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Showing 1-50 of 374·Sorted by endorsements
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We help people reduce x-risk from misaligned AI with scalable online courses and ongoing AI guidance.
+5Developing a practical evaluation framework to identify governance failures in frontier AI systems during elections, strengthening democratic legitimacy and the institutional capacity needed to reduce catastrophic risks from AI.
+4As Hong Kong’s first dedicated AI safety organisation, AI Safety Hong Kong develops local capacity through research, training, convening, and policy engagement.
+4AI safety for builder hackathon in India - to build tools, products, etc. (culminating into a fellowship)
+2The Argentinian AI Safety community (BAISH, baish.com.ar) is the largest in Latin-America. Support BAISH's growth, by providing funding for paying salaries for six months to 2-3 FTEs.
+3
SF based accelerator for communicators educating the public about the transformational impacts of AI.
+2Doom Debates is a modern "infotainment" show that functions as a mainstream-accessible forum for top thinkers to have a high-quality conversation & debate about AI extinction risk.
+2Funding for venue and catering for the first full-day convening, where Europe's AI safety institutions and researchers gather and coordinate on what comes next
+2A six-month effort to build and pilot an online course that equips cross-sector AI professionals and other stakeholders with a deep understanding of military AI technologies and the limits and opportunities for oversight.
AI Safety Quest will scale its free Navigation Calls program from 150 to 750 annual coaching calls by recruiting more volunteer coaches, improving scheduling/software systems, and expanding marketing to guide newcomers into AI…
Fund demonstrated/rigorous quantitative researcher (already run reproduction/audit pipelines on published economics) for 6-month AI safety transition, shipping concrete safety eval audits and positioning for top fellowships.
Measuring whether CoT monitoring fails when an influence reaches an agent through a tool return rather than the user message. We aim to extend our experiment from the 10 initial open-weight models to the larger open-weight models
+1Dean Ball says good AI governance needs democratic input in "what level of catastrophic risk are we willing to tolerate"; we provide that input, and predict the level is far below forecaster estimates, revealing a gap to close.
+2Build low-overhead and robust zero-knowledge protocols for verifying properties of frontier AI training, starting with FLOP counts
+1We are the UK's civic movement dedicated to averting the risks of superhuman artificial intelligence.
Measuring whether open weight models detect that they're being evaluated, whether they change behavior when they do, and whether that gap grows with capability using causal, white-box evidence.
Agent Island places agents in a rich social setting, similar to reality competitions like Survivor, to study multiagent interactions and the consequences of learning pressure in competitive settings.
+1A publication about the institutions we need for powerful AI.
Providing GPU credits and instructional support for 40 participants completing the ARENA AI Safety curriculum through Black in AI Safety and Ethics (BASE)
+1Research agenda aimed at developing methods for constructing powerful, easily interpretable world-models.
Dataset curation, synthetic data generation, and LLM training, fine-tuning, and evals to distinguish and quantify the effects of data improvements, separately from progress in algorithms and architectures, on AI capabilities.
A Veritasium for AI Safety.
Probe an open-weight model’s activations under biasing/cue conditions to test whether chain-of-thought explanations match internal reasoning, releasing paper, code, and datasets.
+1AI risk assessment currently checks few threat models and doesn't compose them into the aggregate risk that matters. We'll build a tool mapping what frontier system cards cover and omit, plus a paper on what the assessments miss.
+1A regularly updated catalogue of AI safety techniques, and of what is known - and what is not known - about their effectiveness and deployment status
+1TLDR: A representative survey with Yougov of the American public on questions about AI futures, including space governance, successionism, values.
+1
Humans in Control (HIC) is a nonpartisan grassroots advocacy organization focused on AI safeguards.
SafeBio-Registry: An Open-Source Verification, SpecDef Weight Locking and Unlearning Platform for Genomic and Protein Language Models
We want to investigate how AI agent overeagerness can backfire when exhibited in safety-critical scenarios.
A training methodology, and transcoder sets that allow to leverage heavy-weight interpretability methods, but made more lightweight for test-time analysis.
Identify what AI early risks or failures could be reported despite strategic rivalries towards a « safe culture » shaped after aviation
+1Safeguarding open-weight genomic foundation models through weight lock against adversarial finetuning
Implementing different types of unlearning methods for genomic and protein language models to remove sensitive biological information (e.g. pathogen virulence) while preserving predictive performance and scientific utility.
A participant-led unconference gathering the global AI safety community, online and at local sites, Nov 20-22, 2026.
Software to match people with shared AIS interests into teams that complete projects, increasing the odds that people beyond scarce talent pipelines upskill, develop credibility, and turn their ideas into output.
It's La Jetée (1962), the time-traveling film later adapted as 12 Monkeys (1995), but it's about X-risk and inspired by AI 2027 and it's directed by, and starring, myself and @p8stie. Ergo, La P8stée
A policy memo, co-authored with the Institute for Public Policy Research, resolving the open technical, economic, and legal questions blocking real-world implementation of token taxes.
Liaise helps close the generalist talent gap in AI safety by helping motivated non‑technical people enter with fluency, alignment, and a trusted network.
Submitting FOI requests across EU Member States to reveal how governments understand and address advanced AI risks, creating evidence for accountability, advocacy and stronger policy.
Funding compute/API costs for Incubator projects that build nonhuman welfare consideration into AI safety work
A hand-verified library of AI-safety theorem statements in Lean 4 with AI-generated proofs, building the skills to trust AI formalization.
Hosting a full day conference based in Sydney, Australia where young, aspiring students in senior high school and university interested in AI Safety can connect and share ideas
Making the mechinterp Discord more active through events and research projects.
Perform research to rigorously elucidate and quantify generalization versus memorization, and examine evidence of originality in LLMS.
I study how training processes produce models that behave deceptively and pursue hidden objectives, with scheming as the most consequential case.
Compression-based PAC-Bayes certification for frontier-scale LLM safety monitors, deployment setting shift, and modern post-training.
Research to scale midtraining for compassion using self-fulfilling alignment so that it robustly survives subsequent fine-tuning.
We have validated the artistic value of our show; this grant would test whether it can become a scalable and repeatable form of AI-safety outreach.
Deploying customer screening software at DNA synthesis providers to reduce AI-enabled biothreats
Identifying reasoning pathologies/disingenuous behavior in reasoning traces based on activation dynamics rather than apparent semantics
