It is good practice to find truth in statements such as these before
dismissing them. This often requires adopting one or more contexts.

In this case, if one assumes a traditional definition of "AI-complete" by
extending Hobbs statement to imply actually creating an artificial
intelligence, then anything short of AI-Complete would be fall under Hobb's
definition of "computer science." If one chooses to apply the dual process
theory ( http://en.wikipedia.org/wiki/Dual_process_theory#Systems ), then
one could argue that an Expert System would fit Hobbs definition of fast,
computer science. Conversely, the massively parallel unconscious processing
that humans regularly perform (e.g. in speech, vision) would require
enormous computing resources and considerable time - even more so using
resources available twenty years ago.

Does solving syntactic ambiguity really result in creating an artificial
intelligence? Yampolskiy's paper AI-Complete, AI-Hard, or AI-Easy:
Classification of Problems in Artificial Intelligence (PDF:
http://louisville.edu/speed/computer/tr/UL_CECS_02_2011.pdf/at_download/file)
is a good read on that question.


On Tue, Nov 26, 2013 at 3:19 PM, Piaget Modeler
<[email protected]>wrote:

> Hobbs' statement:
>
>
> *Q:  What is the difference between computer science and artificial
> intelligence? *
> *A:  In computer science you write programs to do quickly what people do
> slowly. In artificial intelligence, it is just the opposite.*
>
> In AI we don't write programs to do slowly what people do quickly.  In
> Expert Systems in particular, once it is known what people
> do symbolically,  an expert system often does the symbol manipulations faster
>  that a person. Also, Expert Systems can perform
> those symbol manipulations 24 x 7 x 365.  Thereby bringing consistency,
> accuracy, and endurance to the formerly human task.
>
> This statement is clearly false.
>
> ~PM
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