1. CDT403 Research Methodology in Natural Sciences and Engineering Theory of Science INFORMATION, COMPUTATION, KNOWLEDGE AND SCIENCE Gordana Dodig-Crnkovic School of Innovation, Design and Engineering Mälardalen University 1

2. 2 THEORY OF SCIENCE LECTURES Lecture 1 INFORMATION, COMPUTATION, KNOWLEDGE AND SCIENCE Lecture 2 SCIENCE AND CRITICAL THINKING. PSEUDOSCIENCE AND WISHFUL THINKING - DEMARCATION Lecture 3 SCIENCE, RESEARCH, TECHNOLOGY, SOCIETAL ASPECTS. PROGRESS. HISTORY OF SCIENTIFIC THEORY. POSTMODERNISM AND CROSSDISCIPLINES Lecture 4 PROFESSIONAL & RESEARCH ETHICS

3. 3 Science is (a well formed) knowledge structure. Knowledge is (a well formed) information structure. Information is (a well formed) data structure. Data (raw data) yet unstructured ”atoms of information” – signals, visual pixels, before processing and integrating into common framework. Science, Knowledge, Information and Computation

4. 4 Science, based on knowledge, based on information, based on data are the result of our interactions with the physical world / the universe. Our current ability of interaction with the world is a result of a long evolution of our species. http://en.wikipedia.org/wiki/Timeline_of_evolutionary_history_of_life http://www.youtube.com/watch?v=FZ3401XVYww&NR=1http://www.youtube.com/watch?v=FZ3401XVYww&NR=1 The Miracle in Human Brain http://www.youtube.com/watch?v=6RbPQG9WTZM Evolution. The Origin of the Brainhttp://www.youtube.com/watch?v=6RbPQG9WTZM http://www.neuroinformatics2013.org Neuroinformatics congress 2013 Stockholmhttp://www.neuroinformatics2013.org Science, Knowledge, Information and Computation

5. 5 Our interactions with the real world are observer-dependent, depend on what we are - what sensors, actuators and information processing capabilities we have. Information /data structures that we develop throughout our lives depend on our physical architecture and the environment, and thus are observer (agent)-dependent. Knowledge is observer-dependent (contextual). Agent-Dependent Reality

6. 6 http://www.youtube.com/watch?v=N2iJF2I94pghttp://www.youtube.com/watch?v=N2iJF2I94pg The Human Brain: How We Decide Agent-Dependent Reality Science is agent-dependent but definitely not arbitrary! Two observers with close enough hardware and background information/knowledge will have similar understanding of the same phenomena. We agree on majority of basic things. We chose the questions we ask and experiments to study them but we definitely do not control the outcome! Physical theories that make observer-dependency explicit: -Relativity theory -Quantum mechanics -Chaos theory

7. 7 Meaning is use. (Wittgenstein) [for an agent!] Communities of practice share meanings. Consesnsus and controversy are two major driving forces in the development of sciences and human knowledge in general. Science is in a constant process of development. Agent-Dependent Reality

8. 8 Otto E. Rössler, Endophysics: The world as an interface http://books.google.com/books?id=0ckVNqhg3mkC&printsec=frontco ver&hl=sv&source=gbs_ge_summary_r&cad=0#v=onepage&q&f=fals e How does the brain (as a part of a body) provides this interface? See the following: http://www.youtube.com/watch?v=toXkS-MTYCI&feature=related http://www.youtube.com/watch?v=toXkS-MTYCI&feature=related Brain Evolution: The Accidental Mind (I) http://www.youtube.com/watch?v=H8RNq7DiMTs&feature=related http://www.youtube.com/watch?v=H8RNq7DiMTs&feature=related Brain Evolution: The Accidental Mind (II) http://www.youtube.com/watch?v=NEEXK3A57Hk&feature=related http://www.youtube.com/watch?v=NEEXK3A57Hk&feature=related The Origin of Intelligence Agent-Dependent Reality

9. SCIENCE: THE BIG PICTURE Science and the Universe Info-Computational Framework Science, Knowledge, Truth and Meaning The New, Emerging, Networking Paradigm KNOWLEDGE The Physical Basis of Knowledge 9

10. 10 SCIENCE The Big Picture First

11. Science and the Universe http://www.videopediaworld.com/video/12812/Cosmic-Super-Zoomhttp://www.videopediaworld.com/video/12812/Cosmic-Super-Zoom or http://www.youtube.com/watch?v=u9PnJkB1RGUhttp://www.youtube.com/watch?v=u9PnJkB1RGU Cosmic Super Zoom http://www.youtube.com/watch?v=x2fsNkAnzEI&feature=related http://www.youtube.com/watch?v=x2fsNkAnzEI&feature=related MEGA ZOOM http://www.youtube.com/watch?v=PPkPaHI2Usghttp://www.youtube.com/watch?v=PPkPaHI2Usg Cosmic Voyage from your Quarks to the Edge of the Universe http://www.youtube.com/watch?v=CDAUqGHl7UA&feature=related Microcosmos http://www.youtube.com/show?p=As9CDegGF-A&tracker=show0 Cosmic Journeys 11

12. The Idea of Universe The universe is an idea deeply rooted in our human culture, different in different places and during different epochs. At one time, it was a living organism (Tree of Life, Mother Earth, a Turtle, a Fish), at yet another time, mechanical machinery - the Cartesian-Newtonian clockwork. Today’s metaphor for the universe is more and more explicitly becoming a computer. Dodig Crnkovic G., Investigations into Information Semantics and Ethics of Computing, 2006 12

13. Universe as Reality The universe is defined as everything that exists. According to this definition and our present understanding, the universe consists of three elements: space-time matter-energy and physical laws that govern the relationships between the two. Those three elements correspond roughly to the ideas of Aristotle. In his book The Physics Aristotle divided everything that exists into three elements: -- matter (the stuff of which the universe is made), -- form (the arrangement of that matter in space) and -- change (how matter is created, destroyed or altered in its properties, and similarly, how form is altered). Physical laws were conceived as the rules governing the properties of matter, form and their changes. 13

14. Universe as Reality Later philosophers such as Averroes and Spinoza discern two basic elements: the passive elements, the fabric of the universe (natura naturata) the active principles governing the universe acting on the former elements (natura naturans) This compares to Info-Computational Universe (Dodig Crnkovic 2006):Dodig Crnkovic 2006 Information as structure Computation as change 14

15. Comment: Construction of Knowledge Our knowledge depends on our ways of interaction with the world – the nature and the humans as a part of natural world. If we use scientific instruments, such as microscopes, telescopes or particle accelerators, our knowledge will be much more far reaching than if we only use our human bodily sensory organs for interaction with the world. We construct knowledge from pieces of information we get directly from the world or indirectly via other people (again either exchanging information personally or even more indirectly from the information found in diverse kinds of documents.) (See Dodig-Crnkovic, Constructivist Research and Info-Computational Knowledge Generation, http://www.mrtc.mdh.se/~gdc/work/MBR09ConstructiveResearch.pdf )Constructivist Research and Info-Computational Knowledge Generation http://www.mrtc.mdh.se/~gdc/work/MBR09ConstructiveResearch.pdf 15

16. HISTORY OF IDEAS OF THE UNIVERSE The Mytho-Poetic Universe: World Egg In the ancient Hindu Rig-Veda the universe is a cosmic egg that cycles between expansion and collapse. It expanded from a concentrated form — a point called a Bindu. The universe, as a living entity, is bound to the perpetual cycle of birth, death, and rebirth... This model can be found, besides Sanskrit scriptures and Vedanta also in Chinese, Egyptian, and Finnish (Kalevala) mythology. 16 http://en.wikipedia.org/wiki/World_egg http://www.cellularuniverse.org/UniverseModels.htm#SS1

17. The Medieval Geocentric Universe From Aristotle Libri de caelo (1519). 17

18. The Clockwork (Mechanistic) Universe The mechanicistic paradigm which systematically revealed physical structure in analogy with the artificial. The self-functioning automaton - basis and canon of the form of the Universe. Newton Philosophiae Naturalis Principia Matematica, 1687 18

19. The Computational Universe We are all living inside a gigantic computer. No, not The Matrix: the Universe. Every process, every change that takes place in the Universe, may be considered as a kind of computation. E Fredkin, S Wolfram, G Chaitin The universe is on a fundamental level an info-computational phenomenon. GDC http://www.nature.com/nsu/020527/020527-16.html 19

20. 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 itself which he referred to as "Rechnender Raum" or Computing Space/Cosmos. Computationalists: Zuse, Wiener, Fredkin, Wolfram, Chaitin, Lloyd, Seife, 't Hooft, Deutsch, Tegmark, Schmidhuber, Weizsäcker, Wheeler.. http://www.youtube.com/watch?v=DJ0WG3D3m1U http://www.youtube.com/watch?v=DJ0WG3D3m1U Intelligence and the Computational Universe Pancomputationalism http://www.idt.mdh.se/personal/gdc/work/Pancomputationalism.mht http://www.idt.mdh.se/personal/gdc/work/Pancomputationalism.mht The Computational Universe 20

21. Does The Big Picture Make Any Difference At All For Us In Practice? Yes, definitely! It makes a big difference if we believe that the whole of the universe is governed by supernatural beings on which we have hardly any influence or if we believe that humans create their own world to a high extent. The understanding of the universe as organic or mechanistic influences our believes and actions. Today the big ideal is PROGRESS, EVOLUTION and CONSTANT IMPROVEMENT. In the past there were civilizations that avoided change for millennia. In those eras the STABILITY and PERMANENCY was the highest principle. 21

22. 22 However, no model is reality itself as no map is as detailed as a territory – for quite obvious reasons! R. Magritte – The two misteries R. Magritte – This is not a pipe

23. Info-Computationalism as a Framework Information and computation are two interrelated and mutually defining phenomena – there is no computation without information (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. 23

24. Information A special issue of the Journal of Logic, Language and Information (Volume 12 No 4 2003) dedicated to the different facets of information. A Handbook on the Philosophy of Information (Van Benthem, Adriaans) is in preparation as one volume Handbook of the philosophy of science. http://www.illc.uva.nl/HPI/http://www.illc.uva.nl/HPI/ 24

25. Computation The Computing Universe: Pancomputationalism Computation is generally defined as information processing. (See Burgin, M., Super-Recursive Algorithms, Springer Monographs in Computer Science, 2005) For different views see e.g. http://people.pwf.cam.ac.uk/mds26/cogsci/program.htmlhttp://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 is Computation?” Even: Theoretical Computer Science 317 (2004) 25

26. Present Model of Computation: Turing Machine http://plato.stanford.edu/entries/turing-machine/...... Read-Write head Control Unit 1. Reads a symbol 2. Writes a symbol 3. Moves Left or Right Tape 26

27. Computing Nature and Nature Inspired Computation In 1623, Galileo in his book The Assayer - Il Saggiatore, claimed that the language of nature's book is mathematics and that the way to understand nature is through mathematics. Generalizing ”mathematics” to ”computation” we may agree with Galileo – the great book of nature is an e-book! Natural computation includes computation that occurs in nature or is inspired by nature. Computing Inspired by nature: Evolutionary computation Neural networks Artificial immune systems Swarm intelligence Simulation and emulation of nature: Fractal geometry Artificial life Computing with natural materials: DNA computing Quantum computing Journals: Natural Computing and IEEE Transactions on Evolutionary Computation.Natural ComputingIEEE Transactions on Evolutionary Computation 27

28. Turing Machines Limitations – Self-Generating Living Systems Complex biological systems must be modeled as self-referential, self-organizing "component- systems" (George Kampis) which are self- generating and whose behavior, though computational in a general sense, goes far beyond Turing machine model. “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 software defines new hardware. Then the circle starts again.” (Kampis, p. 223 Self-Modifying Systems in Biology and Cognitive Science) 28

29. Ever since Turing proposed his machine model which identifies computation with the execution of an algorithm, there have been 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. The basic difference between an isolated computing box and a network of computational processes (nature itself understood as a computational mechanism) is the interactivity of computation. The most general computational paradigm today is interactive computing (Wegner, Goldin). Beyond Turing Machines 29

30. 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 computational response in a network of interacting computational processes/devices. In many areas, we have to computationally model emergence not being clearly algorithmic. (Barry Cooper) Beyond Turing Machines 30

31. Correspondence Principle Picture after Stuart A. Umpleby http://www.gwu.edu/~umpleby/recent_papers/2004_what_i_learned_from_heinz_von_foerster_figures_by_umpleby.htm http://www.gwu.edu/~umpleby/recent_papers/2004_what_i_learned_from_heinz_von_foerster_figures_by_umpleby.htm TM Natural Computation 31

32. Info-Computationalism Applied: Naturalizing Epistemology (Understanding knowledge as a result of natural processes) 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 not just see how this construction really proceeds? Why not settle for psychology? “("Epistemology Naturalized", Quine 1969; emphasis mine) I will re-phrase the question to be: Why not settle for computing? Epistemology is the branch of philosophy that studies the nature, methods, limitations, and validity of knowledge and belief. 32

33. Naturalist Understanding of Cognition According to Maturana and Varela (1980) even the simplest organisms 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, in some degree. is most suitable as the basis for a computationalist account of the naturalized evolutionary epistemology. 33

34. Natural computing as a new paradigm of computing goes beyond the Turing Machine model 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 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 biology, bioengineering, and smart materials. Info-Computational Account of Knowledge Generation 34

35. At the physical level, living beings are open 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, learning, and/or reasoning. (Gell-Mann) Info-Computational Account of Knowledge Generation 35

36. Cognition as Restructuring of an Agent in Interaction with the Environment As a result of evolution, increasingly complex living organisms arise that are 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 evolutionary advantage of using structured, component-based approaches is improving response-time and efficiency of cognitive processes of an organism. 36

37. 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 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. 37

38. - 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 stuff of the universe - Agents are parts of different cognitive communities - Self-organization - Circularity (recursiveness) is central for biological organisms Natural Computing in Living Agents http://www.conscious-robots.com 38

39. What is Computation? How Does Nature Compute? Learning from Nature * “It always bothers me that, according to the laws as we understand 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 … So I have often made the hypothesis that ultimately physics will not require a mathematical statement, that in the end the machinery 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 ” * 2008 Midwest NKS Conference, Fri Oct 31 - Sun Nov 2, 2008 Indiana University — Bloomington, IN 39

40. Paradigm Shift Information/Computation Discrete/Continuum Natural interactive computing beyond Turing limit Complex dynamic systems Emergency Logic Philosophy Human-centric (agent-centric) Circularity and self-reflection Ethics returns to researchers agenda 40

41. Info-Computational Paradigm of Knowledge Understanding of info-computational mechanisms and processes and their relationship to life and knowledge Argument for evolution of biological life, cognition and intelligence Development of new unconventional computational methods Learning from nature about optimizing solutions with limited resources (Organic Computing) Providing a unified platform (framework) for specialist sciences to communicate and create holistic (multi-disciplinary/inter- disciplinary/transdisciplinary) views 41

42. 42 Two Books on Universe as Quantum Information

43. Science, Knowledge, Truth and Meaning Critical thinking What is science? What is scientific method? What is knowledge? Information and knowledge Truth and meaning Limits of formal systems Science as learning process Info-computational view of knowledge production Complexity 43

44. Red Thread: Critical Thinking “Reserve your right to think, for even to think wrongly is better than not to think at all.” Hypatia, natural philosopher and mathematician 44

45. Eye Maurits Cornelis Escher What is Science? We can see Science from different perspectives… 45

46. Definitions by Goal (Result) and Process (1) science from Latin scientia, scire to know; 1: a department of systematized knowledge as an object of study 2: knowledge or a system of knowledge covering general truths or the operation of general laws especially as obtained and tested through scientific method 46

47. Definitions by Goal (Result) and Process (2) 3: such knowledge or such a system of knowledge concerned with the physical world and its phenomena : natural science 4: a system or method reconciling practical ends with scientific laws 47

48. Science: Definitions by Contrast To do science is to search for repeated patterns, not simply to accumulate facts. Robert H. MacArthur Religion is a culture of faith; science is a culture of doubt. Richard Feynman 48

49. Empirical approach. What Sciences are there? Dewey Decimal Classification ® http://www.geocities.com/Athens/Troy/8866/15urls.html 000 – Computer science, Library and Information science, & general work 100 – Philosophy and psychology 200 – Religion 300 – Social sciences 400 – Language 500 – Science 600 – Technology 700 – Arts 800 – Literature 900 – History, geography & biography 49

50. Dewey Decimal Classification ® 500 – Science 510 Mathematics 520 Astronomy 530 Physics 540 Chemistry 550 Earth Sciences & Geology 560 Fossils & Prehistoric Life 570 Biology & Life Sciences 580 Plants (Botany) 590 Animals (Zoology) 50

51. Culture (Religion, Art, …) 5 Natural Sciences (Physics, Chemistry, Biology, …) 2 Social Sciences (Economics, Sociology, Anthropology, …) 3 The Humanities (Philosophy, History, Linguistics …) 4 Logic & Mathematics 1 Language Based Scheme Classical Sciences in their Cultural Context – 51

52. Understanding what science is by understanding what scientists do "Scientists are people of very dissimilar temperaments doing different things in very different ways. Among scientists are collectors, classifiers and compulsive tidiers-up; many are detectives by temperament and many are explorers; some are artists and others artisans. There are poet-scientists and philosopher-scientists and even a few mystics." Peter Medawar, Pluto's Republic 52

53. Socratic MethodScientific Method 1. Wonder. Pose a question (of the “What is X ?” form). 1. Wonder. Pose a question. (Formulate a problem). 2. Hypothesis. Suggest a plausible answer (a definition or definiens) from which some conceptually testable hypothetical propositions can be deduced. 2. Hypothesis. Suggest a plausible answer (a theory) from which some empirically testable hypothetical propositions can be deduced. 3. Elenchus ; “testing,” “refutation,” or “cross-examination.” Perform a thought experiment by imagining a case which conforms to the definiens but clearly fails to exemplify the definiendum, or vice versa. Such cases, if successful, are called counterexamples. If a counterexample is generated, return to step 2, otherwise go to step 4. 3. Testing. Construct and perform an experiment, which makes it possible to observe whether the consequences specified in one or more of those hypothetical propositions actually follow when the conditions specified in the same proposition(s) pertain. If the test fails, return to step 2, otherwise go to step 4. 4. Accept the hypothesis as provisionally true. Return to step 3 if you can conceive any other case which may show the answer to be defective. 4. Accept the hypothesis as provisionally true. Return to step 3 if there are predictable consequences of the theory which have not been experimentally confirmed. 5. Act accordingly. Science defined by its Method 53

54. The Scientific Method The hypotetico-deductive cycle EXISTING THEORIES AND OBSERVATIONS 1 SELECTION AMONG COMPETING THEORIES 6 EXISTING THEORY CONFIRMED (within a new context) or NEW THEORY PUBLISHED 5 Hypotesen måste justeras PREDICTIONS 3 RESEARCH QUESTION/ HYPOTHESIS 2 TESTS AND NEW OBSERVATIONS 4 Hypothesis must be redefined Hypothesis must be adjusted The scientific-community cycle Consistency achieved 54

55. Formulating Research Questions and Hypotheses Different approaches: Intuition – (Educated) Guess Analogy Symmetry Paradigm Metaphor and many more.. The Scientific Method 55

56. Criteria to Evaluate Theories When there are several rivaling hypotheses number of criteria can be used for choosing a best theory. Following can be evaluated: – Theoretical scope – Heuristic value (heuristic: rule-of-thumb or argument derived from experience ) – Parsimony (simplicity, Ockham’s razor) – Esthetics – Etc. The Scientific Method 56

57. Criteria which Good Scientific Theory Shall Fulfill – Logically consistent – Consistent with accepted facts – Testable – Consistent with related theories – Interpretable: explain and predict – Parsimonious – Pleasing to the mind (Esthetic, Beautiful) – Useful (Relevant/Applicable) The Scientific Method 57

58. Ockham’s Razor (Occam’s Razor) (Law Of Economy, Or Law Of Parsimony, Less Is More!) A philosophical statement developed by William of Ockham, (1285–1347/49), a scholastic, that Pluralitas non est ponenda sine necessitate; “Plurality should not be assumed without necessity.” The principle gives precedence to simplicity; of two competing theories, the simplest explanation of an entity is to be preferred. The Scientific Method 58

59. KNOWLEDGE 59

60. What is Knowledge? Plato´s Definition Plato believed that we learn in this life by remembering knowledge originally acquired in a previous life, and that the soul already has knowledge, and we learn by recollecting what in fact the soul already knows. [At present we know that we inherit some physical preconditions, structures and abilities already at birth. In a sense those structures of our brains and bodies may be seen as the result of evolution, so in a sense they encapsulate memories of the historical development of our bodies.] 60

61. What is Knowledge? Plato´s Definition Plato offers three analyses of knowledge, [dialogues Theaetetus 201 and Meno 98] all of which Socrates rejects. Plato's third definition: " Knowledge is justified, true belief. " The problem with this concerns the word “justified”. All interpretations of “justified” are deemed inadequate. Edmund Gettier, in the paper called "Is Justified True Belief Knowledge?“ argues that knowledge is not the same as justified true belief. (Gettier Problem) 61

62. What is Knowledge? Descartes´ Definition "Intuition is the undoubting conception of an unclouded and attentive mind, and springs from the light of reasons alone; it is more certain than deduction itself in that it is simpler." “Deduction by which we understand all necessary inference from other facts that are known with certainty,“ leads to knowledge when recommended method is being followed. 62

63. What is Knowledge? Descartes´ Definition "Intuitions provide the ultimate grounds for logical deductions. Ultimate first principles must be known through intuition while deduction logically derives conclusions from them. These two methods [intuition and deduction] are the most certain routes to knowledge, and the mind should admit no others." 63

64. What is Knowledge? – Propositional knowledge: knowledge that such-and-such is the case. – Non-propositional knowledge (tacit knowledge): the knowing how to do something. 64

65. Sources of Knowledge –A Priori Knowledge (built in, developed by evolution and inheritance) (resides the brain as memory) –Perception (“on-line input”, information acquisition) –Reasoning (information processing) –Testimony (network, communication) 65

66. Knowledge and Ignorance “Our knowledge is an island in the infinite ocean of the unknown. “ Knowledge and wonder: the natural world as man knows it, Victor F. Weisskopf (1962) "We live in an island of knowledge surrounded by a sea of ignorance. As our island of knowledge grows, so does the shore of our ignorance.“ John Wheeler 66

67. Greg Chaitin: A More Elaborate, Fractal Picture of Knowledge Mathematics is more like an archipelago consisting of islands of truths in an ocean of incomprehensible and uncompressible information. Greg Chaitin, in an interview in September 2003 says: “You see, you have all of mathematical truth, this ocean of mathematical truth. And this ocean has islands. An island here, algebraic truths. An island there, arithmetic truths. An island here, the calculus. And these are different fields of mathematics where all the ideas are interconnected in ways that mathematicians love; they fall into nice, interconnected patterns. But what I've discovered is all this sea around the islands.” http://www.youtube.com/watch?v=WAJE35wX1nQ&feature=related Mandelbrot http://www.youtube.com/watch?v=WAJE35wX1nQ&feature=related http://books.google.se/books?id=RUedyFupPY4C&pg=PA265&lpg=PA265&dq=chaitin+knowledge+island&source=bl&ots=p7AacMKrm u&sig=1WzbvxKbJF16GCTMgxCJMjOoYhw&hl=sv#v=onepage&q=chaitin%20knowledge%20island&f=false 67

68. Physical basis of knowledge 68

69. http://www.youtube.com/watch?v=NJxobgkPEAo&feature=related From RNA to Protein Synthesis http://www.youtube.com/watch?v=3aVT2DTbtA8&feature=related Replication, Transcription, and Translation http://www.goldenswamp.com/page/2 http://www.goldenswamp.com/page/2 Cell Processing Information 69

70. Blurring the Boundary Between Perception and Memory http://www.scientificamerican.com/article.cfm?id=perc eption-and-memory http://www.sciencedaily.com 70

71. The Extended Mind Andy Clark and David Chalmers propose the idea of mind delegating cognitive* functions to the environment - in which objects within the environment function as a part of the mind http://consc.net/papers/extended.html http://consc.net/papers/extended.html 71 The term cognition (Latin: cognoscere, "to know", "to conceptualize" or "to recognize") refers to a faculty for the processing of information, applying knowledge, and changing preferences. Cognition, or cognitive processes, can be natural or artificial, conscious or unconscious. (Wikipedia)Latininformation

72. 72

73. http://online.wsj.com/article/SB124751881557234725.htmlhttp://online.wsj.com/article/SB124751881557234725.html In Search for Intelligence, a Silicon Brain Twitches http://bluebrain.epfl.ch/page-52741-en.html Blue Brain (Human Brain) Project 73

74. HBP - Computational Brain Brain Processing Information 74 The project Introduction Goals Neuroscience The computing challenge Towards understanding the brain Research areas Neuroinformatics Neuroscience Medicine Cognition Theory Simulation Supercomputing Neurorobotics Neuromorphic computing Brain interfaces Education Ethical, legal and social issues A european flagship Animated map Organisation The FET flagship programme Flagship call

75. The Human Brain Project: Science of 21st Century 75 The FET Flagship Program – a new initiative launched by the European Commission as part of its Future and Emerging Technologies (FET) initiative. http://ist.ac.at/fileadmin/user_upload/pictures/IST_Lectures/IST_Lecture_Markram/HB P_presskit__austria.pdf http://ist.ac.at/fileadmin/user_upload/pictures/IST_Lectures/IST_Lecture_Markram/HB P_presskit__austria.pdf http://www.youtube.com/watch?v=_rPH1Abuu9M Henry Markram: Simulating the Brain — The Next Decisive Years [1/3]http://www.youtube.com/watch?v=_rPH1Abuu9M http://www.youtube.com/watch?v=wDY4cFJauls Henry Markram: Simulating the Brain — The Next Decisive Years [2/3]http://www.youtube.com/watch?v=wDY4cFJauls http://www.youtube.com/watch?v=h06lgyES6Oc Henry Markram: Simulating the Brain — The Next Decisive Years [3/3]http://www.youtube.com/watch?v=h06lgyES6Oc http://www.youtube.com/watch?v=HrJQ_qkkx4E Five Tomorrowshttp://www.youtube.com/watch?v=HrJQ_qkkx4E

76. Cognitive Computing IBM have been working on a cognitive computing project called Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE). http://www.ibm.com/smarterplanet/us/en/business_analytics/article/cognitive_computing.html http://cacm.acm.org/magazines/2011/8/114944-cognitive-computing/fulltext Communications of the ACM, Vol. 54 No. 8, Pages 62-71 76

77. What is Universe? What is Knowledge? What is Science? Based on an enormous boost of extended mind of humanity we witness a major paradigm shift in our understanding of the universe and our place in it. This big picture is important as it sets the framework for how we think. That is why not only theory of particular sciences or specific phenomena but even philosophy of nature makes. (And empirical data are as well known theory-laden, even by implicit theory)

78. Network Paradigm 78 Metabolic theory of ecology http://online.kitp.ucsb.edu/online/pattern_i03/west/oh/29.html http://www.santafe.edu/about/people/profile/Geoffrey%20West

79. 79 High School Dating (Bearman, Moody, and Stovel, 2004) (Image by Mark Newman) Corporate E-Mail Communication (Adamic and Adar, 2005) Trails of Flickr Users in Manhattan (Crandall et al. 2009) http://www.cs.cornell.edu/home/kleinber/networks-book http://www.cs.cornell.edu/home/kleinber/networks-book Networks, Crowds, and Markets: Reasoning About a Highly Connected World

80. MAP OF SCIENCE http://www.lanl.gov/news/index.php/fuseaction/nb.story/story_id/%2015965 http://www.lanl.gov/news/albums/science/PL OSMapOfScience.jpg This "Map of Science" illustrates the online behavior of scientists accessing different scientific journals, publications, aggregators, etc. Colors represent the scientific discipline of each journal, based on disciplines Science as a result of Scientific Community 80

81. 81 Summary on Networks and why ”big picture” is necessary: ”http://www.youtube.com/watch?v=nJmGrNdJ5Gw The Power of Networks ”http://www.youtube.com/watch?v=nJmGrNdJ5Gw

82. Dodig Crnkovic, G. and Müller, V., A Dialogue Concerning Two World Systems: Info-Computational vs. Mechanistic; in Dodig Crnkovic G and Burgin, M., Eds.; World Scientific Publishing Co., Inc.: Singapore, 2010 http://arxiv.org/abs/0910.5001 http://arxiv.org/abs/0910.5001 More articles on Info-Computationalism: http://www.mrtc.mdh.se/~gdc/work/publications.html A Dialogue Concerning Two World Systems: Info- Computational vs. Mechanistic

83. Computation, Information, Cognition Editor(s): Gordana Dodig Crnkovic and Susan Stuart, Cambridge Scholars Publishing, 2007 Computation, Information, Cognition p. 83 Information and Computation Editor(s): Gordana Dodig Crnkovic and Mark Burgin, World Scientific, 2011 Computing Nature Editor(s): Gordana Dodig Crnkovic and Raffaela Giovagnoli, Springer, 2013