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◎ Online

Hosted by Apart Research

AI Collusion Research Sprint is a three-day, hands-on AI safety event running 23–25 October 2026 online and at Collider in New York City. Over one intensive weekend, participants will design and run controlled experiments investigating when AI agents collude, how auditors can distinguish coordination from coincidence, which channels carry collusive behaviour, and how defenders might disrupt it. The sprint is organised by Apart Research with Poseidon Research and AE Studio, with an in-person hub hosted by Collider in New York on Saturday and Sunday. What you’ll work on Participants choose one open research question, build an experiment and write up their findings. Projects sit within three tracks: - Markets and collusion: examine which variables allow collusion to emerge, whether it survives changes in participants, how detection could improve, and which restrictions reduce collusion at the lowest cost. - Detection and audit: investigate which tasks encourage collusion, whether combining agents’ statements and actions improves detection, and what should qualify as convincing evidence in logged trajectories. - Carriers and countermeasures: test whether actions, tools or side channels can transmit coordination; whether trusted agents can disrupt it; how agents identify peers; and how coalitions respond when monitored. Each question connects to existing papers and open-source code. Practical resources include starter code, a weekend-sized project suggestion, a rough cost estimate and a route designed to run on a standard 16 GB laptop without a GPU. Format and who it’s for Teams of one to five people will select a track, develop a project and ship their results over three days. You do not need to arrive with a team, have previous sprint experience or possess an AI, machine learning or AI safety background. The programme is particularly relevant to quantitative finance professionals whose market intuition and data skills transfer naturally to the research questions. Engineers, researchers and participants from other industries are also welcome, with mixed teams encouraged. Prizes and next steps… Register for this event

Sponsors: Poseidon Research · AE Studio

◎ Online

Hosted by Apart Research

Build practical AI benchmarks, trust infrastructure and decision-support products online from 13–15 November 2026 in Apart Research’s three-day sprint. The AI x Epistemics Research Sprint examines how AI is changing what people and institutions believe, how they make decisions and how they coordinate. Organised by Apart Research, an independent AI safety research organisation, the event challenges participants to turn open research questions into tangible tools, studies and prototypes that support a healthier information environment. What you’ll do Working solo or in a team of up to five, you’ll choose an open problem, develop a project over one weekend and write up your findings. Possible outputs include a benchmark, verification signal, research study or user-facing product. Reading lists, datasets, design sketches and worked examples are provided as starting points, and several suggested projects require no machine-learning skills. The sprint offers four tracks, including an open track for broader questions in the field. Named areas include: - Model epistemics and decision-making evaluations: test whether models understand the strength of their claims, express confidence accurately, oversell evidence or change their position under pressure. Projects may also investigate benchmark gaming and whether honesty scores predict better decisions. - Trust infrastructure: explore auditable source-reliability scoring, provenance, tamper-evident records and signals that help people and AI agents check claims and trace their origins. The wider goal is to make verification cheap, routine and difficult to manipulate. - Epistemic products: build and assess tools that improve real decisions, for example, evaluating advice users act upon, testing whether chatbots escalate disputes, creating briefings for consequential choices or surfacing disagreements and key cruxes within groups. - Open questions: tackle larger meta-level problems surrounding AI, knowledge, coordination and adoption.… Register for this event