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December 1, 20224:00 pm – 5:00 pm (CDT)

Why AI is Harder Than We Think


Melanie Mitchell (Santa Fe Institute)


Rainer Fries

Event Details

Since its beginning in the 1950s, the field of artificial intelligence
has cycled several times between periods of optimistic predictions
and massive investment (“AI Spring”) and periods of disappointment,
loss of confidence, and reduced funding (“AI Winter”). Even with
today’s seemingly fast pace of AI breakthroughs, the development of
long-promised technologies such as self-driving cars, housekeeping
robots, and conversational companions has turned out to be much
harder than many people expected.

One reason for these repeating cycles is our limited understanding of
the nature and complexity of intelligence itself. In this talk I will
discuss some fallacies in common assumptions made by AI researchers, which can lead to overconfident predictions about the field. I will also speculate on what is needed for the grand challenge of making AI systems more robust, general, and adaptable—in short, more intelligent.

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