From Circuits to Containment: Mechanistic Interpretability as a Tool for AI Biosecurity Governance

Artificial intelligence systems are increasingly capable of assisting with biological research — accelerating drug discovery, modelling protein structures, and synthesising literature across the life sciences. This same capability introduces a critical and underexplored biosecurity risk: AI systems may be exploited to generate, optimise, or disseminate information enabling the creation of dangerous biological agents. Existing governance frameworks for AI biosecurity rely predominantly on output-level filtering — screening generated text after it has been produced. This approach is reactive, brittle, and insufficient for frontier models capable of sophisticated reasoning.This paper proposes a complementary framework grounded in mechanistic interpretability: by identifying and monitoring the internal neural circuits that activate during biological hazard reasoning, we can develop proactive, auditable biosecurity governance tools that intervene before harmful outputs are produced. We propose a three-layer architecture — (1) Circuit Identification Layer, mapping hazard-relevant neural circuits; (2) Signal Translation Layer, converting internal activations into interpretable biosecurity risk indicators; and (3) Governance Interface Layer, embedding these signals in institutional monitoring dashboards and decision-support tools.The framework is grounded in the biological analogy of immune surveillance: robust containment requires redundant, threshold-based detection mechanisms operating at multiple levels. We connect this to formal evolutionary game theory results (Ochola, 2025) demonstrating threshold dynamics in alignment monitoring. Applications include dual-use research of concern (DURC) monitoring, AI biosafety level classification, and deployment in resource-constrained research environments. The paper directly addresses the governance challenges of AI adoption in the Global South, where powerful AI tools are deployed without commensurate biosecurity oversight infrastructure.