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Nonprofit lab building open tools to understand and oversee AI systems, including its Docent analysis tool and public reports on how models behave, such as its mental-health evaluation.
Research papers, investigations, explainers, videos, laws and the organizations doing the work, from people who are alarmed and people who are skeptical. New additions are checked by two people before they are listed. The launch collection was compiled with the help of AI research assistants, and every link was opened and checked on 22 September 2026.
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Nonprofit lab building open tools to understand and oversee AI systems, including its Docent analysis tool and public reports on how models behave, such as its mental-health evaluation.
Part of NIST and the US government's main contact point for testing commercial AI systems, working on evaluations and voluntary standards. Formerly the US AI Safety Institute.
Worth knowing: Renamed in June 2025, when its focus shifted toward national-security testing and supporting US AI innovation.
Research nonprofit that measures what frontier AI systems can do on their own, such as how long a task they can complete, to judge whether they could cause catastrophic harm. Began as ARC Evals.
Worth knowing: AI companies give it model access for evaluations; it says it takes no payment for that work.
Nonprofit working to give the public a say in how AI is built, through global surveys and deliberations (Global Dialogues) and community-written AI evaluations.
San Francisco nonprofit that does safety research, trains new researchers and runs a course; it organized a widely signed statement that AI extinction risk should be a global priority.
Worth knowing: Also advocates for AI safety standards.
Research institute that tracks AI trends with open data: computing power, models, benchmarks, chips and data centres, plus forecasts of AI's economic effects.
Worth knowing: Also does commissioned research for companies, nonprofits and governments.
Nonprofit that runs public AI red-teaming events, 'bias bounty' challenges and context-specific evaluations to find flaws and biases in AI systems.
One of the oldest AI safety groups, whose early research helped found the field; it now argues that building superintelligence with current methods would most likely lead to human extinction.
Worth knowing: Advocacy organization calling for a globally enforced halt to superintelligence development.