Understanding the Theoretical Limits of AI-Enabled Pathogen Design: Insights from a Delphi Study

Concerns that artificial intelligence (AI) might enable pathogen design are increasing, but risks and timelines remain unclear. In this study, the authors present findings from a Delphi study designed to assess the near-term limits of AI-enabled biological design (AIxBio). Rather than forecasting specific risks, the authors' central objective was to identify which biological and AI-related constraints might serve as hard or persistent barriers to this specific misuse. To do so, they conducted two parallel Delphi elicitations, engaging experts in biology and AI to independently and comparatively evaluate the limits that each field faces. The authors asked participants in the study to assess the validity and applicability of a set of proposed constraints within the near-term future (from 2025 to 2027). The constraints included biological trade-offs, such as transmissibility and environmental stability, and technical challenges in data availability and AI model generalization. The overarching goal of this study is to inform policy and risk analysis by clarifying which scenarios fall outside the plausible envelope of near-future capabilities and which will remain impossible indefinitely. By focusing on what might be impossible or unlikely, this research can help refine the scope of biosecurity planning and improve the signal-to-noise ratio in discussions about AIxBio.