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AI safety fellowship to upskill local talent, build a pipeline of people who understand AI safety deeply enough to contribute to research, advise on policy, and coordinate when AI governance decisions are being made.
Three members of PauseAI Canada would like to attend PauseCon 2026 in London, England. We will require funds for travel from Montreal and Winnipeg, accommodation for one night, food, and other expenses.
Benchmark for agents spending human money - paybench.org
Building computational tools to identify and address pathological behavioral states in conversational and autonomous AI
An AI safety community that trains professionals and researchers to become competent AI safety contributors within industries and the academia, by learning and doing something.
AIxBio Africa is a five-week remote fellowship mentoring early-career researchers on Africa-relevant projects at the intersection of AI safety, biosecurity, governance and public health, producing publishable outputs.
An LLM benchmark for emergency response communications in existential catastrophes.
A dangerous-capability benchmark testing whether frontier LLMs can extract sensitive attributes from anonymized brain recordings, enable adversaries to build privacy-violating tools, or over-refuse legitimate neuroscience queries.
A high-production visual journalism series combining primary-source data and motion graphics to break down the mechanics, safety crises, linguistic biases, and Arab-world implications of transformative AI.
Feature-length documentary that captures the intellectual and cultural zeitgeist surrounding frontier AI at the moment before AGI, and communicates X-Risk ideas to a broad range of elites.
Multi-agent cooperative contractual obligation framework.
Audit and brief Philippine agencies to update compute export-control rules, border identification, inspections, and a compute registry to govern frontier AI chips ahead of the Pax Silica hub.
Defining which sequences are dangerous enough to screen for, so providers and regulators screen consistently
An open, cheap method that detects when an inoculation prompt inoculates against off-target traits, so labs and developers can catch undesired trait/persona cha
Detailed models of how delegating critical functions to AI agents could destabilise strategic stability: pathways, likelihoods, and defenses.
There's an asymmetry between the level of communication about AI capabilities, compared to AI risks. If we hit AGI tomorrow, the world would not be prepared.
Funding compute/API costs for Incubator projects that build nonhuman welfare consideration into AI safety work
Drone swarms hunting people in the woods, as a less-dry video explainer of risks from AI.
Build a digital intervention that measures the human time needed to produce AI-generated outputs
A diagnostic evaluation framework that tells whether computer-use agent attacks fail because the agent is robust, refused, never saw the attack, or was simply unable to execute the harmful action.
We are building the first AI policy and safety talent pipeline at Yale University to equip future global decision-makers with frontier AI risk literacy and technical governance tools.
How exactly does scaling inference compute affect the performance and reliability of LM agents in agentic benchmarks? We believe that most current evaluations underestimate performance because they do not account harness.
Assess AI-enabled biosecurity safeguards in Nigeria by reviewing governance, red-teaming frontier models with local language/culture, and testing DNA synthesis screening for orders from resource-limited settings.
Extend recently developed deception detection+steering method to larger and more diverse open-weight models, releasing the tooling that makes frontier-scale honesty interventions reproducible.
An open-source library that both detects self-chosen deception in open-weight LLMs and steers the model back toward honesty at inference — the correction half that current honesty tools lack.
proofbundle lets people verify AI safety evaluation results offline instead of trusting a number in a PDF and it catches if an evaluation record was altered or swapped
Coordination Studies is a new field-building project oriented towards solving coordination problems and designing new coordination mechanisms.
An open benchmark measuring how model honesty survives long, pressured conversations and multi-agent interaction - lying, sycophancy, and calibration tracked turn by turn
*Comprehension audits* are a novel development-process assurance mechanism to verify human understanding of AI research outputs to act as a gate to slow automation of AI R&D.
Post-training virtue into open models as a third alignment technique and control mechanism
6 months of salary support for my research and operations work to help found a quasi-governmental AI safety institution, the [Estonian AI Security Institute](https://www.aisi.ee/) (Turvalise Tehisaru Teadmuskeskus T3).
Run AgentHarm on 3–4 frontier/open-weight models, manually audit transcripts for metric gaming and spurious failures, compare to prior critiques, and publish a detailed evidence-based writeup.
Free, open, forkable safety infrastructure for agentic AI: a peer-reviewed pathology nosology, a safety runtime with reproducible benchmarks, and enforcement gating every agent tool call against human-authored policy.
An open benchmark and causal interpretability study of when individually power-motivated LLM agents compete, form coalitions, collude, or betray—and whether internal signals reveal these shifts before behavior does.
A strategic model of governance under uncertainty: how disagreement about AI consciousness undermines the coordination that keeps AI risks in check.
Career transition grant to allow for research focused on how advanced AI models may be used to concentrate power in middle powers
Build an open-source RL environment using Ramulator and real disturbance data to post-train language models to exploit simulated DRAM RowHammer vulnerabilities, plus write-up/blog and trained models.
Neutral, reproducible benchmark measuring whether AI memory systems update correctly when facts change — every major system in one open table, October 2026.
Educate everyday people on AI risk, and bring marginalized voices into the global AI conversation.
Demystifying AI evaluation research by lowering technical barriers through practical, open evaluation infrastructure.
A mechanism for evolutionary post training in models using activation steering based methods.
With raise of GDN and different sorts of attention meachanisms, those are much closer to lstm/recurrent architectures being very stateful rather than normal attention, we aim to explain explore common patters in lstm and GDN.
Facilitating AI X-risk Education in India, Southwest Cameroon, and beyond!
NTU AI Safety seeks $13k for organizer stipends to expand Taiwan’s first student AI safety group into three reading-group tracks (fundamentals, technical, policy/governance) and grow outreach.
Next year of Commec (the Common Mechanism), the free, open-source, globally-available DNA synthesis screening tool hosted by IBBIS
Deigned to get everyday people more knowledgable and more invested in AI Safety causes! Designed similarly to Dave Jorgenson's "Local News International".
Accepted paper at Mechanistic Interpretability for Foundation Models workshop.no travel funding. Early Career Researcher
Expand Humanity Tomorrow with a multilingual, jargon-free AI existential-risk section featuring a comprehensive FAQ, field map, action recommendations, and supporting visuals/audio, plus outreach and maintenance.
Seeking travel and registration fee support to present my sole-authored mechanistic audit of medical AI at MICCAI 2026 MI4MedFM workshop at Strasbourg, France
Giving people and their prosocial agents ergonomic SQL query power over the internet, with structured judgement kernels to organize the information across interpretable high-dimensional axes.
