Prioritizing Feasible and Impactful Actions to Enable Secure AI Development and Use in Biology

As artificial intelligence continues to enhance biological innovation, the potential for misuse must be addressed to fully unlock the potential societal benefits. While significant work has been done to evaluate general-purpose AI and specialized biological design tools (BDTs) for biothreat creation risks, actionable steps to mitigate the risk of AI-enabled biothreat creation are underdeveloped. This paper provides policy and technology strategies collected from a diverse range of sources placed in the context of an organizing framework aligned with steps in the AI-enabled creation of a biothreat. After collating previous reports (typically on one or a small set of mitigation options) and evaluating the proposed mitigation options by projected feasibility and impact, we prioritize development of seven mitigation strategies (with a total of twelve individual mitigations): model unlearning and information removal techniques (a combination of five mitigations), classifier-based input and output filtering for BDTs, AI agents for biosecurity, safety bug bounty programs, ensuring enforcement of existing material/equipment protections, enhancing biosurveillance and bioattribution, and screening metadata/audit logs before DNA synthesis. We invite collaboration among policymakers, researchers, and technologists to refine and implement these strategies into a strong layered defense, ensuring that AI can be used safely and securely to the benefit of all.