FAR.AI is a research & education non-profit
Ensuring advanced AI is safe and beneficial for everyone.
ORGANIZATIONS WE'VE WORKED WITH
recent & upcoming Events
Building the global field of trustworthy & secure AI.
FAR.AI hosts and delivers a suite of events on safe and beneficial AI.
Held just before NeurIPS 2025 in San Diego, California, the Alignment Workshop will bring researchers and leaders from around the world together to debate and discuss current issues in AI safety.
San Diego, California
December 1, 2025
FAR.AI, in collaboration with FAI, CNAS and RAND, is organizing the inaugural Technical Innovations for AI Policy Conference.
Washington, DC
May 30, 2025
Held around ICLR 2025 in Singapore, the Singapore Alignment Workshop will bring together researchers and leaders from around the world together to debate and discuss current issues in AI safety.
Singapore
April 23, 2025
June 3, 2025
Large language models (LLMs) are already more persuasive than humans in many domains. While this power can be used for good, like helping people quit smoking, it also presents significant risks, such as large-scale political manipulation, disinformation, or terrorism recruitment. But how easy is it to get frontier models to persuade into harmful beliefs or illegal actions? Really easy – just ask them.
July 26, 2024
Frontier LLMs like ChatGPT are powerful but not always robust. Scale helps with many things. We wanted to see if scaling up the model size can ‘solve’ robustness issues.
Programs
Supporting innovation in trustworthy & secure AI
Risks from advanced AI pose societal-scale challenges and will require a concerted effort that goes beyond FAR.AI. Our programs equip researchers and organizations with the tools, resources and connections they need to overcome these challenges. By providing targeted support and fostering collaboration, we help ensure the ecosystem thrives and drives impactful, lasting change.
View programs
Our targeted grantmaking program for academics and independent researchers developing innovative solutions to critical AI risks.
