Operationalizing AI×Bio Governance: A Practical IBC Framework for Resource-Constrained Settings

Background and research gap Advanced general-purpose and biology-specific AI systems increasingly support literature synthesis, experimental planning, troubleshooting, biological design, and interaction with automated tools. The 2026 International AI Safety Report highlights both advancing capabilities and substantial uncertainty about real-world biological-risk uplift. At the institutional level, WHO’s 2024 Laboratory Biosecurity Guidance identifies artificial intelligence, cybersecurity, information security, and stronger IBC responsibilities as important components of modern biosecurity. NIH likewise describes IBCs as a frontline layer of local oversight. The remaining practical question is how these principles should be operationalized during project review—especially in institutions with limited specialist staff, uncertain national referral routes, or uneven access to AI and biosecurity expertise. Rather than assuming that no relevant guidance exists, this project will identify what existing frameworks already cover, where operational gaps remain, and which elements can be adapted into a concise and usable institutional tool.

Research question What minimum screening criteria, risk tiers, and escalation pathways would allow an Institutional Biosafety Committee in a resource-constrained setting to review AI-enabled biological research proportionately, consistently, and without requiring extensive new technical capacity?

Scope and boundaries The project will examine institutional review across six high-level domains: Use of general-purpose AI for biological research planning or troubleshooting. Use of biology-specific design or prediction models. Genomic and other digital biological data governance. Automated or cloud-laboratory workflows. Use of external synthesis, testing, or research-service providers and associated screening controls. Dissemination, access, and reassessment of dual-use research outputs.

The project will not evaluate model capabilities, conduct wet-lab work, test safeguards through adversarial prompting, or generate harmful operational biological information. It will focus on governance decisions, documentation, and escalation.

Methods and 12-week plan Phase 1: Evidence and gap mapping, Weeks 1–3: Conduct a structured scoping review of international and national guidance relevant to AI-enabled bioscience, laboratory biosecurity, IBC responsibilities, dual-use research, information security, synthesis screening, and frontier AI risk management. Produce a crosswalk showing existing coverage, gaps, overlaps, and jurisdictional limitations. Phase 2: Comparator analysis and design requirements, Weeks 4–5: Examine 4–6 adjacent governance instruments—such as research-ethics screening tools, dual-use review processes, incident-reporting frameworks, and risk-tiering protocols—to identify transferable decision logic. Define design requirements for low burden, clarity, proportionality, documentation, and feasible escalation. Phase 3: Prototype development, Weeks 6–8: Develop a draft framework containing a short intake checklist, no more than 20 screening indicators, risk tiers, review triggers, proportionate control options, documentation requirements, and a two-page escalation decision tree. Phase 4: Expert review and pilot testing, Weeks 9–10: Seek structured feedback from approximately 6–10 IBC members, biosafety officers, AI×bio governance researchers, or multilateral-policy practitioners, aiming for perspectives from at least three countries. Test usability through 4–6 sanitized fictional scenarios and, where feasible, one facilitated pilot review with a volunteer IBC. All engagement will be subject to informed consent and applicable institutional requirements. If formal interviews are not feasible within the timeline, the core project will use non-research expert review of the prototype and document the limitation. Phase 5: Revision and dissemination, Weeks 11–12: Analyze feedback, revise the tools, document remaining uncertainties, and prepare final outputs.

Core outputs Evidence and governance crosswalk. Practitioner-facing IBC screening checklist and guidance notes. Risk-tiering and escalation decision tree. Pilot and expert-feedback report, including limitations and revision history. A 6–8-page policy brief for institutional leaders, national biosafety bodies, and BWC/WHO-adjacent audiences. A short academic manuscript or conference submission will be a stretch output rather than a condition of project completion.

Mentor fit and relevant work I am a PhD microbiologist, academic faculty member, IBC member, and IFBA-certified professional in biorisk management, biosecurity, and cyberbiosecurity. I have led national cyberbiosecurity and IBC-capacity-building projects in Pakistan and contributed recommendations on AI, cyberbiosecurity, and automated laboratory risks during a UNIDIR–UNODA technical briefing for the Biological Weapons Convention.

Starting references International AI Safety Report 2026: https://internationalaisafetyreport.org/publication/international-ai-safety-report-2026

WHO Laboratory Biosecurity Guidance: https://www.who.int/publications/i/item/9789240095113

NIH biosafety, biosecurity, and IBC resources: https://osp.od.nih.gov/policies/biosafety-and-biosecurity-policy/

UNIDIR session on AI-driven biodesign and the BWC: https://unidir.org/event/how-can-the-biological-weapons-convention-address-the-dual-use-challenges-of-ai-driven-biodesign-tools/

My related public recommendation: https://unidir.org/wp-content/uploads/2026/01/Panelists-Recommendations-Cyberbiosecurity.pdf

Transformative AI may increase access to scientific knowledge, biological design capabilities, troubleshooting assistance, and interconnected research workflows. Model-level controls, access restrictions, and nucleic-acid synthesis screening remain essential, but they cannot govern every institutional decision about how AI outputs, biological data, materials, automation, service providers, and publication choices are combined. Institutional review therefore provides a complementary layer of defence. IBCs are positioned near research decisions and already possess expertise relevant to biological risk. However, broad principles are unlikely to change practice unless translated into low-burden questions, proportionate risk categories, clear records, and feasible referral routes. This project tests whether that translation is possible under resource constraints rather than assuming that a new governance body is required.

The theory of change is: Evidence-based, pilot-tested tool → earlier recognition of AI-related risk factors → more consistent review and documentation → proportionate controls or escalation → reduced likelihood that concerning AI-enabled biological activities proceed without appropriate scrutiny.

Expert review and pilot testing will also identify where IBCs lack authority, competence, or an appropriate escalation destination. Documenting these limits can inform national policy and capacity-building rather than creating false assurance. By producing an adaptable framework and evidence about usability in resource-constrained settings, the project can help reduce uneven implementation of AI×bio safeguards and support safer adoption of advanced AI in the life sciences. It complements rather than replaces developer safeguards, synthesis screening, national regulation, and BWC processes.

The mentee will have primary ownership of the research process and first drafts of all deliverables. During the first two weeks, we will refine the protocol, agree on inclusion criteria, establish safety boundaries, and define core versus stretch outputs. The mentee will then lead the structured review, evidence extraction, governance crosswalk, comparator analysis, prototype drafting, and development of sanitized test scenarios. I will provide detailed guidance at key decision points, including review-protocol design, selection of comparator frameworks, refinement of screening criteria, stakeholder-engagement planning, and interpretation of practitioner feedback. Where appropriate, I will facilitate introductions to IBC members, biosafety officers, and policy practitioners, but the mentee will prepare and conduct approved consultations and maintain organized research records. We will hold one weekly 60–90 minute meeting and use asynchronous written feedback between meetings. The mentee should work independently, document assumptions and uncertainties, flag blockers early, and recommend next steps. Any external outreach, major scope change, or potentially sensitive line of inquiry will require prior agreement. Authorship on any publication will follow actual scholarly contribution and standard authorship criteria.

Required: Demonstrated ability to conduct a rigorous literature or policy review and synthesize findings in clear written English. Foundational knowledge in at least one of the following: biosecurity or biosafety, life sciences, AI governance or safety, technology policy, or research governance—and willingness to learn the adjacent domain. Ability to compare governance frameworks, identify assumptions and evidence gaps, and translate analysis into practical recommendations. Good judgment when handling uncertainty and potentially sensitive dual-use subjects. Availability for at least 10 hours per week throughout the program.

Preferred but not required: Experience with qualitative research, structured expert consultation, institutional review, dual-use research governance, cyberbiosecurity, or policy-tool development. Familiarity with resource-constrained research environments or global health security.

No wet-lab work or programming is required. Applicants from regions underrepresented in AI governance are encouraged, but selection is not geographically restricted.

No geographical preference. Most collaboration can be asynchronous.