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HTTP/2 200 date: Sun, 28 Dec 2025 23:47:46 GMT content-type: text/html server: cloudflare cf-ray: 9b54f1d52ac0c7d3-BLR cf-cache-status: HIT content-encoding: gzip last-modified: Tue, 23 Dec 2025 12:02:47 GMT strict-transport-security: max-age=31536000 surrogate-control: max-age=2147483647 surrogate-key: safe.ai 63fe96aeda6bea77ac7d3000 pageId:64324a03a316080c41b5c9de x-lambda-id: 07b1b46a-4a1b-47a1-9159-e80e49dca33d vary: Accept-Encoding set-cookie: _cfuvid=TAt05R3kagJeU3.iXH39SAO6wXHHfiK_g4nHylrNYdo-1766965666357-0.0.1.1-604800000; path=/; domain=.safe.ai; HttpOnly; Secure; SameSite=None alt-svc: h3=":443"; ma=86400 Center for AI Safety (CAIS)

Reducing Societal-scale
Risks from AI

The Center for AI Safety (CAIS — pronounced 'case') is a San Francisco-based research and field-building nonprofit. We believe that artificial intelligence (AI) has the potential to profoundly benefit the world, provided that we can develop and use it safely.

View our work

Our mission

In contrast to the dramatic progress in AI, many basic problems in AI safety have yet to be solved. Our mission is to reduce societal-scale risks associated with AI by conducting safety research, building the field of AI safety researchers, and advocating for safety standards.

Featured CAIS Work

AI Safety Field-Building

Featured

Philosophy Fellowship

AI Safety, Ethics, & Society

Now accepting applications for the November 3 to February 1 session

The course offers a comprehensive introduction to how current AI systems work, their societal-scale risks, and how to manage them.

Learn More

CAIS Compute Cluster

Compute Cluster

Enabling ML safety research at scale

To support progress and innovation in AI safety, we offer researchers free access to our compute cluster, which can run and train large-scale AI systems.

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ML Safety Infrastructure

Philosophy Fellowship

Tackling conceptual issues in AI safety

The CAIS Philosophy Fellowship is a seven-month research program that investigates the societal implications and potential risks associated with advanced AI.

Learn more

See all work

Dan Hendrycks

Director, Center for AI Safety
PhD Computer Science, UC Berkeley

"Preventing extreme risks from AI requires more than just technical work, so CAIS takes a multidisciplinary approach working across academic disciplines, public and private entities, and with the general public."

Risks from AI

Artificial Intelligence (AI) possesses the potential to benefit and advance society. Like any other powerful technology, AI also carries inherent risks, including some which are potentially catastrophic.

Current AI Systems

Current systems already can pass the bar exam, write code, fold proteins, and even explain humor. Like any other powerful technology, AI also carries inherent risks, including some which are potentially catastrophic.

AI Safety

As AI systems become more advanced and embedded in society, it becomes increasingly important to address and mitigate these risks. By prioritizing the development of safe and responsible AI practices, we can unlock the full potential of this technology for the benefit of humanity.

AI risks overview

Our Research

We conduct impactful research aimed at improving the safety of AI systems.

Technical Research

At the Center for AI Safety, our research exclusively focuses on mitigating societal-scale risks posed by AI. As a technical research laboratory:

We create foundational benchmarks and methods which lay the groundwork for the scientific community to address these technical challenges.
We ensure our work is public and accessible. We publish in top ML conferences and always release our datasets and code.

Conceptual Research

In addition to our technical research, we also explore the less formalized aspects of AI safety.

We pursue conceptual research that examines AI safety from a multidisciplinary perspective, incorporating insights from safety engineering, complex systems, international relations, philosophy, and other fields.
Through our conceptual research, we create frameworks that aid in understanding the current technical challenges and publish papers which provide insight into the societal risks posed by future AI systems.

CAIS research