Know Your Scientist: KYC as Biosecurity Infrastructure
Jonathan Feldman, Tal Feldman, Annie I Anton
TL;DR
The paper addresses the dual-use risks posed by advances in biological AI and argues that model-level restrictions are inadequate for biology. It introduces a three-tier KYC framework—Tier I institutional gatekeeping, Tier II output screening, and Tier III behavioral monitoring—inspired by AML practices to shift governance toward user verification and traceability. The approach leverages existing institutional infrastructure, emphasizes shared responsibility, and outlines voluntary adoption, standardization pathways, and high-risk federal oversight as needed. This framework aims to preserve legitimate research access while increasing the cost and difficulty of misuse through accountability, monitoring, and information sharing, with immediate implementability and a roadmap for future refinement. The work highlights limitations and open questions, advocating proactive governance to stay ahead of rapidly evolving biological design capabilities.
Abstract
Biological AI tools for protein design and structure prediction are advancing rapidly, creating dual-use risks that existing safeguards cannot adequately address. Current model-level restrictions, including keyword filtering, output screening, and content-based access denials, are fundamentally ill-suited to biology, where reliable function prediction remains beyond reach and novel threats evade detection by design. We propose a three-tier Know Your Customer (KYC) framework, inspired by anti-money laundering (AML) practices in the financial sector, that shifts governance from content inspection to user verification and monitoring. Tier I leverages research institutions as trust anchors to vouch for affiliated researchers and assume responsibility for vetting. Tier II applies output screening through sequence homology searches and functional annotation. Tier III monitors behavioral patterns to detect anomalies inconsistent with declared research purposes. This layered approach preserves access for legitimate researchers while raising the cost of misuse through institutional accountability and traceability. The framework can be implemented immediately using existing institutional infrastructure, requiring no new legislation or regulatory mandates.