h+ Magazine - May 4, 2009, by Ben Goertzel
The news media is buzzing with talk of IBM's new DeepQA project, aimed at creating a program that can beat humans at the question-answering game of Jeopardy. This is indeed exciting indeed – although, at the moment, it's a partly-completed plan rather than a demonstrated accomplishment. But let's suppose IBM succeeds at its aim. What will this really mean?
To interpret DeepQA in the proper way, one needs to grasp the notion of "AI-completeness" -- an informal concept that is central to the folklore of modern AI. Here's the basic concept behind AI-completeness: Some problems are so hard that the only way to solve them is to create an artificial entity with human-level general intelligence. These problems are AI-complete. On the other hand, some problems --- even though they're hard for humans and seem to require great general intelligence --- are actually amenable to simple, specialized approaches. These problems are not AI-complete.
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