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Stanford HAI
Stanford HAI is an interdisciplinary institute studying AI and its impact on people.
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Overview
It connects research, education, policy, and practice rather than operating as an AI product company.
Deep Dive
Stanford HAI describes its work as advancing AI and data-science research, education, policy, and practice. Its human-centered framing emphasizes human impact and AI designed to augment rather than replace people. The institute’s AI Index is an annual report that assembles measures and context about AI development. CRFM studies foundation models and their implications. These are research and education activities; HAI is not a regulator or model-certification body. Stanford HAI officially launched in 2019. CRFM researchers describe choosing and coining the term “foundation model” to emphasize a base adapted to downstream applications. Stanford HAI’s 2026 AI Index technical-performance chapter spans vision, video, language, speech, reasoning, robotics, and agentic systems; the chapter is one part of the annual report.
Real-World Implementation
Researchers consult Stanford’s AI Index for reported measures and trends.
Students and scholars join interdisciplinary AI research and education programs.
CRFM studies foundation models, including their opportunities and risks.
Policymakers can use HAI research as one input among many.
The Future of Stanford HAI
HAI’s published programs and reports can change. Cite a particular report edition or institute program, and do not infer that analysis constitutes official policy or product certification.
Putting it into practice
Why it matters
- Vendor strategy. Vendor roadmaps influence what features your team can build next.
- Cost and budget. Commercial terms and deployment options affect long-term cost and risk.
- Risk and safety. Company incentives shape product defaults, safety posture, and openness.
Watch out for
- Launch announcements may outpace stability in real production workflows.
- API pricing or policy shifts can break assumptions overnight.
- Single-vendor dependency increases lock-in and migration costs.
Next steps
- Evaluate providers using your own tasks and datasets.
- Review privacy, security, and legal terms before integration.
- Maintain a fallback plan across models or vendors.
- Monitor release notes so roadmap changes do not surprise teams.
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Frequently asked questions
What is Stanford HAI?
Stanford HAI is an interdisciplinary institute studying AI and its impact on people. It connects research, education, policy, and practice rather than operating as an AI product company.
What does the 'H' in Stanford HAI stand for?
HAI stands for the Stanford Institute for Human-Centered Artificial Intelligence, emphasizing people over pure technology.
What does Stanford HAI describe as a guiding principle for AI?
Stanford HAI states its belief that AI should be guided by human impact and designed to augment people.
What does Stanford’s AI Index report aim to provide?
The AI Index compiles information on AI research, industry, policy, and societal trends.
Which best describes Stanford HAI?
HAI is Stanford’s interdisciplinary institute for human-centered AI research and practice.
Which term was popularized by HAI's Center for Research on Foundation Models?
Researchers at HAI's CRFM coined and popularized the term 'foundation models' for large, broadly capable AI systems.
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