What is intelligence, in the context of machine learning and AI? A classic from 1979, Hofstadter’s GEB, gives eight essential abilities for intelligence:

1. to respond to situations very flexibly
2. to take advantage of fortuitous circumstances
3. to make sense out of ambiguous or contradictory messages
4. to recognize the relative importance of different elements of a situation
5. to find similarities between situations despite differences which may separate them
6. to draw distinctions between situations despite similarities which may link them
7. to synthesize new concept by taking old concepts and putting them together in new ways
8. to come up with ideas which are novel

It seems to me that the keyword is “flexibility“. Our world is complex, and a creature must be able to act in an infinite variety of circumstances. Sometimes a simple rule is enough, sometimes you need a combination of rules, and sometimes a totally new rule is required.

Hofstadter’s usage of the term stereotyped response got me thinking about Kahneman’s System 1 and 2. In those terms, it seems that System 1 covers all eight abilities. System 1 is fast thinking, applying a stereotypic solution to a situation. No actual reasoning or logical “thinking” is required to fulfil the requirements. However, the stereotypic solutions or rules must be flexible.