Critiques of the Turing Test Donald Michie Prominent

Critiques of the Turing Test

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

Donald Michie � 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. ”

Michie � 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.

Michie � Consciousness Interaction and Human-Computer ◦ 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

John Searle � 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.

Block’s Critisisim �A successful Turing Test could be accomplished through table lookup (given a large enough memory) � Is this really intelligence?

Robert French CACM, November 2012 � 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.

Weak and Strong AI � 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

What is the field of AI? � 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

Heuristics � “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

Expert Systems � 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.

Search Algorithms � Puzzle solving � Finding the best of a set of possible permutations

Two-person Games � Chess � Checkers � Go � Chinese Chess � Dots and Boxes

Automated Reasoning � Given a set of facts, deduce “useful” conclusions ◦ Representation of facts ◦ Method used for deduction ◦ Identification of “useful” facts

Production Rules � If (some criteria) then some fact � If (some criteria) then perform some action Expert Systems were often produced using production rules.

Neural Networks � 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.

Genetic Algorithms and Evolutionary Systems � 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