Rachel Thomas

Rachel Thomas is co-founder of fast.ai, which is making deep learning more accessible, and a researcher-in-residence at University of San Francisco Data Institute. Rachel has a mathematics PhD from Duke and has previously worked as a quant, a data scientist + backend engineer at Uber, and a full-stack software instructor at Hackbright.

Rachel was selected by Forbes as one of 20 "Incredible Women Advancing A.I. Research." She co-created the course "Practical Deep Learning for Coders," which is available for free at course.fast.ai and >50,000 students have started it. Her writing has made the front page of Hacker News 4x, the top 5 list on Medium, and been translated into Chinese, Spanish, & Portuguese. She is on twitter @math_rachel

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Keynote: Some healthy principles about ethics & bias in AI

AI & Data, Novice
8/17/2018 | 7:00 PM-7:45 PM | House Canary

Description

Algorithms are increasingly used to make life-changing decisions about health care benefits, who goes to jail, and more, and play a crucial role in pushing people towards extremism. Through a series of case studies, I want to debunk several misconceptions about bias and ethics in AI, and propose some healthier principles.