Joaquin Candela, Tech Lead for Responsible AI at Facebook, on definitions of fairness

Joaquin chats about scaling and democratizing AI at Facebook, while understanding fairness and algorithmic bias.

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Joaquin Quiñonero Candela is Distinguished Tech Lead for Responsible AI at Facebook, where he aims to understand and mitigate the risks and unintended consequences of the widespread use of AI across Facebook. He was previously Director of Society and AI Lab and Director of Engineering for Applied ML. Before joining Facebook, Joaquin taught at the University of Cambridge, and worked at Microsoft Research.

Connect with Joaquin:
Personal website: https://quinonero.net/
Twitter: https://twitter.com/jquinonero
LinkedIn: https://www.linkedin.com/in/joaquin-qui%C3%B1onero-candela-440844/

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Topics Discussed:
0:00 Intro, sneak peak
0:53 Looking back at building and scaling AI at Facebook
10:31 How do you ship a model every week?
15:36 Getting buy-in to use a system
19:36 More on ML tools
24:01 Responsible AI at Facebook
38:33 How to engage with those effected by ML decisions
41:54 Approaches to fairness
53:10 How to know things are built right
59:34 Diversity, inclusion, and AI
1:14:21 Underrated aspect of AI
1:16:43 Hardest thing when putting models into production

Transcript:
http://wandb.me/gd-joaquin-candela

Links Discussed:
Race and Gender (2019): https://arxiv.org/pdf/1908.06165.pdf
Lessons from Archives: Strategies for Collecting Sociocultural Data in Machine Learning (2019): https://arxiv.org/abs/1912.10389
Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification (2018): http://proceedings.mlr.press/v81/buolamwini18a.html

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