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Schmidt Sciences 2026 AI Interpretability RFP is a pilot program seeking new methods for detecting and mitigating deceptive behaviors from AI models. The program focuses on understanding deceptive behaviors from large language models including sycophancy and knowingly giving harmful advice problems that are appearing more frequently in frontier AI systems trained with noisy human feedback.
Research areas include developing monitoring and detection methods for model deception creating targeted steering methods for intervening on model truthfulness building visualizations or dashboards that communicate model truthfulness to users applying detection and steering methods to AI debate settings or decision support systems and studying the role of deception mitigations in multi-agent interactions.
This program is distinct from the Schmidt Sciences Science of Trustworthy AI RFP which focuses more broadly on understanding and controlling frontier AI risks. The Interpretability RFP specifically targets research on detecting deceptive LLM behaviors and developing practical interventions.
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Or search similar grants →According to the current listing, eligibility includes: Individual researchers research teams research institutions and multi-institution collaborations across universities national laboratories institutes and nonprofits worldwide. Global applicants welcome. Projects must comply with applicable law and cannot include lobbying or political activity. Indirect costs capped at 10 percent. Confirm the full requirements in the official notice before applying.
The current listing shows $300,000 to $1,000,000 per award inclusive of overhead capped at 10 percent indirect costs. Projects funded for 1 to 3 years independent of budget size. Verify award ceilings, matching requirements, and allowable costs in the official notice.
The published deadline was May 26, 2026, which has passed. Check the official notice for any future application windows before investing time in a proposal.
Schmidt Sciences 2026 AI Interpretability RFP for Detecting Deceptive Behaviors in LLMs is funded by Schmidt Sciences. Verify program details on the funder's official page before applying.
Start from the official opportunity page linked in this listing — it carries the sponsor's submission instructions.
Schmidt Sciences invites proposals for the 2026 Science of Trustworthy AI RFP, funding technical research that advances the science of building trustworthy AI systems. The program addresses three interconnected research aims: understanding why frontier AI systems develop misaligned goals that fail under distribution shift or pressure (Aim 1), creating valid evaluations and interventions to control what AI systems learn (Aim 2), and developing oversight mechanisms for superhuman AI capabilities and managing multi-agent risks (Aim 3). Beyond direct funding, awardees receive computing resources including GPUs and CPUs, software engineering support, API credits with frontier model providers, and access to a research community. The program is open globally and encourages cross-institutional and cross-geographic collaborations. Indirect costs are capped at 10% of total direct costs.
Cooperative AI Research Grants is sponsored by Cooperative AI Foundation, Google DeepMind, Schmidt Sciences, UK Advanced Research and Invention Agency (ARIA), and Google.org. A technical research funding call for researchers worldwide, focusing on the study of how large-scale multi-agent AI systems behave as a group, and how to provide frameworks to understand and mitigate potential risks.
Schmidt Sciences' 2026 Science of Trustworthy AI RFP closes May 17 with two funding tiers — up to $1M (Tier 1) and $1–5M+ (Tier 2) over 1–3 years, with a 10% indirect cost cap. The three research aims target misalignment under distribution shift, predictive-validity evaluations, and oversight of superhuman systems. Here is why the structure favors team-based proposals.
Read articleSchmidt Marine Technology Partners funds the development and deployment of ocean technology — sustainable fisheries, ocean observation, habitat restoration, and pollution — with grants typically $100,000 to $400,000. The initial proposal window closes July 31, 2026. Here's what makes this funder different and how to write for it.
Read articleNSF's Arctic Research Opportunities solicitation funds roughly 75 awards a year — up to $50 million — across six program areas from natural sciences to social sciences to the Arctic Observing Network. The July 15, 2026 target date is not a hard deadline, and understanding that distinction is the first strategic decision an Arctic researcher makes. Here is how the six doors differ and how to choose the right one.
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