Algorithmic Fairness

Online
Essay
Affirmative Algorithms: The Legal Grounds for Fairness as Awareness
Daniel E. Ho
Daniel E. Ho is the William Benjamin Scott and Luna M. Scott Professor of Law, Professor of Political Science, Senior Fellow at the Stanford Institute for Economic Policy Research, Associate Director for the Stanford Institute for Human-Centered Artificial Intelligence (HAI), and Director of the Regulation, Evaluation, and Governance Lab.
Alice Xiang
Alice Xiang is the Head of Fairness, Transparency, and Accountability Research at the Partnership on AI.

The authors thank Alexandra Chouldechova, Jacob Goldin, Peter Henderson, Jessica Hwang, Mark Krass, Patrick Leahy, Laura Trice, and Chris Wan for helpful comments. Authors are listed alphabetically and have equally contributed to this work.

Acentral concern with the rise of artificial intelligence (AI) systems is bias.

Algorithmic Fairness Disparate Impact Machine Learning

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