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Superalignment Fast Grants

Justin Jay Wang ✗ DALL·E

We’re launching $10M in grants to support technical research towards the alignment and safety of superhuman AI systems, including weak-to-strong generalization, interpretability, scalable oversight, and more.

We believe superintelligence could arrive within the next 10 years. These AI systems would have vast capabilities—they could be hugely beneficial, but also potentially pose large risks.

Today, we align AI systems to ensure they are safe using reinforcement learning from human feedback (RLHF). However, aligning future superhuman AI systems will pose fundamentally new and qualitatively different technical challenges. 

Superhuman AI systems will be capable of complex and creative behaviors that humans cannot fully understand. For example, if a superhuman model generates a million lines of extremely complicated code, humans will not be able to reliably evaluate whether the code is safe or dangerous to execute. Existing alignment techniques like RLHF that rely on human supervision may no longer be sufficient. This leads to the fundamental challenge: how can humans steer and trust AI systems much smarter than them? 

This is one of the most important unsolved technical problems in the world. But we think it is solvable with a concerted effort. There are many promising approaches and exciting directions, with lots of low-hanging fruit. We think there is an enormous opportunity for the ML research community and individual researchers to make major progress on this problem today. 

As part of our Superalignment project, we want to rally the best researchers and engineers in the world to meet this challenge—and we’re especially excited to bring new people into the field.

Superalignment Fast Grants

In partnership with Eric Schmidt, we are launching a $10M grants program to support technical research towards ensuring superhuman AI systems are aligned and safe:

  • We are offering $100K–$2M grants for academic labs, nonprofits, and individual researchers.

  • For graduate students, we are sponsoring a one-year $150K OpenAI Superalignment Fellowship: $75K in stipend and $75K in compute and research funding.

  • No prior experience working on alignment is required; we are actively looking to support researchers who are excited to work on alignment for the first time.

  • Our application process is simple, and we’ll get back to you within four weeks of applications closing.

With these grants, we are particularly interested in funding the following research directions(opens in a new window):

  • Weak-to-strong generalization: Humans will be weak supervisors relative to superhuman models. Can we understand and control how strong models generalize from weak supervision

  • Interpretability: How can we understand model internals? And can we use this to e.g. build an AI lie detector?

  • Scalable oversight: How can we use AI systems to assist humans in evaluating the outputs of other AI systems on complex tasks?

  • Many other research directions, including but not limited to: honesty, chain-of-thought faithfulness, adversarial robustness, evals and testbeds, and more.

For more on the research directions, FAQs, and other details, see our Superalignment Fast Grants page(opens in a new window).

Join us in this challenge

We think new researchers could make enormous contributions! This is a young field with many tractable research problems; outstanding contributions could not just help shape the field, but be critical for the future of AI. There has never been a better time to start working on alignment.




Leopold Aschenbrenner, Jan Leike, Sherry Lachman, Aleksander Madry, Chris Clark, Collin Burns, Pavel Izmailov, Nat McAleese, William Saunders, Bobby Wu, Lisa Pan, Janine Korovesis, Ilya Sutskever, Elie Georges, Kayla Wood, Kendra Rimbach, Thomas Degry, Ruby Chen