1




   Info-Computationalism and Philosophical
           p                         p
   Aspects of Research in Informat...
2



What is Science?
How did Sciences Develop?




 Eye
                            2
 Maurits Cornelis Escher
3




The Mytho-Poetic Universe
     y
Mytho-Poetic Universe of Egypt           Hindu Mytho-Poetic Universe




  In ancie...
4




 The M h i l U i
 Th Mechanical Universe
The Medieval Geocentric Universe   The Clockwork Universe




             ...
5




The Computational Universe

                We are all living inside a gigantic
                  computer. No, not ...
6




    The Computational Universe

                                         Konrad Zuse was the first to suggest (in 19...
7



The Major Paradigm Shifts in our View
of the Universe



                        (Classical)   Info-
                ...
8




    The Classical Model of Science
    The Classical Model of Science is a system S of propositions and
    concepts...
9




    The Classical Model of Science
    There are in S a number of so-called fundamental propositions
               ...
10




               The Classical Model of Science
               All concepts or terms of S are adequately known A non-...
11


                     The Scientific Method
EXISTING KNOWLEDGE
THEORIES
                                              ...
12




Natural Philosophy
Natural philosophy or the philosophy of nature (Latin philosophia
   naturalis),
   naturalis) i...
13




Info-Computationalism
        p
Information and computation are two interrelated and mutually defining
       p
   ...
14




  Information

                                         A special i
                                               ...
15




“IT IS TEMPTING TO SUPPOSE THAT SOME CONCEPT OF
INFORMATION COULD SERVE EVENTUALLY TO UNIFY MIND,
MATTER, AND MEANI...
16




Computation
       The Computing Universe: Pancomp tationalism
           Comp ting Uni erse Pancomputationalism


...
17



Computing Nature and
Nature Inspired Computation
                                                              Natur...
18




 Turing Machines Limitations –
 Self-Generating
 Self Generating Living Systems
                       Complex biol...
19




Beyond Turing Machines
  y         g
 Ever since Turing proposed his machine model which identifies
   computation ...
20




Beyond Turing Machines
  y         g

 The challenge to deal with computability in the real world (such as
   compu...
21



Correspondence Principle
picture after Stuart A Umpleby
                     A.
http://www.gwu.edu/~umpleby/recent_p...
22



Computability Theory
Barry Cooper




http://www.amsta.leeds.ac.uk/~pmt6sbc/
23


 Info-Computationalism Applied:
 Epistemology Naturalized
   p       gy
Naturalized epistemology (Feldman, Kornblith,...
24




  Naturalist Understanding of Cognition

   According t M t
   A     di to Maturana and V l (1980) even the simples...
25



Info-Computational Account of
Knowledge Generation
             Natural computing as a new paradigm of
             ...
26



Info-Computational Account of
Knowledge Generation

        At the ph sical le el li ing beings are open comple
    ...
27



Cognition as Restructuring of an Agent in
Interaction with the Environment

As a result of evolution increasingly co...
28



 Cognition as Restructuring of an Agent in
 Interaction with the Environment

Naturalized knowledge generation ackno...
29



  Natural Computing in Cognizing Agents
- Agent-centered (information and
computation is in the agent)
- Agent is a ...
30




Self-Reflection




              http://brain.oxfordjournals.org/cgi/content/full/125/8/1808
31



 What is computation? How does nature
 compute? Learning from Nature *

“It always bothers me that according to the ...
32




An Ongoing Paradigm Shift
               Information/Computation as basic building blocks of
           •
         ...
33




An Ongoing Paradigm Shift
     g   g       g
              Emergency (emergent property - a quality possessed by th...
34




There is a crack, a crack in everything ..
                ,                y    g




                            ...
35




An Example ..

Until the 18th century, alchemy was regarded as the ‘art of all
arts, the science of all sciences’. ...
36




Summary

Philosophy in general and especially Computing and Philosophy
can contribute to Sciences of Information by...
37




Summary

  Helping understanding and improvement of learning processes
providing broader, more general context and ...
38




References
Gordana Dodig-Crnkovic
  Semantics of Information as Interactive Computation
  in Manuel Moeller, Wolfga...
39




Gordana Dodig-Crnkovic
  Knowledge G
  K     l d Generation as N t l C
                     ti     Natural Computat...
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Info-Computationalism and Philosophical Aspects of Research in Information Sciences

  1. 1. 1 Info-Computationalism and Philosophical p p Aspects of Research in Information Sciences Gordana Dodig Crnkovic School of Innovation, Design and Engineering, Mälardalen University, Sweden Philosophy's Relevance in Information Science Paderborn University Paderborn, Germany, 2008 10 04 http://groups.uni-paderborn.de/hagengruber/pris08/
  2. 2. 2 What is Science? How did Sciences Develop? Eye 2 Maurits Cornelis Escher
  3. 3. 3 The Mytho-Poetic Universe y Mytho-Poetic Universe of Egypt Hindu Mytho-Poetic Universe In ancient Egypt the dome of the sky In Hindu myth, the tortoise supports elephants that hold up the world, and was represented by the goddess Nut, everything is encircled by the world the night sky, and the sun, the god serpent Ra, was born from her every morning. 3
  4. 4. 4 The M h i l U i Th Mechanical Universe The Medieval Geocentric Universe The Clockwork Universe Newton Philosophiae Naturalis The universe depicted in The p Principia Matematica, 1687 Nuremberg Chronicle (1493) 4
  5. 5. 5 The Computational Universe We are all living inside a gigantic computer. No, not The Matrix: the Universe. Every process, every change that takes E h h k place in the Universe, may be considered as a kind of computation. E Fredkin S Wolfram G Chaitin Fredkin, Wolfram, The universe is on a fundamental level an info-computational phenomenon info computational phenomenon. GDC http://www nature com/nsu/020527/020527- http://www.nature.com/nsu/020527/020527- 16.html 5
  6. 6. 6 The Computational Universe Konrad Zuse was the first to suggest (in 1967) that the physical behavior of the entire universe is being computed on a basic level, possibly on cellular automata by the universe automata, itself which he referred to as quot;Rechnender Raumquot; or Computing Space/Cosmos. Computationalists: Zuse, Wiener, Fredkin, Wolfram, Chaitin, Lloyd, Seife, 't Hooft, Deutsch, Tegmark, Schmidhuber, Weizsäcker, Wheeler.. http://en.wikipedia.org/wiki/Pancomputationalism http://www.nature.com/nature/journal/v 435/n7042/full/435572a.html 6
  7. 7. 7 The Major Paradigm Shifts in our View of the Universe (Classical) Info- Mechanic Computational Mytho-poetic, Universe Universe God Centric God-Centric Universe
  8. 8. 8 The Classical Model of Science The Classical Model of Science is a system S of propositions and concepts satisfying the following conditions: All propositions and all concepts (or terms) of S concern a specific • set of objects or are about a certain domain of being(s). There are in S a number of so-called fundamental concepts (or • terms). All other concepts (or terms) occurring in S are composed of (or • are definable from) these fundamental concepts (or terms). 8
  9. 9. 9 The Classical Model of Science There are in S a number of so-called fundamental propositions so called propositions. • All other propositions of S follow from or are grounded in (or are • provable or demonstrable from) these fundamental propositions propositions. All propositions of S are true. • All propositions of S are universal and necessary in some sense or • another. 9
  10. 10. 10 The Classical Model of Science All concepts or terms of S are adequately known A non- known. non • fundamental concept is adequately known through its composition (or definition). The Classical Model of Science is a reconstruction a posteriori and • sums up the historical philosopher’s ideal of scientific explanation. The fundamental is that “All propositions and all concepts (or • terms) of S concern a specific set of objects or are about a certain domain of being(s).” Betti A & De Jong W R., Guest Editors, The Classical Model of Science I: A Millennia Old Model of Scientific W. R Editors Millennia-Old Rationality, Forthcoming in Synthese, Special Issue 10
  11. 11. 11 The Scientific Method EXISTING KNOWLEDGE THEORIES PREDICTIONS HYPOTHESIS AND OBSERVATIONS Hypothesis must Hypothesis must be adjusted be redefined SELECTION AMONG TESTS AND NEW COMPETING THEORIES OBSERVATIONS Consistency achieved The hypotetico-deductive cycle EXISTING THEORY CONFIRMED (within a new context) or NEW THEORY PUBLISHED The Scientific-community cycle 11
  12. 12. 12 Natural Philosophy Natural philosophy or the philosophy of nature (Latin philosophia naturalis), naturalis) is a study of nature and the physical universe that was dominant before the development of modern science in the 19th century. Newton was natural philosopher. At older universities, l ld i iti long-established Ch i of N t l Phil t bli h d Chairs f Natural Philosophy are h nowadays occupied mainly by physics professors. http://en.wikipedia.org/wiki/Natural_philosophy http://en.wikipedia.org/wiki/Natural philosophy At present, interesting complexity phenomena are studied on the intersection of several research fields such as computing, biology, neuroscience, cognitive science, philosophy, physics, and similar i iti i hil h hi d i il information/computation intensive fields which might again form a core of a new life-centric natural philosophy.
  13. 13. 13 Info-Computationalism p Information and computation are two interrelated and mutually defining p phenomena – there is no computation without information p (computation understood as information processing), and vice versa, there is no information without computation (all information is a result of computational processes). Being interconnected, information is studied as a structure, while computation presents a process on an informational structure. In order to learn about foundations of information, we must also study computation.
  14. 14. 14 Information A special i i l issue of th f the Journal of Logic, Language and Information (Volume 12 No 4 2003) dedicated to the different facets of information information. A Handbook on the Philosophy of Information (Van Benthem Adriaans) is in preparation as Benthem, one volume Handbook of the philosophy of science. http://www.illc.uva.nl/HPI/ The Internet http://www.sdsc.edu/News%20Items/PR022008_moma.html http://www.sdsc.edu/News%20Items/PR022008 moma.html
  15. 15. 15 “IT IS TEMPTING TO SUPPOSE THAT SOME CONCEPT OF INFORMATION COULD SERVE EVENTUALLY TO UNIFY MIND, MATTER, AND MEANING IN A SINGLE THEORY.” (Emphasis in the original) Daniel C. Dennett And John Haugeland. Intentionality. in Richard L. Gregory, Editor. The Oxford Companion To The Mind. Oxford University Press, Oxford, 1987.
  16. 16. 16 Computation The Computing Universe: Pancomp tationalism Comp ting Uni erse Pancomputationalism Computation i generally d fi d as i f C t ti is ll defined information processing. ti i (See Burgin, M., Super-Recursive Algorithms, Springer Monographs in Computer Science, 2005) p ) For different views see e.g. http://people.pwf.cam.ac.uk/mds26/cogsci/program.html Computation and Cognitive Science 7–8 July 2008, King's College Cambridge The definition of computation is widely debated, and an entire issue of the journal Minds and Machines (1994, 4, 4) was devoted to the question “What i C “Wh t is Computation?” E t ti ?” Even: Th Theoretical C ti l Computer S i t Science 317 (2004)
  17. 17. 17 Computing Nature and Nature Inspired Computation Natural computation includes computation that occurs in nature or is inspired by nature Computing nature. Inspired by nature: •Evolutionary computation •Neural networks •Artificial immune systems •Swarm intelligence In 1623, Galileo in his book The Assayer - Simulation and emulation of nature: Il Saggiatore, claimed that the language of •Fractal geometry nature's book is mathematics and that the •Artificial life Artificial way to understand nature is through mathematics. Generalizing ”mathematics” Computing with natural materials: to ”computation” we may agree with Galileo – the great book of nature is an e- •DNA computing book! •Quantum computing http://www.youtube.com/watch?v=JA5QoTMvsiE&feature=related Journals: Natural Computing and IEEE Transactions on Evolutionary Computation.
  18. 18. 18 Turing Machines Limitations – Self-Generating Self Generating Living Systems Complex biological systems must be modeled as self- referential, self-organizing quot; f il lf i i quot;component-systemsquot; quot; (George Kampis) which are self-generating and whose behavior, though computational in a general sense, goes f beyond T i machine model. far b d Turing hi dl “a component system is a computer which, when executing its operations (software) builds a new hardware.... [W]e have a computer that re-wires itself in a hardware software interplay: the hardware defines the software and the hardware-software software defines new hardware. Then the circle starts again.” (Kampis, p. 223 Self-Modifying Systems in Biology and Cognitive Science)
  19. 19. 19 Beyond Turing Machines y g Ever since Turing proposed his machine model which identifies computation with the execution of an algorithm there have been algorithm, questions about how widely the Turing Machine (TM) model is applicable. With the advent of computer networks, which are the main paradigm of computing today, the model of a computer in isolation, represented by a Universal Turing Machine, has become insufficient. i ffi i t The basic difference between an isolated computing box and a network of computational processes (nature itself understood as a t kf t ti l (t it lf d t d computational mechanism) is the interactivity of computation. The most general computational paradigm today is interactive computing (Wegner Goldin). (Wegner, Goldin)
  20. 20. 20 Beyond Turing Machines y g The challenge to deal with computability in the real world (such as computing on continuous data, biological computing/organic computing, quantum computing, or generally natural computing) has brought new understanding of computation. Natural computing has different criteria for success of a computation, halting problem is not a central issue, but instead the adequacy of the comp tational response in a net ork of interacting computational network computational processes/devices. In many areas, we have to computationally model emergence not being clearly algorithmic. (Barry Cooper)
  21. 21. 21 Correspondence Principle picture after Stuart A Umpleby A. http://www.gwu.edu/~umpleby/recent_papers/2004_what_i_learned_from_heinz_von_foerster_fig ures_by_umpleby.htm TM Natural Computation
  22. 22. 22 Computability Theory Barry Cooper http://www.amsta.leeds.ac.uk/~pmt6sbc/
  23. 23. 23 Info-Computationalism Applied: Epistemology Naturalized p gy Naturalized epistemology (Feldman, Kornblith, Stich) is, in general, an idea that knowledge may be studied as a natural phenomenon -- that the subject matter of epistemology is not our concept of knowledge, but the knowledge itself. “The stimulation of his sensory receptors is all the evidence anybody has had to go on, ultimately, in arriving at his picture of the world. Why g , y, g p y not just see how this construction really proceeds? Why not settle for psychology? “(quot;Epistemology Naturalizedquot;, Quine 1969; emphasis mine) I will re-phrase the q p question to be: Why not settle for computing? y p g Epistemology is the branch of philosophy that studies the nature, methods, limitations, and validity of knowledge and belief.
  24. 24. 24 Naturalist Understanding of Cognition According t M t A di to Maturana and V l (1980) even the simplest organisms d Varela th i l t i possess cognition and their meaning-production apparatus is contained in their metabolism. Of course, there are also non-metabolic interactions with the environment, such as locomotion, that also generates meaning for an organism by changing its environment and providing new input data. Maturana’s and Varelas’ understanding that all living organisms posess some cognition, i some d iti in degree. i most suitable as th b i f a is t it bl the basis for computationalist account of the naturalized evolutionary epistemology. Info-Computationalism and Philosophical Aspects of Scientific Research
  25. 25. 25 Info-Computational Account of Knowledge Generation Natural computing as a new paradigm of computing goes b ti beyond th T i M hi model d the Turing Machine dl and applies to all physical processes including those going on in our brains. The next great change in computer science and information technology will come from mimicking gy g the techniques by which biological organisms process information. To do this computer scientists must draw on expertise in subjects not usually associated with their field including organic chemistry molecular field, chemistry, biology, bioengineering, and smart materials.
  26. 26. 26 Info-Computational Account of Knowledge Generation At the ph sical le el li ing beings are open comple physical level, living complex computational systems in a regime on the edge of chaos, characterized by maximal informational content. Complexity is found between orderly systems with high information compressibility and low information content and random systems with low compressibility and high information content. (Flake) The essential feature of cognizing living organisms is their ability to manage complexity, and to handle complicated environmental conditions with a variety of responses which are results of adaptation, variation, selection, l lt f d t ti i ti l ti learning, i and/or reasoning. (Gell-Mann)
  27. 27. 27 Cognition as Restructuring of an Agent in Interaction with the Environment As a result of evolution increasingly complex living organisms arise that are evolution, able to survive and adapt to their environment. It means they are able to register inputs (data) from the environment, to structure those into information, and in more developed organisms into knowledge. The p g g evolutionary advantage of using structured, component-based approaches is improving response-time and efficiency of cognitive processes of an organism. The Dual network model, suggested by Goertzel for modeling cognition in a living organism describes mind in terms of two superposed networks: a self-organizing associative memory network and a perceptual-motor network, process hierarchy, with the multi-level logic of a flexible command structure.
  28. 28. 28 Cognition as Restructuring of an Agent in Interaction with the Environment Naturalized knowledge generation acknowledges the body as our basic cognitive instrument. All cognition is embodied cognition, in both microorganisms and humans (Gärdenfors, Stuart). In more complex cognitive agents, knowledge is built upon not only reasoning about input g g g p y g p information, but also on intentional choices, dependent on value systems stored and organized in agents memory. It is not surprising that present day interest in knowledge generation places information and computation (communication) in focus, as information and its processing are essential structural and dynamic elements which characterize structuring of input data (data → information → knowledge) by an interactive computational process going on in the agent during the adaptive interplay with the environment.
  29. 29. 29 Natural Computing in Cognizing Agents - Agent-centered (information and computation is in the agent) - Agent is a cognizing biological organism or an intelligent machine or both - Interaction with the physical world and other agents is essential - Kind of physicalism with information as a s u of e universe stuff o the u e se - Agents are parts of different cognitive communities - Self-organization - Circularity (recursiveness) is central for biological organisms http://www.conscious-robots.com
  30. 30. 30 Self-Reflection http://brain.oxfordjournals.org/cgi/content/full/125/8/1808
  31. 31. 31 What is computation? How does nature compute? Learning from Nature * “It always bothers me that according to the laws as we understand It that, them today, it takes a computing machine an infinite number of logical operations to figure out what goes on in no matter how tiny a region of space and no matter how tiny a region of time … space, So I have often made the hypothesis that ultimately physics will not require a mathematical statement, that in the end the machinery i th ti l t t t th t i th d th hi will be revealed, and the laws will turn out to be simple, like the chequer board with all its apparent complexities.” Richard Feynman “The Character of Physical Law” The Law * 2008 Midwest NKS Conference, Fri Oct 31 - Sun Nov 2, 2008 Indiana University — Bloomington, IN
  32. 32. 32 An Ongoing Paradigm Shift Information/Computation as basic building blocks of • understanding Discrete/Continuum as two complementary levels of • description Natural interactive computing beyond Turing limit – not • only computing as is but also computing as it may be Complex dynamic systems (grounds for future • communication across cultural gaps of research)
  33. 33. 33 An Ongoing Paradigm Shift g g g Emergency (emergent property - a quality possessed by the whole • but not by its p y parts) ) Logical pluralism • Philosophy (“Everything must go” approach synthetic Phil h (“E thi t” h th ti • besides analytic approaches, philosophy informed by sciences) Human-centric (agent-centric) models • Circularity and self reflection (computing cybernetics) self-reflection (computing, • Ethics returns to researchers agenda (Science as a • constructivist project – what is it we construct and why?)
  34. 34. 34 There is a crack, a crack in everything .. , y g Ring the bells that still can ring Forget your perfect offering There is a crack, a crack in everything That's how the light gets in. Leonard Cohen
  35. 35. 35 An Example .. Until the 18th century, alchemy was regarded as the ‘art of all arts, the science of all sciences’. Whereas one branch of alchemy developed into modern natural sciences its other sciences, offshoots became the dark side of science, and were either forgotten or suppressed. The crisis consists precisely in the fact that the old is dying and the new cannot be born… Antonio G A t i Gramsci, Prison Notebooks i Pi Ntb k From the lecture “The dark side: relevance and accountability in interdisciplinary collaborations” Ronald Jones & Rolf Hughes, Konstfack, Stockholm
  36. 36. 36 Summary Philosophy in general and especially Computing and Philosophy can contribute to Sciences of Information by: Providing P idi a common l language and an unified platform (f d ifi d l tf (framework) k) for specialist sciences to communicate and create holistic (multi- disciplinary/inter-disciplinary/transdisciplinary) views Deepening understanding of info-computational mechanisms and processes and their relationship to life and knowledge Prompting development of new unconventional computational pg p p methods
  37. 37. 37 Summary Helping understanding and improvement of learning processes providing broader, more general context and agendas Contributing to argument for evolution of biological life, cognition and intelligence Encouraging learning from nature about optimizing solutions with of finite resources constraints and so on..
  38. 38. 38 References Gordana Dodig-Crnkovic Semantics of Information as Interactive Computation in Manuel Moeller, Wolfgang Neuser, and Thomas Roth-Berghofer (eds.), Fifth International Workshop on Philosophy and Informatics, Kaiserslautern 2008 ((DFKI Technical Reports; Berlin: S Springer) ) Gordana Dodig-Crnkovic Where do New Ideas Come From? How do They Emerge? Epistemology as Computation (Information Processing) Chapter for a book celebrating the work of Gregory Chaitin, Randomness & Complexity, from Leibniz to Chaitin, C. Calude d World Scientific, Singapore, 2007 B k C C C l d ed., W ld S i tifi Si Book Cover Gordana Dodig-Crnkovic Epistemology Naturalized: The Info-Computationalist Approach APA Newsletter on Philosophy and Computers, Spring 2007 Volume 06, Number 2
  39. 39. 39 Gordana Dodig-Crnkovic Knowledge G K l d Generation as N t l C ti Natural Computation, t ti Proceedings of International Conference on Knowledge Generation, Communication and Management (KGCM 2007), Orlando, Florida, USA, July 8-11, 2007 Gordana Dodig-Crnkovic Investigations into Information Semantics and Ethics of Computing PhD Thesis, Mälardalen University Press September 2006 Thesis Press, Dodig-Crnkovic G. and Stuart S., eds. Computation, Information, Cognition – The Nexus and The Liminal p , , g Cambridge Scholars Publishing, Cambridge 2007 Gordana Dodig-Crnkovic Shifting the Paradigm of the Philosophy of Science the Philosoph of Philosoph Science: Philosophy Information and a New Renaissance Minds and Machines: Special Issue on the Philosophy of Information,November 2003, Volume 13, Issue 4 / http://www.springerlink.com/content/g14t483510156726/

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