Melanie Mitchell: “Why AI is Harder Than We Think”
"Melanie Mitchell talks about why the development of long-promised AI tech has turned out to be much harder than many people expected."
- Speaker: Melanie Mitchell, Santa Fe Institute, USA
- Moderator: Allison Stanger, Middlebury College, USA
About the Event
February 22, 2022
5:00 – 6:00 PM
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.
Here you can download the slides: Download the slides.
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