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Stanford Center for AI Safety
webaisafety.stanford.edu·aisafety.stanford.edu/
Stanford's institutional AI safety center; a useful reference for academic research programs, courses, and policy initiatives in AI safety, though the current tags referencing corrigibility and shutdown-problem appear mismatched to this homepage's broad institutional scope.
Metadata
Importance: 55/100homepage
Summary
The Stanford Center for AI Safety is an interdisciplinary research center focused on ensuring AI systems are safe, trustworthy, and beneficial. It conducts research across formal methods, learning and control, transparency, AI governance, and human-AI interaction, while also offering education and engaging with policymakers and industry.
Key Points
- •Research spans formal methods, learning & control, transparency, AI governance & policy, and human-AI interaction.
- •Aims to shape global AI policy and industry standards through interdisciplinary collaboration across CS, law, and social sciences.
- •Offers AI safety education at Stanford from introductory to advanced levels.
- •Engages industry through corporate membership and collaborative research partnerships.
- •Publishes a white paper outlining its approach to safe, trustworthy, and beneficial AI development.
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| Corrigibility Failure | Risk | 62.0 |
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HTTP 200Fetched Mar 20, 20262 KB
[Stanford University](https://stanford.edu/) OUR MISSION The Stanford Center for AI Safety leads research, education, and policy to ensure AI systems are safe, trustworthy, and beneficial for humanity. OUR VISION We envision a future where AI technologies are developed and deployed responsibly, with robust safety guarantees, transparent decision-making, and alignment with human values. Through interdisciplinary collaboration spanning computer science, engineering, law, and social sciences, we aim to shape the policies and practices that govern AI development worldwide. [Read Our White Paper](https://aisafety.stanford.edu/whitepaper.pdf) RESEARCH AREAS ### Formal Methods Using precise mathematical modeling to ensure the safety, security, and robustness of conventional software and hardware systems. ### Learning & Control Designing systems that intelligently balance learning under uncertainty and acting safely in dynamic environments. ### Transparency Understanding safety in the context of fairness, accountability, and explainability for autonomous and intelligent systems. ### AI Governance & Policy Developing frameworks for responsible AI governance, working with policymakers and industry to create standards and best practices. ### Human-AI Interaction Studying how humans and AI systems can work together effectively and safely through trust calibration and human oversight mechanisms. [Explore Our Research](https://aisafety.stanford.edu/pages/research.html) EXPLORE [**Research** \\ \\ Explore our flagship projects in formal methods, learning & control, and AI transparency.](https://aisafety.stanford.edu/pages/research.html) [**Education** \\ \\ Discover AI safety courses offered at Stanford, from introductory to advanced levels.](https://aisafety.stanford.edu/pages/courses.html) [**Events** \\ \\ Join our annual meetings, seminars, and workshops on AI safety research.](https://aisafety.stanford.edu/pages/events.html) [**Industry** \\ \\ Collaborate with us through corporate membership and collaborative research.](https://aisafety.stanford.edu/pages/industry.html) ## Stay Connected Subscribe to our newsletter for the latest updates on AI safety research, events, and opportunities. [Join Our Mailing List](https://aisafety.stanford.edu/pages/contact.html)
Resource ID:
787d80854a4e36b4 | Stable ID: MzZlZjYyM2