AI in Science and Society

The Science of Trustworthy AI program from Schmidt Sciences funds technical research to understand, predict, and control risks from frontier AI systems. The 2026 RFP offers two funding tiers: Tier 1 up to $1 million and Tier 2 from $1 million to $5 million or more, each spanning one to three years.

The research agenda focuses on three aims: characterizing misalignment in frontier AI, developing generalizable measurements and interventions, and overseeing AI systems with superhuman capabilities including multi-agent risks. Proposals are open globally to universities, national laboratories, institutes, and nonprofit research organizations, with preference for multi-PI collaborations.

Schmidt Sciences also provides compute resources, software engineering support, and API credits with frontier model providers. Indirect costs must not exceed 10 percent.

2026 Science of Trustworthy AI RFP - Schmidt Sciences Opportunities for Funding Stay up to date on the latest news, stories and funding announcements.

Science of Trustworthy AI 2026 Science of Trustworthy AI RFP Schmidt Sciences invites proposals for the Science of Trustworthy AI program , which supports technical research that improves our ability to understand, predict, and control risks from frontier AI systems while enabling their trustworthy deployment.

May 17, 2026, 11:59PM AoE Tier 1: Up to $1M (1-3 years) Tier 2: $1M – $5M (1-3 years) Submit Applications via Survey Monkey Previous awards under program ‎‎ ‎ ‎ March 11, 2026, 10-11am ET. Register here April 15, 2026, 2-3pm ET. Register here This Request for Proposals is grounded in our Research Agenda , which defines the scientific scope and priorities.

The questions in each subsection guide what we consider in scope; they are not an exhaustive checklist. Proposals need not match any question(s) verbatim, but should clearly advance the underlying scientific objectives of our research agenda and explain why the work advances the science of trustworthy AI.

We expect strong proposals—especially at funding Tier 2—to take a clear stand on a small number of core questions and pursue them deeply, rather than addressing many agenda items superficially.

The research agenda has three connected aims: Aim 1 : Characterize and forecast misalignment in frontier AI systems: why frontier AI training-and-deployment safety stacks still result in models learning effective goals that fail under distribution shift, pressure, or extended interaction.

Aim 2 : Develop generalizable measurements and interventions: Advance the science of evaluations with decision-relevant construct and predictive validity, and develop interventions that control what AI systems learn (not just what they say).

Aim 3 : Oversee AI systems with superhuman capabilities and address multi-agent risks: develop oversight and control methods for settings where direct human evaluation of correctness or safety isn’t feasible, and address risks that emerge from interacting AI systems. Preference will be given to proposals from collaborations among multiple PIs and labs.

For Aim 3, we are considering grouping projects together to expedite rapid empirical progress on effective superhuman oversight. More broadly, we encourage collaboration across this agenda and expect to support shared compute and targeted convenings, where helpful. We invite applicants to apply to either or both funding tiers.

Applicants may submit more than one proposal to each tier. Tier 1: Up to $1M (1-3 years) Tier 2: $1M-5M+ (1-3 years) Although we expect to fund projects at both tiers, we are most interested in ambitious Tier 2 proposals that, if successful, would change what the field believes is possible for understanding, measuring, or controlling risks from frontier AI systems.

Schmidt Sciences aims to support the compute needs of ambitious and risky AI research. Applicants may request either funding for compute or access to Schmidt Sciences’ computing resources (subject to availability and terms). The computing resources offer access to cutting edge GPUs and CPUs, accompanied by large-scale data storage and high-speed networking.

Please see the application for more information.

Beyond compute, Schmidt Sciences offers a range of support: Software engineering support through the Virtual Institute for Scientific Software API credits with frontier model providers Opportunities to engage with the program’s community through convenings and workshops We invite individual researchers, research teams, research institutions, and multi-institution collaborations across universities, national laboratories, institutes, and nonprofit research organizations.

We are open globally and encourage collaborations across geographic boundaries. Indirect costs must be at or below 10% to comply with our policy . Proposals will be evaluated by Schmidt Sciences staff and external reviewers holistically.

Key considerations include: Research Agenda Fit. Does the proposal clearly engage with the intention behind the scientific questions and objectives in the research agenda? Scientific Quality and Rigor.

Is the proposed work technically sound, well-motivated, and capable of producing generalizable insight? Potential Impact. If successful, would it materially advance the science of trustworthy AI and is there a plausible argument for why this will meaningfully reduce risks from frontier AI systems (ideally through ambitious, field-shaping contributions)?

Feasibility and Scope. Is the project appropriately scoped for the requested budget and duration? Team Expertise.

Is the team well-suited to execute the proposed work, with relevant technical expertise, sufficient capacity, and a level of time commitment commensurate with the ambition of the project? Cost Effectiveness . Is the proposed budget reasonable and well-justified given the project’s goals and planned activities?

Tiers 1 and 2 have the same selection criteria, with a higher bar for tier 2 projects. For Tier 2, priority will be given to projects which are demonstrably a primary focus for the lead investigator(s).

Common reasons proposals are non-competitive Proposals lack a core focus Proposals suggest tools/benchmarks/evaluations without a credible validity argument (e.g., construct validity, predictive validity, robustness under optimization pressure) Proposals describe vague methods (“we will explore…”) instead of concrete activities, experiments, analyses, and baselines Proposals do not state clearly what would happen if the project succeeds, and what we learn if it fails Opportunities for Funding The technical storage or access that is used exclusively for statistical purposes.

The technical storage or access that is used exclusively for anonymous statistical purposes. Without a subpoena, voluntary compliance on the part of your Internet Service Provider, or additional records from a third party, information stored or retrieved for this purpose alone cannot usually be used to identify you.

The technical storage or access is required to create user profiles to send advertising, or to track the user on a website or across several websites for similar marketing purposes. Manage {vendor_count} vendors Read more about these purposes