Know Your Scientist: KYC as Biosecurity Infrastructure
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 11 of its 101 references that are in the map. First posted on arXiv 5 Feb 2026.
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11 of 101 references.
References · 11
- 2025Protein Large Language Models: A Comprehensive Surveycited by 18
- 2023Protecting Society from AI Misuse: When are Restrictions on Capabilities Warranted?cited by 15
- 2023Oversight for Frontier AI through a Know-Your-Customer Scheme for Compute Providerscited by 12
- 2025On the Impossibility of Separating Intelligence from Judgment: The Computational Intractability of Filtering for AI Alignmentcited by 12
- 2020Monitoring Misuse for Accountable 'Artificial Intelligence as a Service'cited by 6
- 2023Towards Responsible Governance of Biological Design Toolscited by 5
- 2024FoldMark: Protecting Protein Generative Models with Watermarkingcited by 5
- 2025Generative AI for Biosciences: Emerging Threats and Roadmap to Biosecuritycited by 4
- 2025Open-weight genome language model safeguards: Assessing robustness via adversarial fine-tuningcited by 4
- 2025Biothreat Benchmark Generation Framework for Evaluating Frontier AI Models I: The Task-Query Architecturecited by 3
- 2025Resilient Biosecurity in the Era of AI-Enabled Bioweaponscited by 2
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