Our Work
Field Building

CAIS Field Building

Supporting the broader research community with workshops, competitions, social events, fellowships, and online resources.

Empowering the research community

AI safety is a challenge that is beyond any single research lab. We run a variety of initiatives to support and empower the existing research community while lowering barriers to entry and further expanding the community. Our efforts include providing infrastructure and resources for the AI safety research ecosystem, initiating multi-disciplinary projects to explore the societal effects of AI from new perspectives, and creating educational resources to encourage newcomers to join.

Active Projects

All of our currently active projects.


AI Safety, Ethics, and Society

AI Safety, Ethics and Society is a textbook and online course providing a non-technical introduction to how current AI systems work, why many experts are concerned that continued advances in AI could pose severe societal-scale risks, and how society can manage and mitigate these risks.

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The SafeBench competition stimulates research on new benchmarks which assess and reduce risks associated with artificial intelligence. We are providing $250,000 in prizes: five $20,000 prizes and three $50,000 prizes for top benchmarks.

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Compute Cluster

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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Educational and Student Resources

Lowering the barriers to entry in studying ML safety.

Intro to ML Safety

Intro to ML Safety is a comprehensive training program designed for individuals seeking additional support, community, and accountability while completing the ML safety course. Accepted participants receive access to peer discussion groups, mentorship, and a small stipend.

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Student Scholarships

A $2000 scholarship for undergraduates and masters students who secure ML Safety research mentorship.

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ML Safety Course

An online course which offers a comprehensive introduction to ML safety.

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ML Safety Newsletter

A monthly newsletter detailing the latest advancements in ML safety.

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Past Projects

All of CAIS's past projects.

Statement on AI Risk

Hundreds of AI experts and public figures express their concern about AI risk in this open letter. It was covered globally in publications like the New York Times, the Wall Street Journal, and the Washington Post.

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Philosophy Fellowship

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

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ML Safety Workshop at NeurIPS 2022

The ML Safety Workshop at NeurIPS 2022 brought together researchers from various fields to discuss and advance the field of ML safety.

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Trojan Detection Competition at NeurIPS 2022

Neural Trojans are a growing concern for the security of ML systems, but little is known about the fundamental offense-defense balance of Trojan detection. The Trojan Detection Competition at NeurIPS 2022 poses the question: How hard is it to detect hidden functionality that is trying to stay hidden?

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Adversarial Robustness Prizes at ECCV 2022

Three best paper awards to study model robustness to threats beyond small l_p perturbations, including attacks that are perceptible and attacks with specifications not known beforehand and are unforeseen.

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