Many of us assume that tech is neutral, and we have turned to tech as a way to root out racism, sexism, or other “isms” plaguing human decision-making. But as data-driven systems become a bigger and bigger part of our lives, we also notice more and more when they fail, and, more importantly, that they don’t fail on everyone equally. Glad You Asked host Joss Fong wants to know: Why do we think tech is neutral? How do algorithms become biased? And how can we fix these algorithms before they cause harm?
0:00 Intro
1:24 Is AI Racist?
4:15 The Myth Of The Impartial Machine
11:09 Saliency Testing
13:52 How Machines Become Biased
18:33 Auditing The Algorithms
20:24 Wrap Up
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