Uncertainty in AI – Nov 29
With increasing frequency, AI algorithms are making high-impact decisions: When should a self-driving car slam on the brakes? Can an MRI scan reliably detect a tumor? Will facial recognition software identify you as a Most Wanted fugitive? AI algorithms need to be aware of their confidence level — to “know what they don’t know” — in order to be reliable and safe. Fortunately, time-tested ideas in statistics are providing solutions. How are old and fundamental mathematical concepts blending with recent tech breakthroughs to create safe, uncertainty-aware AI?
Our presenter, Dr. Stephen Bates, is a postdoctoral researcher in two departments at UC Berkeley: Statistics and Electrical Engineering & Computer Science. He is also a distinguished alumnus of Wonderfest’s Science Envoy Program.
Dr. Stephen Bates
This admission-free Wonderfest event will be COVID-free, as well, because we ask that attendees be masked (except when dining) and vaccinated. The warm feeling of Wondernaut camaraderie radiates through masks and across social distances; please join us! Also, kindly use the Eventbrite space, below, to help Wonderfest promote the understanding and appreciation of science. (Please ignore any mention of "tickets"!)
COSMIC BONUS: If early-evening skies are clear during the hour that precedes this Wonderfest event, attendees can enjoy telescopic views of Jupiter, Saturn, and Venus. Wondernauts need only ascend the grassy knoll of HopMonk's Beergarden to reach Dan Smiley and his impressive telescope. BIG THANKS to Marin Stargazers and HopMonk Tavern for trying this pilot pre-Wonderfest astronomy program!
Collaborators:
Marin Stargazers [https://www.facebook.com/groups/252208946754119/]