AI-Biosecurity Governance

Examine a comprehensive governance framework for dual-use AI that can design novel biological agents. Identify risk categories (biosecurity, safety, dual-use misuse), governance layers (research screening, access controls, licensing, ongoing oversight), technical safeguards (model alignment, red-teaming, anomaly detection), and international collaboration. Outline an evaluation metric suite, incident response playbooks, and a stage-based risk mitigation plan for researchers, publishers, platforms, and funders. Compare different international approaches and propose a balanced path forward that preserves beneficial research while reducing risk.