Facebook routinely deploys recommendation systems and predictive models that affect the lives of billions of people everyday. That kind of reach comes with great responsibility — among other things, the responsibility to develop AI tools that ethical, fair and well characterized. This isn’t an easy task. Human beings have spent thousands of years arguing about what “fairness” and “ethics” mean, and haven’t come close to a consensus. Which is precisely why the responsible AI community has to involve as many disparate perspectives as possible in determining what policies to explore and recommend — a practice that Facebook’s Responsible AI team has applied itself. For this episode of the podcast, I’m joined by Joaquin Quiñonero-Candela, the Distinguished Tech Lead for Responsible AI at Facebook. Joaquin has been at the forefront of the AI ethics and fairness movements for years, and has overseen the formation of Facebook’s responsible AI team. As a result, he’s one of relatively few people with hands-on experience making critical AI ethics decisions at scale, and seeing their effects. Our conversation covered a lot of ground, from philosophical questions about the definition of fairness, to practical challenges that arise when implementing certain ethical AI frameworks.

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“What did the council decide on item 42?” — answered with the speaker and the moment.

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