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.
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.
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.
Reducing barriers to entry in ML safety
The ML Safety course offers a comprehensive introduction to ML safety, covering topics such as anomaly detection, alignment, risk engineering, and so on.
Dan Hendrycks
Director, Center for AI Safety
PhD Computer Science, UC Berkeley
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.
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.
At the Center for AI Safety, our research exclusively focuses on mitigating societal-scale risks posed by AI. As a technical research laboratory:
In addition to our technical research, we also explore the less formalized aspects of AI safety.
We have compiled a list of frequently asked questions to help you find the answers you need quickly and easily.
CAIS’ mission is to reduce societal-scale risks from AI. We do this through research and field-building.
CAIS’ main offices are located in San Francisco, California.
By field-building, we mean expanding the research field of AI safety by providing funding, research infrastructure, and educational resources. Our goal is to create a thriving research ecosystem that will drive progress towards safe AI. You can see examples of our projects on our field-building page.
CAIS is always looking for value-driven, talented individuals to join our team. You can also make a tax-deductible donation to CAIS to help us maintain our independent focus on AI safety here.
Our work is driven by three main pillars: advancing safety research, building the safety research community, and promoting safety standards. We understand that technical work will not solve AI safety alone, and prioritize having a real-world positive impact. You can see more on our mission page.
As a technical research laboratory, CAIS develops foundational benchmarks and methods which concretize the problem and progress towards technical solutions. You can see examples of our work on our research page.