Stanford HAI Co-Director James Landay speaks about defining human-centered AI, HAI's accomplishments over the past five years, and broader societal impacts of AI technology.
Stanford HAI Deputy Director Russell Wald discusses California's #1 ranking in America's Top States for AI, which utilizes data from the AI Index, and the role that Stanford HAI plays in shaping AI's future, measuring current metrics, and evaluating labor market impacts.
Stanford HAI Senior Fellow Daniel E. Ho comments on his research on legal hallucinations in large language models and the viability of using similar models for judicial interpretation.
Stanford HAI Senior Fellow Daniel E. Ho's research explains why retrieval-augmented generation (RAG) based legal research tools still make mistakes and struggle to complete legal researching tasks.
A summary of the HAI AI Index's key takeaways for businesses, including AI's strengths in tasks, profit margins, worker productivity, increased AI regulations, and industry adoption of AI tools.
Stanford HAI Denning Co-Director Fei-Fei Li is nominated for the VentureBeat Women in AI Award, "Responsibility and Ethics of AI: Thoughtfully building AI that leads to a better and more equitable world."
Nestor Maslej, editor-in-chief of the AI Index, explains key findings in the 2024 AI Index Report, including AI and associations with productivity and quality in workers; business manager's anticipation of job increases and decreases; and insights into AI's impact on organizational hierarchy in the workforce.
Erik Brynjolfsson, Stanford HAI Senior Fellow and Director of the Stanford Digital Economy Lab, reports on AI transformation for jobs in the customer service industry.
This article discusses debates on openness of AI tools, referencing the CRFM and HAI issue brief on Considerations for Governing Open Foundation models and debates that took place at the HAI at Five Conference.
Stanford HAI Senior Fellow Dan Ho gives input on how to reduce AI hallucinations and discusses his research into AI legal tools that rely on retrieval augmented generation.
