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One of AI’s biggest, unsolved problems is what the advanced algorithms should do when they confront a situation they don’t have an answer for. For programs like Chat GPT, that could mean providing a confidently wrong answer, what’s often called a “hallucination”; for others, as with self-driving cars, there could be much more serious consequences. But what if AIs could be taught to recognize what they don’t understand and adjust accordingly? Usama Fayyad, the executive director for the Institute for Experiential Artificial Intelligence at Northeastern University thinks this could be the algorithmic answer to making future AIs better at what they do, by doing something too few humans can: recognizing their own limits.
What do you think about the show? Let us know on Apple Podcasts or Spotify, or email us: FOEPodcast@wsj.com
Further reading:
How Did Companies Use Generative AI in 2023? Here’s a Look at Five Early Adopters.
Your Medical Devices Are Getting Smarter. Can the FDA Keep Them Safe?
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Usama Fayyad
provost.northeastern.eduInstitute for Experiential Artificial Intelligence
ai.northeastern.eduApple Podcasts
podcasts.apple.comSpotify
open.spotify.comArtificial: The OpenAI Story
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