Abstract
It is a well-known fact that artificial intelligence (AI) research seeks both to
reproduce the outcome of our intelligent behaviour by non-biological means, and to produce the non-biological equivalent of our intelligence. As a branch of engineering interested in intelligent behaviour reproduction, AI has been astoundingly successful. We increasingly rely on AI-related applications (smart technologies) to perform tasks that would be simply impossible by un-aided or un-augmented human intelligence. But as a branch of cognitive science interested in intelligence production, AI has been a dismal disappointment. Productive AI does not merely underperform with respect to human intelligence; it has not joined the competition yet. The fact that Watson—IBM’s system capable of answering questions asked in natural language—recently won against its human opponents when playing Jeopardy! only shows that artefacts can be smart without being intelligent.
reproduce the outcome of our intelligent behaviour by non-biological means, and to produce the non-biological equivalent of our intelligence. As a branch of engineering interested in intelligent behaviour reproduction, AI has been astoundingly successful. We increasingly rely on AI-related applications (smart technologies) to perform tasks that would be simply impossible by un-aided or un-augmented human intelligence. But as a branch of cognitive science interested in intelligence production, AI has been a dismal disappointment. Productive AI does not merely underperform with respect to human intelligence; it has not joined the competition yet. The fact that Watson—IBM’s system capable of answering questions asked in natural language—recently won against its human opponents when playing Jeopardy! only shows that artefacts can be smart without being intelligent.
Original language | English |
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Pages (from-to) | 227-232 |
Number of pages | 6 |
Journal | Philosophy and Technology |
Volume | 24 |
Issue number | 3 |
DOIs | |
Publication status | Published - 1 Sept 2011 |