Resources

The hub for technical AI alignment research and discussion.

Community blog on rationality and AI safety — much of the field's writing lives here.

Regular updates on AI safety research, policy, and news.

Technical alignment research and interpretability work from Redwood Research.

Newsletter on responsible AI integration, with balanced perspectives on hype, safety, and social impact.

Princeton researchers demystify AI claims and examine where machine learning adds value versus hype.

Helen Toner outlines the key disagreements shaping AI governance and long-term safety priorities.

Jack Clark on balancing optimism and caution in AI development.

In-depth interviews about the world's most pressing problems, including AI safety.

Deep conversations with leading AI researchers and thinkers about the future of AI.

Part-time remote AI safety and policy research, pairing mentees with established researchers.

Twelve-week mentored AI alignment research fellowship in Berkeley and London.

Fully funded five-month Berkeley fellowship pairing senior advisors with emerging researchers.

Nine-week London research fellowship in AI safety, governance, and biosecurity.

Ten-week funded Cambridge fellowship on technical AI safety and governance.

Places emerging-tech experts in funded US federal, congressional, and think-tank policy roles.

Thirteen-week London programme where teams produce technical AI safety papers.

Part-time programme pairing small teams with mentors on AI safety research.

Ten-week in-person fellowship on AI safety and security, and nuclear security.

Ten-week fully funded Cambridge, MA research fellowship in AI safety and governance.

One-year AI journalism fellowship with training and a nine-month newsroom placement.

Four-month funded AI safety research fellowship with Anthropic mentorship.

Funded external research fellowship on AI safety and alignment.

Four-week taught course on foundational AI alignment for mathematical backgrounds.

by Brian Christian

by Stuart Russell

by Nick Bostrom