Knowledge%20in%20Individuals%20%20Prof.%20Andrew%20Basden.%20km@basden.demon.co.uk%20with%20thanks%20to%20Prof.%20Elaine%20Ferneley - PowerPoint PPT Presentation

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Knowledge%20in%20Individuals%20%20Prof.%20Andrew%20Basden.%20km@basden.demon.co.uk%20with%20thanks%20to%20Prof.%20Elaine%20Ferneley

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Title: Knowledge%20in%20Individuals%20%20Prof.%20Andrew%20Basden.%20km@basden.demon.co.uk%20with%20thanks%20to%20Prof.%20Elaine%20Ferneley


1
Knowledge in Individuals Prof. Andrew
Basden. km_at_basden.demon.co.uk with thanks to
Prof. Elaine Ferneley
2
From tacit to articulate knowledge
  • We know more than we can tell.
  • Michael Polanyi, 1966

High
Low
Codifiability
Tacit
Articulated
2
3
We know more than we can tell.
Knowledge is experience, everything else is just
information. -Albert Einstein
3
4
Explicit Knowledge
  • Formal and systematic
  • easily communicated shared in product
    specifications, scientific formula or as computer
    programs
  • Management of explicit knowledge
  • management of processes and information
  • Are the activities to the right information or
    knowledge dependent ?

5
Tacit Knowledge Examples
  • Highly personal
  • hard to formalise
  • difficult (but not impossible)to articulate
  • often in the form of know how.
  • Management of tacit knowledge is the management
    of people
  • how do you extract and disseminate tacit
    knowledge.

6
Knowledge As An Attribute of Expertise
  • An expert in a specialized area masters the
    requisite knowledge
  • The unique performance of a knowledgeable expert
    is clearly noticeable in decision-making quality
  • Experts are more selective in the information
    they acquire they know what is important
  • Experts are beneficiaries of the knowledge that
    comes from experience

7
Expertise, Experience Understanding
  • Experience rules of thumb What e.g. gardener
    might have
  • Understanding general knowledge What a biology
    graduate might have
  • Expertise E U in harmony What an expert has

8
Definitions Data, Information, Knowledge,
Understanding and Wisdom
  • The appreciation of why
  • The difference between learning and memorising
  • If you understand you can take existing knowledge
    and creating new knowledge, build upon currently
    held information and knowledge and develop new
    information and knowledge
  • In computing terms AI systems possess
    understanding in the sense that they are able to
    infer new information and knowledge from
    previously stored information and knowledge

9
Definitions Data, Information, Knowledge,
Understanding and Wisdom
  • Evaluated understanding
  • Essence of philosophical probing
  • Critically questions, particularly from a human
    perspective of morals and ethics
  • discerning what is right or wrong, good or bad
  • A mix of experience, values, contextual
    information, insight
  • In computing terms may be unachievable can a
    computer have a soul??

10
Illustrations of the Different Types of Knowledge
Know that
Know how
11
Types (Categorization) of Knowledge
  • Shallow (readily recalled) and deep (acquired
    through years of experience)
  • Explicit (already codified) and tacit (embedded
    in the mind)
  • Procedural (repetitive, stepwise) versus
    Episodical (grouped by episodes)
  • Knowledge exist in chunks

12
Reasoning and Thinking and Generating Knowledge
13
Experts Reasoning Methods
  • Reasoning by analogy relating one concept to
    another
  • Formal reasoning using deductive or inductive
    methods (see next slide)
  • Case-based reasoning reasoning from relevant
    past cases

14
Deductive and inductive reasoning
  • Deductive reasoning exact reasoning. It deals
    with exact facts and exact conclusions
  • Inductive reasoning reasoning from a set of
    facts or individual cases to a general conclusion

15
Learning
  • Learning by experience a function of time and
    talent
  • Learning by example more efficient than learning
    by experience
  • Learning by sharing, education.
  • Learning by discovery explore a problem area.
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