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Cognitive information science

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Introduces the research domain of Cognitive Information Science

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Cognitive information science

  1. 1. Cognitive Information Science Dr. S. Kate Devitt
  2. 2. INTRODUCTION
  3. 3. > Cognitive information science is the study of the human mind in the information age
  4. 4. > What is the human mind? Perception Memory Imagination Inference
  5. 5. > What is the human mind? Perception Memory Imagination Inference
  6. 6. > Is it the information age?
  7. 7. > Humans have constructed external epistemic devices to manage information and enhance cognitive capacities for thousands of years. E.g. paths writing mathematical devices Inca Machu Picchu Trail Sumerian Cuniform Sumerian Abacus
  8. 8. Socrates (Phaedrus) > Does writing, by offering a crutch to memory, hinder the development of knowledge? [writing]…will create forgetfulness in the learners' souls, because they will not use their memories; they will trust to the external written characters and not remember of themselves…. [With Writing]… you give your disciples not truth, but only the semblance of truth; they will be hearers of many things and will have learned nothing; they will appear to be omniscient and will generally know nothing; they will be tiresome company, having the show of wisdom without the reality—Plato (Phaedrus). > Socrates argued that those who can merely gather facts without integrating them in memory will have confidence, without the wisdom to back it up.
  9. 9. The Tower of Wisdom (1475) > Humans have improved memory and cognition with the method of loci and other mnemonics
  10. 10. > Humans have worked collaboratively to achieve informationally intense tasks through managing their environment and their memories. Elizabethan Theatre (1562-1642) Locke’s (1685-1706) Commonplace book > We have changed the organisation of information to increase efficiencies
  11. 11. > With the advent of the printing press, came concerns about information overload. As long as the centuries continue to unfold, the number of books will grow continually, and one can predict that a time will come when it will be almost as difficult to learn anything from books as from the direct study of the whole universe. It will be almost as convenient to search for some bit of truth concealed in nature as it will be to find it hidden away in an immense multitude of bound volumes— Diderot. > Diderot worried that the proliferation of books recording facts, might hinder, rather than promote learning. Diderot’s Encylopedie (1755)
  12. 12. > Card catalogs can do anything! > “Card catalogs can maintain order among tens of thousands of small and large items in the warehouse management of large industrial plants, they can structure any number of addresses in personnel departments, they can control the movement of hundreds of thousands of people in urban registration offices, they can make themselves useful in the bookkeeping departments of commercial offices...” Fortschritt GmbH: Karteien können alles! (“Card indexes can do anything!”, Zeitschrift fur Organisation und moderne Betriebsführung 3(23):6 (1929))
  13. 13. > In World War II women performed complex mathematical operations on information using machines, paper and pens and their own physical movements helping break codes. Women of Bletchley park
  14. 14. > Alan Turing invented the modern computer by taking an existing card catalog and imagining a (theoretically) infinite partitioned tape and a machine head that could write ‘1’, or ‘0’, or erase a number or move over a square and all computable functions could be performed. ‘Computers’: From people to machines
  15. 15. Rise of Computers 1950s 1960s 1970s 1980s 1990s
  16. 16. > Is there too much information, or not enough?...
  17. 17. > …or are we struggling to make best use of the information we have?
  18. 18. > What are our best theories of how to manage and process information?
  19. 19. > Humans or machines?
  20. 20. > How much do we need higher order, reflective human agents filtering, curating information and making decisions?
  21. 21. > Can we build humans to be better at managing information?
  22. 22. > How much of the processing of information can we (and should we) automate?
  23. 23. > Perhaps it is an age of disruptive information?
  24. 24. COGNITIVE INFORMATION SCIENCE
  25. 25. Current view of the mind and information > Information Science Emerged from 20th C. organisation of huge volumes of information Memory no longer a crucial part of finding the best solutions to organising, storing and retrieving information > Cognitive science Rise of the computational theory of the mind Rapid progress in understanding memory systems, reasoning, decision-theory, and rationality
  26. 26. Cognitive Information Science > The domain is information. > Many of the methodologies and theoretical commitments stem from cognitive science.
  27. 27. Future of the mind and information > Will there be a re-integration between the mind and information systems? Information systems need to be built according to our best theories of cognition. > Is cognition changing as our information environments change? Cognition needs to be understood relative to overwhelming and changing information environments > Can we meet Socrates’ challenge? To understand and have wisdom while externalising information processing
  28. 28. Big data and philosophy > Big Data creates a radical shift in how we think about research . . .. [It offers] a profound change at the levels of epistemology and ethics. Big Data reframes key questions about the constitution of knowledge, the processes of research, how we should engage with information, and the nature and the categorization of reality . . . Big Data stakes out new terrains of objects, methods of knowing, and definitions of social life Boyd D and Crawford K (2012) Critical questions for big data. Information, Communication and Society 15(5): 662–679.
  29. 29. Problem with big data is small patterns > The problem with big data is small patterns > The game will be won by those who “know how to ask and answer questions” (Plato, Cratylus, 390c) and therefore know which data may be Useful Relevant Worth collecting Worth curating - in order to exploit valuable patterns. > We need more and better techniques and technologies to see the small data patterns, but we need more and better epistemology to sift the valuable ones (p.437)”. Floridi, L. (2012). Big data and their epistemological challenge. Philosophy & Technology, 25(4), 435-437.
  30. 30. > The research framework of cognitive information science…
  31. 31. > …will help us thrive in an age of information disruption. 01010101010101010101 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 01010101010101010101 01010101010101010101 01010101010101010101

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