language, acting both as a new social commu­ nication tool and as an open-ended symbolic system, our collective capabilities o f being in the world and to relate with each other have boomed. Subsequently, our individual uknowledge instinct” [Perlowsky and Kozma, 2007] has been enormously amplified within the social matrix. Historically» we have been able to gradually develop those social repositories or stocks o f knowledge we cali Science and all kinds of accompanying technologi tools that allow us a new contemplation and action onto the world arou ^ Now, we can sense the most remóte perceptions, we can colligate them the different disciplines, and produce adaptive [or non-adaptive] responses,

Ten Principies of Information Science


with supposedly the final goal of advancing our Uves, both individually and collectively. An “ecology o f knowledge” [Zong, 2011], where múltiple disciplines mix and recombine their contents, has been taking shape with increasing complexity. All of this is but a way to overeóme the cognitive limitations of each subject. For, the social creation o f knowledge, and the growth of all kinds o f Science, finally derive from knowledge recombination processes taking place in the cerebral workspace o f individuáis [Dehaene, 2009]. The strict conditions put by the scientific method would represent the ways and means to directly interconnect standardized individual perceptions and actions beyond time, space, and cultural limitations, allowing the social decomposability of problems and the occurrence o f knowledge recombination dynamics at a global and intergenerational scale [Marijuán et a/., 2012]. This multidisciplinary process o f knowledge generation, with

emphasis in com binatory processes, was intuited by the medieval thinker Raimundus Lullus, who dubbed it as the intellectual “A rs M agna” . Entering into the final block of principies, we confront a difficult question: what is the extent to which “narratives” should occupy a central role in establishing coherent processes of social communication and cooperation? The ultimate challenge is to go beyond the preconceptions and premises of strict rationality, either in social communication or in economic action or in the political organization o f society. Although we have a social nature, indeed a “sociotype” [Marijuan et al., 2017b] basically realized by talking, by bonding via informal conversation, crucial questions such as H ow much do we speak? and With w hom ? remain factically unanswered. It is the allure

of the formal structures o f language [Chomsky, 1957] that has obscured the study of the fundamental communicative necessity: conversation as an intuitive practice to cement social bonding [Enfield, 2017], to serve as a new form of “virtual groom ing” [Dunbar, 2004; Navarro et al., 2016], and to exchange the meaningful experiences o f daily life. Rather unexpectedly, and very cióse to the previous criticism, “narratives” appear to be a central focus for critics of orthodox thinking in economic theory and political theory5as noted in a relevant critical work o f two Nobel laureates in Economics [Akerloff and Shiller, 2015]. Again, the allure o f formalizable constructs has °bscured the in-depth study o f the essentially “relational” phenomena that sustain our social life. Restating the problem in our own parlance: How can ^ r e la te narratives to the regular advancement o f individual life eyeles? us try it. We may consider narratives as the higher-level architectures organized by our minds in order to articúlate meanings, to consolídate ’ and to share them among the members o f our social groups. From


P. C. Marijuán & J. Navarro

the microscopio molecular elaboration of intracellular meaning by each neuron within the continuous adaptation of its synaptic arborization structures, there would emerge further processing rhythms and interconnected layers of neuronal organization that are evolutionarily assembled so that individuáis can finally behave ecologically and adaptively in the real world — under the conditions o f their bodily physiology and the recurrent ecological affordances. For any individual fully participating in the social life around, all they can come across fundamentally is but other individuáis’ life cycles, ceaselessly. It is a full “sociotype” of interrelated individuáis engaged in coalitions and competitions, continuously communicating and acting, endlessly focusing themselves on thinking and talking about others — along the common events and happenstances of the colligated lives. The most important ecological events in any life cycle are those that mark age-transitions and changes of “social state” , plus all those that mobilize fundamental emotions, the core of life cycles. Accordingly, there are not so many essential narratives to tell [Booker, 2004]; in spite that the open-ended embroideries o f language and the cornucopia of imagination apparently result in infinite stories [Tobias, 1993]. But there are bad stories and good stories. Good stories are those that have a well-defined structure o f meanings [Olson, 2015] so that they grab listeners’ attention and can be widely shared. These widely shared narratives, by configuring our aspirations and valúes, sitúate us into the reaches of society, where they oriéntate our thoughts and our actions [Bruner, 1998]. Thereafter, coupled with the ostensible bias of our personal appreciations [Khaneman, 2012], the apparently detached, rational decisions of economics and politics become completely ensnared into the network of shared meanings and narratives, where “phising

fo r


has a towering presence and pushes towards its own kind of economic and political equilibrium [Akerloff and Shiller, 2015], certainly away from the dictates of the traditional, orthodox theories. Indeed, the deep relational structures of the human life-cycle transcend the pretended rationality of abstract economic agents and politic agents. In a general sense, given the density of information exchanges that accompany our social life, it is no wonder that the biggest global changes of societies along history have always been induced or accompanied by substantial changes in the information and communication environm ents around individuáis: writing, códices, printing press, books, newspapers, neW media, computers, internet, mobiles, social networks... Human soC^ ^ have always been “information societies” [Hobart and Schifman, ’ Wright, 2007; Poe, 2011]. In this respect, the current accelerationof arti c

Ten Principies of Information Science


Information flows represents a challenge regarding the most natural information flows (face-to-face conversation) so ingrained in our social and psychological adaptations and in our personal lives. Paradoxically, in the “information society” , mental health and wellbeing problems are steadily mounting as public health concerns: social disintegration, escalation of depression and suicides, psycho-immune and pain diseases, obesity epidemics, plus other new de-socialization pathologies that are accompanying the techno-globalization process and the growth o f inequality. Blinded by the promises of global big data, we barely recognize the perils and pitfalls of that intangible “social information” stuff — highly valuable, but dense, problematic, and fragüe in so many ways. The advancement of social information Science is really imperative for a more enlightening and robust “ecology of knowledge” in our times.



The new kind of thinking to promote around the informational “looking at the world” would demand a new kind of “observer” , starting from a differentiated set of principies of observation, sidestepping the worst conceptual problems and allowing the development o f a fresh, new scientific-philosophical thought. In this too brief a discussion, we have barely outlined some strategic directions of advancement, most of them empirically oriented. Probably, the parallel realization of a theoretical synthesis incorporating a new stock of scientific concepts (admittedly, most of them yet in the making) would be necessary [Burgin, 2010], or at least the making of a compendium on the numerous theories and conceptual developments around already existing information. Problems related to information percolate in a number o f disciplines: physics, computing, artificial intelligence, cognitive Science, biology, neuroscience, social Science, communication studies, economics, politics, etc. It is not a series of coincidences: it points to an inadequate articulation o f some hasic interpretive concepts that have been tweaked in so many ways. The visión of a renewed information Science could be supportive in most those disciplines — there is no need to “reinvent the wheel” everyere. Or at least it can be useful to advance toward similar conceptual ^tions in a few central disciplines [Yan, 2017]. At the end, a more congealso anC* e® c*ent aPProach to our “natural intelligence” limitations would ecol erne^ e’ emPowering the individual and social handling o f “knowledge


P. C. Marijuán & J. Navarro

The quest for meaning permeates human lives and social narratives. At stake is whether adequately centering the spectrum o f information phenomena upon the life cycle would contribute to fill in some o f the essential gaps between natural Sciences and humanities. W hether the “cycle” can be meaningfully incorporated in physical explanation becomes another matter [Josephson, 2017].

Acknowledgm ent The authors thank the colleagues of FIS Discussion List (Foundations of Information Science), for many years o f companionship, inspiration, and endurance.

Bibliography Akerlof, G. A. and Shiller, R. J. (2015). Phishing fo r Phools: The Economics of Manipulation and Deception. Princeton University Press, Princeton. Arieh, B. N. (2012). Entropy and the Second Law. World Scientific, Singapore. Booker, C. (2004). The Seven Basic Plots: Why We Tell Stories. Bloomsbury, London. Brenner, J. (2017). Principie of IS. Discussion List: Foundations of Infor­ mation Science (FIS), https://www.mail-archive.eom/[email protected]/ msg03468.html (accessed 15/9/2007). Bruner, J. (1998). Acts o f Meaning: Four Lectures on Mind and Culture. Harvard University Press, Cambridge. Burgin, M. (2010). Theory o f Information: Fundamentality, Diversity and Unification. World Scientific, Singapore. Chomsky, N. (1957). Syntactic Structures. Mouton, The Hague. Conrad, M . (1 9 9 6 ). Cross-scale information processing in evolution, development, and intelligence. BioSystems 3 8 , pp. 9 7 -1 0 9 . Davis, P. (2010). The universe from bit. In: Davies, P. and Gregersen, N. H. (eds.) Information and The Nature of Reality: From Physics to MetaphysicsCambridge University Press, Cambridge. Dehaene, S. (2009). Reading in the Brain. Penguin, New York. Dodig-Crnkovic, G. (2017). Ten principies of information, from yet anot er perspective. Discussion List: Foundations o f Information Science ( ’ https://www.mail-archive.eom/[email protected]/msg03545.html sed 6/10/2017). Dunbar, R. (2004). The Human Story: A New History of Mankind’s Evoluti • Faber & Faber Ltd., London. . RaSic Enfield, N. J. (2017). How We Talk: The Inner Workings of Conversation. Books, New York.

Ten Principies of Information Science


Goranson, H. (2017). Information: Just a matter of math. Discussion List: Foundations of Information Science (FIS), [email protected]/msg03476.html (accessed 17/9/2017). Hobart, M. E. and Schiffman, Z. S. (1998). Information Ages. The John Hopkins University, Baltimore, MD. Hustvedt, S. (2016). The Delusions of Certainty. Hachette UK, London. Josephson, B. (2017). Incorporating Meaning into Fundamental Physics, Univer­ sity of Cambridge Frontiers of Fundamental Physics Conferences. h ttp :// (accessed 29/11/2017). Klein, J. T. (2004). Interdisciplinary and complexity: An evolving relationship. Complexity 6 (1-2), pp. 2-10. Kuhn, T. (1962). The Structure o f Scientific Revolutions. University of Chicago Press, Chicago. Lenski, W. (2010). Information: A conceptual investigation. Information 1(2), pp. 74-118. Marijuán, P. C., del Moral, R. and Navarro, J. (2012). Scientomics: An emergent perspective in knowledge organization. Knowledge Organization 39(3), p p .153-164. Marijuán, P. C., Navarro, J. and del Moral, R. (2015). How the living is in the world: an inquiry into the informational choreographies of life. Progress in Biophysics and Molecular Biology 119(3), pp. 469-480. Marijuán, P. C., Navarro, J. and del Moral, R. (2017a). How prokaryotes ‘encode’ their environment: Systemic tools for organizing the information flow. BioSystems 164, pp. 26-38. Marijuán, P. C., Montero-Marín, J., Navarro, J., García-Campayo, J. and del Moral, R. (2017b). The “sociotype” construct: Gauging the structure and dynamics of human sociality. PLoS ONE 12(12), pp. 1-24. Morowitz, H. J. (1968). Energy Flow in Biology. Academic Press, New York. Navarro, J., del Moral, R. and Marijuán, P. C. (2016) Laughing bonds: A multidisciplinary inquiry into the social information processes of human laughter. Kybernetes 45(8), pp. 1292-3107. Olson, R. (2015). Houston We Have a Narrative: Why Science Needs Story. University of Chicago Press, Chicago. Ortega y Gasset, J. (2004-2010). Complete Works, Obras Completas. Editorial Taurus; Santillana Ediciones Generales, Madrid, erlovsky U. and Kozma R. (2007). Neurodynamics o f Higher-Level Cognition and Consciousness. Springer-Verlag, Heidelberg. °e, M. T. (2011). A History of Communications: Media and Society from the Evolution of Speech to the Internet. Cambridge University Press, Cambridge/New York/Melbourne. °senbloom, P. S. (2013). On Computing: The Fourth Great Scientific Domain. Schrad16 ^ ress> Cambridge, MA. f’ e^’ (1984). In search of a ñame. Information Science and its concep^uPpes^ antecec*ents’ Library and Information Science Research 6, pp. 227-271. p \ i (^02). Representation and Invariance of Scientific Structures. CSLI

^bücations, Stanford.


P. C. Marijuán & J. Navarro

Tobías, R. B. (1993). 20 Master Plots: And How to Build Them. Writer’s Digest Books, Blue Ash, OH. West, G. (2017). Scale: The Universal Laws o f Growth, Innovation, Sustainability, and the Pace o f Life in Organisms, Cities, Economies, and Companies. Penguin, New York. Whitehead, A. N. (1911). An Introduction to Mathematics. London: Williams & Northgate, H. Holt, New York. Wiener, N. (1948). Cybemetics or Control and Communication in the Animal and the Machine. Hermann & Cié, París; MIT Press, Cambridge. Wright, A. (2007). Glut: Mastering Information Through the Ages. National Academies Press, Washington. Wu, K. (2012). The essence, classification and quality of the different grades of information. Information 3(3), pp. 403-419. Yan, X. (2017). Verification of the Principie of Information Science and the Definition of Information. Discussion List: Foundations of Infor­ mation Science (FIS), https://www.mail-archive.eom/[email protected]/ msg03601.html (accessed 19/10/2017). Zhong, Y. (2011). Unity-based diversity: System approach to defining informa­ tion. Information 2(3), pp. 406-416.

Chapter 20

Knowledge Structures and Conceptual Networks for Evaluation of Knowledge Integration

José María Díaz-Nafría*’§, Mark Burgin*’^ and Blanca Rodríguez-Bravo*’H *BITrum Research Group, C/San Lorenzo 2 24007 León, Spain *Department of Mathematics, University of California Los Angeles, CA 90095-1555, USA *Facultad de Filosofía y Letras, Universidad de León 24004 León, Spain §[email protected] es ^mburgin @math. ucla. edu [email protected] The chapter addresses the general problem of assessing the integration of knowledge from different scientific disciplines joined in interdisciplinary settings and its specific application to the study of information. The method is based on the development of Interdisciplinary Glossaries as tools foi the elucidation of the network of concepts involved which also serve as proxies of the corresponding knowledge integration. We show the results obtained from the application of the network approach to a specific interdisciplinary glossary devoted to the study of information. These results show the capacity of the methodology depicted to guide the future development of knowledge integra­ tion by the corresponding interdisciplinary or transdisciplinary teams, as well 88 to assess their integration achievements. However, the results described are rather qualitative with respect to the knowledge integration attainments. In °rder to offer a quantitative assessment, we propose an enhanced methodology


4 58

J. M . Díaz-Nafria, M . Burgin & B. Rodríguez-Bravo

in which each contribution and participant in the elucidation process is identified by the knowledge domains involved using a set of domains adapted from the higher categories of the Universal Decimal Classification. Such Identifica­ tion allows assessing the integration through a multidimensional perspective based on: (i) the diversity of the disciplines involved, measured in terms of Shannon Diversity Index, and (ii) the effective integration achieved through the meeting of different perspectives, measured through the analysis of both the semantic network of elucidated concepts and the network of participant researchers, in terms of the average minimal distance between any two nodes and the clustering coefficient, which are combined through the small-worldcoefficient, a.



The disintegration of scientific knowledge has partially been a consequence of the intensification and widening of the scientific endeavor. Many specialized disciplines aróse in the eighteenth century, in which the intensity required to address specific problems implied professional restraint to restricted areas of scientific knowledge [Porter, 2003]. This more specialized approach resulted in knowledge disintegration and fragmentation. Nevertheless, this was also an effect of the methodological principies with respect to the adequate means for the articulation of such endeavor, which in turn was based on strong ontological assumptions regarding the nature of reality. This approach is explicitly expressed in Descartes’ second rule from the system of four rules that suffice to arrive “at a knowledge of all the things of which [our minds are] capable [...]” . Namely, the second rule instructs: “divide each of the difficulties [...] into as many parts as possible, and as seemed requisite in order that it might be resolved in the best manner pos­ sible” [Descartes, 1952: pp. 46-47]. Indeed, if the complex reality faced by the scientist is difficult to understand as a whole, then its división into small parts allows arriving at a point where the isolated parts can be understood with relative ease. Descartes calis this approach “analysis” in opposition to “synthesis” , reframing their original meanings as stated by Aristotle an praising the former as the sure means to achieve truths [Aristotle, omi and Ross, 1908-1952]. The critical issue is not overlooking some essentia relation between the parts separated in the analysis. Descartes does n^ offer a guide on how to preserve essential relations of the reality under study of the división process. The method he depicts directly goes to a sePj arate and distinct understanding of all parts of the wholes. It is that reality, epistemologically reduced in such a way, is ontologically a

Knowledge Structures and Conceptual Networks fo r Evaluation


When this methodology was generalized from an individual researcher to Science as a whole, the path to its división into specialized disciplines was the natural consequence, despite the concerns stated by a few, and in particular, by Leibniz’s concerns about breaching the necessary unity of Science [Leibniz, 1996]. In the nineteenth and twentieth century, this división of Science into sepárate disciplines grew to a much larger degree. However, the concerns on the mutilation of fundamental relations through the process of fragmentaron of reality were growing since the second half of the twentieth century. Appeals for reunification of Science aróse in different arenas caused by the necessity to address the fundamental complexity of the reality and the problems to be solved. The emergence of information theory, Systems Science, cybernetics, and the broad quest for interdisciplinarity belong to this trend [Frodeman et a/., 2010; Díaz-Nafría and Salto-Alemany, 2011; Burgin and Hofkirchner, 2017]. The relevance of this concern can be also observed in the declarations and efforts devoted by international institutions, such as UNESCO and OECD, since the 1970s to merging scientific disciplines into integrated frameworks. However, despite the national and international efforts to boost interdisciplinary research in the past decades, one of the fundamental barriers for its establishment has been the lack of assessment criteria of interdis­ ciplinarity itself [Frodeman et a/., 2010; DEA-FBA, 2008; EURAB, 2004]. This brought the scientific community to the following questions: How is it possible to measure the effort of merging diverse knowledge? How is it possible to assess the quality of the knowledge integration achieved through interdisciplinary settings? This “lack of appropriate quality criteria introduces a remarkable degree of uncertainty in the evaluation of interdisciplinary research” [Frodeman a/., 2010: p. 316] often causing research proposal assessment to be inefficient and disregard promising interdisciplinary research projects, mainly due to the application of disciplinary criteria. For this reason, the development of assessment criteria has been one of the objectives marked by National and international research funding agencies [DEA-FBA, 2008; 2004]. This problem is addressed in our work, based on the study knowledge structures and a network theoretical approach to knowledge t^creatioH is specifically applied to the interdisciplinary study of informa°n. This approach serves to embark upon a meta-theoretical inquiry of sessmg the diversity and intensity of knowledge integration. ductio6 C^a^ter ^as following structure. In Sec. 2, right after the Intro’ We C hórate a methodological base for knowledge integration


J. M . Díaz-Nafría, M. Burgin & B. Rodríguez-Bravo

and build a mathematical model of conceptual integration. According to methodology of Science, concepts belong to the basic level of advanced knowledge systems. Naturally, they allow extended knowledge representation due to their intrinsic structure. That is why in Sec. 2.1, we give a brief description of knowledge structures representing big domains of reality. In Sec. 2.2, we show how these big knowledge structures are mapped onto conceptual systems. In Sec. 3, we adopt a network perspective in order to map the dynamics of knowledge co-creation, particularly focusing on interdisciplinarity and its various levels. Based on this approach, we present in Sec. 4 a methodology to assess knowledge integration through interdisciplinary glossaries as proxies of the integration achieved in interdisciplinary settings. In Sec. 4.2, we discuss the results of applying this methodology to an interdisciplinary glossary in the field of information studies. In Sec. 5, we develop an improved methodology based on the evaluation of the discipline diversity and the intensity of knowledge integration observed in interdisciplinary glossaries. In the last section, we discuss the obtained results and possibilities of their more advanced applications and developments.

2. 2.1.

Structural Perspective on Knowledge Integration Megalevel structures o f knowledge

Comprehensive knowledge systems about big domains of reality are called megalevel structures of knowledge [Burgin, 2017]. The most explored megalevel structures of knowledge are scientific theories, structures of which are studied in the methodology of Science. Many researchers studied innei structures of scientific theories building their models, which are often called reconstructions, and testing their validity by application to existing scientific theories. The most popular is the standard (positivist) model (reconstruction) of a scientific theory, which utilizes means of logic representing a scientific theory as a system of propositions (cf., for example, [Suppe, 1999. pp. 16-24]). Another popular approach to description of the scientific theory structure is the structuralist model (reconstruction) of a scientific theory (cf., for example, [Balzer et a/., 1987]), which utilizes means of set theory representing a scientific theory as a system of models of the theory domain. Some researchers treat scientific theories as devices for formu and resolving scientific problems. In this context, they model scie

Knowledge Structures and Conceptual Networks for Evaluation


theories by Systems of statements and questions (problems) including (in some models) various forms of problem representation, rules and heuristics for resolving problems and utilizing erotetic logic for rigorous analysis of problems and problem-solving (cf., for example, [Garrison, 1988]). In his model, Thagard [1988] represented a scientific theory as a highly organized package of rules, concepts, and problem Solutions. All these and some other approaches were unified in the structurenominative model or reconstruction of a scientific theory, which was the first methodological and mathematical model of comprehensive knowledge Systems [Burgin and Kuznetsov, 1994]. As a result, other models of theoretical knowledge that describe the inner structure of big knowledge systems, such as scientific theories, became subsystems of the structure-nominative model of scientific knowledge (a scientific theory) and all structures used in those models are either named sets or systems of named sets [Burgin, 2011]. For instance, the structuralist model of a scientific theory (cf., for example, [Balzer et a/., 1987]) is represented as the model-representing subsystem of the structure-nominative model, while the standard (positivist model) of a scientific theory (cf., for example, [Suppe, 1999]) is represented as the logic-linguistic subsystem of the structure-nominative model. Later, this model was extended and enriched in [Burgin, 2011] forming a higher step in modeling global knowledge. Now, the most advanced is the modal stratified bond model of global knowledge elaborated in [Burgin, 2016], which comprises all other existing models of scientific knowledge systems and other big knowledge systems. According to the modal stratified bond model, global knowledge expands in three dimensions — systemic, modal and hierarchical. The modal d im en sión is based on modalities of knowledge: (1) Assertoric knowledge consists of epistemic structures with implicit or explicit affirmation of being knowledge. (2) Hypothetic or heuristic knowledge consists of epistemic structures with implicit or explicit supposition that they may be knowledge. \ ) Erotetic knowledge consists of epistemic structures that express lack of knowledge. Logical propositions or statements, such as “The Sun is a star” , are im ples of assertoric units of knowledge. Beliefs with low extent of rtainty, i.e. when they are not sufficiently grounded, are examples of taowl d 1C kn° W^ectee‘ Questions and problems are examples of erotetic


J. M . Díaz-Nafría, M . Burgin & B. Rodríguez-Bravo

Knowledge with different modalities forms strata in knowledge Sys­ tems determining the h orizon tal stru ctu re of comprehensive knowledge systems. The h i e r a r c h i c a l d i m e n s i ó n delineates three levels of global knowl­ edge systems: (1) The c o m p o n en tia l level consists of elements, parts and blocks from which systems from the attributive level are built. In some sense, the componential level is the substructural level of a global knowledge system. (2) The a ttrib u ted level reflects the static structure of global knowledge as a system constructed from elements, parts and blocks from the componential level. (3) The

p ro d u ctiv e




of global of global

knowledge knowledge,





means for

knowledge acquisition, production and transmission. Note that, each of these three levels has its strata and sublevéis. Levels in global knowledge systems determine the vertical stru ctu re of this system. Three categories of knowledge form the s y s t e m i c

d im e n sió n


knowledge structuration: (1) D e s c r ip tiv e knowledge (also called d eclara tive knowledge or sometimes p r o p o sitio n a l knowledge) is the knowledge about properties and rela-

tions of the objects of knowledge, e.g. “a swan is white” , or “three is larger than two” . (2) R e p r e s e n ta tio n a l knowledge about an object is the set of representations of this object by knowledge structures, such as models and images, e.g. when Bob has an image of his friend Ann, this image is representational knowledge about Ann. (3) O p era tion a l knowledge (also called procedural knowledge) consists of rules, procedures, algorithms, etc., and serves for organization o f behavior of people and animáis, for control of system functioning and for performing actions. As

we can see,



big domains

is also big aíl^

diverse.a However, it is usually represented as conceptual systems c

aIt is possible to read more about modeling global knowledge system s [Burgin, 2017]

in the book

Knowledge Structures and Conceptual Networks fo r Evaluation


encyclopedia, encyclopedic dictionaries, thesauri and glossaria. This representation is based on conceptual integration of knowledge, which is formalized in the next section. 2.2.

C onceptual in tegration o f know ledge

Representation of knowledge structures by conceptual systems is a mapping c 0f a knowledge structure (system) K into a conceptual system C and this mapping c: K —» C is called a conceptualization mapping of knowledge K. However, any mapping in a complete form is a named set [Burgin, 2011]. This gives us the following definition. Defínition 2.1. The named set (K , c, C ) is called a conceptualization of knowledge K by the conceptual system C. For instance, the general theory of information [Burgin, 2010] as a knowledge system K can be represented by the system C of concepts, which inelude such system concepts as information, principies of the general theory of information, infological system, statistical information theory, semantic information theory, algorithmic information theory, dynamic information theory, and so on. Whenever this is possible, the conceptual system C can be regarded as a transáisciplinary setting as we will refer to it in Sec. 3.2. Definition 2.2. When knowledge from different systems is mapped into one conceptual system it is called conceptual knowledge integration. For instance, it is possible to take several information theories, e.g. statistical information theory, semantic information theory, algorithmic information theory and dynamic information theory (cf., [Burgin, 2010]), and conceptualize them using one common conceptual system C. Definition 2.3. A conceptual system consists of concepts and relations between them. When we abstract the conceptual system from its role of conceptualization of knowledge referred above (Definition 2.1), we can regard it as a network of concepts as we will do in the following sections. There are three types of concepts in a conceptual system: Systemic (or primary) concepts form sepárate knowledge Ítems and have (2) ^eSCr^pt*ons (definitions). Emphasized (or secondary) concepts are concepts used in descriptions (3) °b S^Stem^C concePts and have descriptions (definitions). "ground (or tertiary) concepts are concepts used in descriptions of systemic concepts and do not have descriptions (definitions).


J. M. Díaz-Nafría, M. Burgin & B. Rodríguez-Bravo

Concept Ñame Fig. 1.

________________________________________ ^

Conceptual Representaron

The first specification rank of the representational model of a concept.

To build a mathematical model of conceptual knowledge integration, we use the representational model of a concept introduced in [Burgin and Gorsky, 1991] and further developed in [Burgin, 2016]. Its surface structure is a specific kind of named sets or fundamental triads [Burgin, 2011]. It is presented in Fig. 1, in which concept ñame can be one word, e.g. “information” , an expression, e.g. “structural information in a Computer” , or a text, e.g. a set of postulates describing information as in [Burgin, 2010]. It is demonstrated that the representational model of a concept comprises all other models of a concept as a structure having higher level of abstraction [Burgin, 2016]. For instance, to get Frege’s model of a concept [Frege, 1891; 1892a,b], it is possible to consider the components Denotation and Sense as the conceptual representative of the concept. In a similar way, to get Russelhs model of a concept [Russell, 1905], it is possible to consider the components Denotation and Meaning as the conceptual representative of the concept. Here, we divide the conceptual representative into three parts — the domain, meaning and representation: (1) The concept domain is the domain of reality described by the concept. It corresponds to the Denotation in the sense of Frege [1891; 1892a] and Russell [1905]. (2) The meaning of a concept C is knowledge about the concept domain D e •This knowledge is called the broad-spectrum concept knowledge. All knowledge about the concept domain is called the abundant domain knowledge. Meaning corresponds to the Sense in the sense of Frege [1892b]. (3) The representation of a concept C consists of different representations of knowledge about the concept domain D e • For instance, if the ñame of the concept is information, then an article about information in an encyclopedia or a dictionary is a representado^ of the concept information. This shows that one concept can have ^ representations, while the unión of concept representations is also a r sentation of this concept.

Knowledge Structures and Conceptual Networks for Evaluation

4 65

At the same time, in a conceptual system, the meaning of a concept is also formed by the description (definition) of this concept in the considered conceptual system. These descriptions and definitions represent the components of the ampie knowledge in the same way as a map represents the corresponding terrain. This situation is represented by the contraction conceptual diagram (1), in which p is a knowledge projection.


Broad-spectrum Concept Knowledge



Conceptual Description/Definition

Taking a conceptual system C and combining all diagrams of the form (1) corresponding to the systemic concepts from C, we obtain the broadspectrum knowledge BK as the unión of all broad-spectrum concept knowl­ edge Ítems of all systemic concepts from C forming the conceptualization diagram (2), which is a named set (BK, p, C ) in general and a fiber bundle with the projection p in particular. Broad-spectrum Knowledge (BK)

1 P


Conceptual System (C) This diagram represents a conceptualization of the broad-spectrum knowledge BK by the conceptual system C. Conceptual Systems are often represented by conceptual networks, which show explicit connections and ties between concepts from the system. Connections and ties between concepts consist of connections and ties between elements and components of these concepts. When we wish to stress the dynamical aspects of the conceptual system \ r instance, in case of the theoretical transformations on which Kuhn or akatos were primarily focused [Kuhn, 1970], [Lakatos, 1978]) these can rnther be seen as networks abstracting the functional role in the conceptu^ a ion of knowledge, as mentioned above. For these conceptual networks, set ^ an° ^ er named set worth considering: the nominalization named tion ' rePresented by Diagram (3) characterized by the projecis r 1S re^ ey X 0 0 0 0




























y x ^ y x Vy 0



->y x = y ->y y —»■ X

-> x

X —> y






















1 0










—i x V


1 0

1 1




1 1 i i

The two-valued binary neuron (perception) model (Fig. 5) can be used to simúlate the 16 types of information processing (transformation) modes by changing the internal State parameters a, b, e, as detailed in Table 4.

The internal s truc ture of two valued neurons Fig. 5.

Two-valued binary neuron (perception) model.

Second, the base model can inherit the completeness in the two-valued information processing at 0, 1 endpoint. The new logical operation type brought by the presence of intermediate transition valúes can be compensated by the average operator and the combination operator. It will be proved later that the adjustment function corresponding to various uncertainty parameters ensure that the processing o f the intermediate transition valué x £ (0,1 ) is complete (see Fig. 6).

3 .4 .

F i n d th e b a se m o d e l o f fle x ib le p r o p o s itio n a l logic

The results show that there are five kinds of uncertainties in the flexible propositional logic operator, except for the uncertainty x , y , z € [0> ^ 0 the flexible proposition itself, also including the uncertainty of the propo sition truth valué error k £ [0,1], the uncertainty of generalized correlation between two propositions h £ [0,1], the uncertainty o f relative between two propositions ¡3 £ [0,1], the uncertainty o f the true and ase thresholds o f the proposition e £ [0,1]. These uncertainties will affect

The 16 State parameters in two-valued binary information processing. All 16 types of State parameters of information processing (transformation) mode



x Ay

x A —>y













-1 0








x Vy

—>x A ->y





















■^y 0










-1 0 -1



-1 1 -1


—>x V

—i y








Universal Logics for Intelligent Information Processing

Table 4.





“\ a x


cell wall


x input






y_ t


x delay A t

t riiv:

T T ^ z

w h e re

tf(x, * ) =


= max(0, x + y - 1 )

= m in(l, x + y ) Implication /(x, y ) = m a x (z]y ^ T(x, z)) = m in(l, 1 - x + :y ) Equivalence