All Work Published on Ethics, Equity, Inclusion
Stanford RegLab, Princeton, and the County of Santa Clara Collaborate to Use AI to Identify and Map Racial Covenants from over 5 Million Deed Records
The approach paves the way for faster and more accurate compliance with California’s anti-discrimination law.
The approach paves the way for faster and more accurate compliance with California’s anti-discrimination law.
Peter Norvig, Distinguished Education Fellow at the Stanford HAI, comments on how limiting the budget at an AI agent’s disposal as well as transaction times and capabilities can help AI agents “operate safely within defined boundaries."
Peter Norvig, Distinguished Education Fellow at the Stanford HAI, comments on how limiting the budget at an AI agent’s disposal as well as transaction times and capabilities can help AI agents “operate safely within defined boundaries."
Large language models exhibit alarming magnitudes of bias when generating stories about learners, often reinforcing harmful stereotypes
Large language models exhibit alarming magnitudes of bias when generating stories about learners, often reinforcing harmful stereotypes
Real AI Threats Are Disinformation, Bias, And Lack Of Transparency: Stanford’s James Landay
James Landay, Co-Founder of Stanford HAI, says disinformation, deepfake, discrimination and job displacement; of which not a lot has happened yet, are the real harms of AI.
James Landay, Co-Founder of Stanford HAI, says disinformation, deepfake, discrimination and job displacement; of which not a lot has happened yet, are the real harms of AI.
HAI Co-Director Fei-Fei Li is recognized for her commitment to ethical AI and interdisciplinary research, continuing to shape the future of AI development and application.
HAI Co-Director Fei-Fei Li is recognized for her commitment to ethical AI and interdisciplinary research, continuing to shape the future of AI development and application.
Vanessa Parli, HAI Director of Research Programs, explains the importance of evaluation methods when it comes to AI benchmarking, noting the significance of assessing traits like "bias, toxicity, truthfulness, and other responsibility aspects."
Vanessa Parli, HAI Director of Research Programs, explains the importance of evaluation methods when it comes to AI benchmarking, noting the significance of assessing traits like "bias, toxicity, truthfulness, and other responsibility aspects."