All Work Published on Ethics, Equity, Inclusion
Using AI to analyze Google Street View images of damaged buildings across 16 states, Stanford researchers found that destroyed buildings in poor areas often remained empty lots for years, while those in wealthy areas were rebuilt bigger and better than before.
Using AI to analyze Google Street View images of damaged buildings across 16 states, Stanford researchers found that destroyed buildings in poor areas often remained empty lots for years, while those in wealthy areas were rebuilt bigger and better than before.
Stanford scholars respond to a federal RFI regarding public and private sector uses of biometric technologies, proposing six principles for the responsible use of biometrics and AI.
Stanford scholars respond to a federal RFI regarding public and private sector uses of biometric technologies, proposing six principles for the responsible use of biometrics and AI.
Five teams will use the funding to advance their work in biology, generative AI and creativity, policing, and more.
Five teams will use the funding to advance their work in biology, generative AI and creativity, policing, and more.
This brief warns that AI systems that infer patients’ race in medical settings could deepen existing healthcare disparities.
This brief warns that AI systems that infer patients’ race in medical settings could deepen existing healthcare disparities.
How Congress Could Stifle The Onslaught Of AI-Generated Child Sexual Abuse Material
HAI Policy Fellow Riana Pfefferkorn advises on ways in which the United States Congress could move the needle on model safety regarding AI-generated CSAM.
HAI Policy Fellow Riana Pfefferkorn advises on ways in which the United States Congress could move the needle on model safety regarding AI-generated CSAM.
Toward Fairness in Health Care Training Data
This brief highlights the lack of geographic representation in medical-imaging AI training data and calls for nationwide, diversity-focused data-sharing initiatives.
This brief highlights the lack of geographic representation in medical-imaging AI training data and calls for nationwide, diversity-focused data-sharing initiatives.
