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HAI Policy Briefs

November 2020

Domain Shift and Emerging Questions in Facial Recognition Technology

Improving AI Software for Healthcare Diagnostics Facial recognition technologies have grown in sophistication and adoption throughout American society. Significant anxieties around the technology have emerged—including privacy concerns, worries about surveillance in both public and private settings, and the perpetuation of racial bias.

Key Takeaways

Policy Brief November 2020

➜  FRT vendors and developers should ensure their models are created in a way that is as transparent as possible, capable of being validated by the user, and well documented. The effect these systems have on the decision making of their users must be understood more deeply and policymakers should embrace A/B testing as a tool to gauge this.

➜ Users in government and business settings should condition the procurement of FRT systems on in-domain testing and adherence to established protocols

➜ We support calls for a moratorium on FRT adoption in government and policing while a more responsible testing framework is developed.

Authors

Daniel E. Ho - Stanford University
Emily Black - Stanford University
Maneesh Agrwawala - Chapman University 
Fei-Fei Li - Sequoia Professor of Computer Science; Denning Co-Director, Stanford HAI

Read the full brief