2.  Prominent AI Reseacher  Colleague of Alan Turing at Bletchley Park  1992 Paper: ◦ Turing’s Test and Conscious Thought Turing’s Test and Conscious Thought ◦ Provides a critique of the test

3.  Solipsism and the “Charmed Circle” ◦ “…Turing underestimated the appeal of a more subtle form of solipsism generalized to groups.” ◦ The argument can be stated as: “the only way by which one could be sure that a machine thinks is to be a member of a charmed circle which has accepted that machine into its ranks and can collectively feel itself thinking.”

4.  Subarticulate Thought ◦ “The test can only detect only those processes that are susceptible to introspective verbal report.”  Many thought processes that cannot be articulated by humans  A machine might be able to articulate them, even when a human cannot. ◦ Most highly developed mental skills are of the verbally inaccessible kind (Hutchins) ◦ “Expert Systems” famously failed in knowledge extraction through dialog-acquisition.

5.  Consciousness and Human-Computer Interaction ◦ What story is assigned to a sequence of events? ◦ Cutaneous Rabbit  5 taps on the wrist  2 near the elbow  3 at the upper arm

6.  Chinese Room ◦ Consider a program that can appear intelligent in conversation in Chinese ◦ Suppose that someone who doesn’t speak Chinese executes the program “by hand” ◦ The non-Chinese speaker does not understand the conversation, just as a computer does not understand the conversation.

7.  A successful Turing Test could be accomplished through table lookup (given a large enough memory)  Is this really intelligence?

8.  Turing’s test might not be passed in the foreseeable future, but that doesn’t really matter.  Let machines make progress without the requirement that they imitate people  Computers will provide their own contributions without the need for imitation.

9.  Weak AI ◦ How the task is accomplished doesn’t matter ◦ We can use a mechanism vastly different than what humans do ◦ Success is based strictly on performance  Strong AI ◦ Tasks should use the same mechanisms used by humans ◦ We want to duplicate human intelligence ◦ We want machines to be conscious of what they are doing

10.  Defined by a set of problems that are generally considered to require intelligence in humans ◦ Knowledge Processing ◦ Natural Language Understanding ◦ Game Players ◦ Diagnostic/Classification Problems ◦ Machine Learning

11.  “Rules of Thumb” ◦ Methods that tend to work, but don’t guarantee success.  Find a simpler problem you know how to solve and try to generalize to the larger problem  Work backwards from the goal state

12.  In the 1970’s and 1980’s many people believed “expert systems” would replace many if not most experts  “Knowledge Engineers” were tasked with extracting and encoding knowledge from experts.  It didn’t work very well, largely because much if not most expertise is subarticulate.

13.  Puzzle solving  Finding the best of a set of possible permutations

14.  Chess  Checkers  Go  Chinese Chess  Dots and Boxes

15.  Given a set of facts, deduce “useful” conclusions ◦ Representation of facts ◦ Method used for deduction ◦ Identification of “useful” facts

16.  If (some criteria) then some fact  If (some criteria) then perform some action Expert Systems were often produced using production rules.

17.  Simplified model of basic building blocks of the brain  Much smaller number of neurons  Much simpler model of how neurons work  Neural Networks are used in many pattern matching/classification/generalization problems.

18.  Simulate evolution  Natural selection used as a form of search ◦ Genetic Algorithms  A population of simulated genes evolves in an attempt to solve a problem ◦ Genetic Programming  A population of programs evolves in an attempt to solve a problem