Up to $500,000 in prizes for ML Safety benchmark ideas.
Get started Open Oct 2022–August 2023
Benchmarks should relate to Monitoring, Robustness, Alignment, or Safety Applications. You could concretize one of the example directions we've provided or propose a novel idea.
Submit a research paper or formalize your idea in a write-up using our guidelines. You are not required to provide a dataset with your submission.
Oct 2022–August 31, 2023
Early submissions will be eligible for feedback and resubmission.
Oct 2022-Oct 2023
We will award \$100,000 for outstanding benchmark ideas and \$50,000 for good benchmark ideas. We will award at least \$100,000 in prizes total and up to \$500,000 depending on the quality of the ideas submitted. For especially promising proposals, we may offer funding for data collection and engineering expertise so that teams can build their benchmark. Submissions will be judged by Dan Hendrycks, Paul Christiano, and Collin Burns.
Authors can choose to keep their proposals private during the competition (for example, if they are preparing a research paper); however, all winning and non-winning proposals and the names of the winners will eventually be made public for the sake of transparency. By default, we will release proposals several months after the competition ends, though this can be negotiated on a case-by-case basis.