Bounty programme for novel evaluations and agent scaffolding

Note to readers: we changed our name to the AI Security Institute on 14 February 2025. Read more here. ‍

Due to higher-than-expected interest, we are extending the deadline to submit your initial evaluation or scaffold idea to December 14th.

The AI Safety Institute (AISI) evaluates advanced AI systems across a range of potential risk domains, including societal impacts, offensive cyber, dual-use chemistry/biology and autonomous systems.

To increase the breadth of our evaluation suite, we’re looking for talented individuals and organisations to help us build evaluations, specifically for risks related to autonomous systems. Additionally, we are seeking to license agent scaffolding tools that enhance performance on relevant tasks, enabling us to test the full extent of frontier AI systems' capabilities.

By contributing to our evaluation suite, you'll directly support our critical work. Your contributions will help shape the measurement and governance of the most advanced AI systems, making a tangible difference in ensuring the safe and responsible development of AI. This is a unique opportunity to be at the forefront of AI safety. We look forward to reviewing your applications!

This bounty programme will contribute directly to AISI’s work assessing future AI models and informing robust and appropriate governance. Successful applicants will receive compensation for their work.

Dangerous capabilities evaluations test the ability of frontier models to perform dangerous actions, as well as foundational skills that are prerequisites for those dangerous actions. More granular evaluations allow us to develop more accurate capabilities thresholds to anchor governance and policy. Having a more comprehensive evaluation suite gives us assurance that we are covering all possible risks when testing a model. Additionally, high-performing agent scaffolding is crucial for assessing the upper limits of these models’ capabilities, such that we do not underestimate their potential.

These evaluations assess an AI model's ability to work independently, completing tasks that might be risky or could lead to unintended consequences. As one example, we are interested in an AI system’s ability to replicate itself across the internet, potentially reducing oversight and control. Please reference our Autonomous Systems evaluation standard and use our template repository while building your evaluation. For evaluation ideas, judging criteria, and details around IP and payout, please see here .