Keynote – Some Healthy Principles About Ethics & Bias In AI | Rachel Thomas @ PyBay2018
This talk was presented at PyBay2018 - the Bay Area local Python conference. See pybay.com for more details about PyBay and click SHOW MORE for more information about this talk.
Abstract:
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.
Slides: https://goo.gl/ThXJQm
Presenter:
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 more than 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
This and other PyBay2018 videos are brought to you by our Gold Sponsor Cisco!
This talk was presented at PyBay2018 – the Bay Area local Python conference. See pybay.com for more details about PyBay and click SHOW MORE for more information about this talk.
Abstract:
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.
Slides: https://goo.gl/ThXJQm
Presenter:
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 more than 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
This and other PyBay2018 videos are brought to you by our Gold Sponsor Cisco!
