How can AI be designed to ensure fairness, transparency, and inclusivity?
Stanford HAI researchers create eight new AI benchmarks that could help developers reduce bias in AI models, potentially making them fairer and less likely to case harm.
Stanford HAI researchers create eight new AI benchmarks that could help developers reduce bias in AI models, potentially making them fairer and less likely to case harm.
HAI believes that all researchers and funding agencies have a responsibility to mitigate potential long-term harms from their research. HAI provides select examples, on-the-ground experiences, and perspectives from devising and administering an ethical reflection process for research. While HAI believes that ethical reflection can be integrated into any grantmaking process, the exact process can and should be tailored to the needs of the institution.
HAI believes that all researchers and funding agencies have a responsibility to mitigate potential long-term harms from their research. HAI provides select examples, on-the-ground experiences, and perspectives from devising and administering an ethical reflection process for research. While HAI believes that ethical reflection can be integrated into any grantmaking process, the exact process can and should be tailored to the needs of the institution.
New research tests large language models for consistency across diverse topics, revealing that while they handle neutral topics reliably, controversial issues lead to varied answers.
New research tests large language models for consistency across diverse topics, revealing that while they handle neutral topics reliably, controversial issues lead to varied answers.
This brief explores the complexities of accounting for race in clinical algorithms for evaluating kidney disease and the implications for tackling deep-seated health inequities.
This brief explores the complexities of accounting for race in clinical algorithms for evaluating kidney disease and the implications for tackling deep-seated health inequities.
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.
This white paper, produced in collaboration with Black in AI, presents considerations for the Congressional Black Caucus’s policy initiatives by highlighting where AI holds the potential to deepen racial inequalities and where it can benefit Black communities.
This white paper, produced in collaboration with Black in AI, presents considerations for the Congressional Black Caucus’s policy initiatives by highlighting where AI holds the potential to deepen racial inequalities and where it can benefit Black communities.
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
In this brief, Stanford scholars present one of the first empirical investigations into AI ethics on the ground in private technology companies.
In this brief, Stanford scholars present one of the first empirical investigations into AI ethics on the ground in private technology companies.
Because tech industry ethics teams lack resources and authority, their effectiveness is spotty at best, according to a new study.
Because tech industry ethics teams lack resources and authority, their effectiveness is spotty at best, according to a new study.
In this brief, Stanford scholars test a variety of ordinary text prompts to examine how major text-to-image AI models encode a wide range of dangerous biases about demographic groups.
In this brief, Stanford scholars test a variety of ordinary text prompts to examine how major text-to-image AI models encode a wide range of dangerous biases about demographic groups.
A Stanford collaboration with the Department of the Treasury yields the first direct evidence of differences in audit rates by race.
A Stanford collaboration with the Department of the Treasury yields the first direct evidence of differences in audit rates by race.