Many recent mainstream media articles and popular books have raised alarms over anti-social algorithmic behavior, especially regarding machine learning and artificial intelligence. The concerns include leaks of sensitive personal data by predictive models, algorithmic discrimination as a side-effect of machine learning, and inscrutable decisions made by complex models. While standard and legitimate responses to these phenomena include calls for stronger and better laws and regulations, researchers in machine learning, statistics and related areas are also working on designing better-behaved algorithms. An explosion of recent research in areas such as differential privacy, algorithmic fairness and algorithmic game theory is forging a new science of socially aware algorithm design.

Michael Kearns and Aaron Roth join us at Google and survey these developments, attempting to place them in a broader societal context. It is based on their book The Ethical Algorithm (Oxford University Press, 2019).

Moderated by Emily Denton.

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