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Assess the model, dataset, documentation, and access method together; screen the proposed release for plausible accidental exposure and deliberate misuse; then choose a proportionate release path and record who approved it, what uncertainty remains, and when the decision must be revisited. A staged review—initial screening, deeper review where warranted, and mitigation before release—is more useful than treating publication as a one-time yes-or-no gate. No single release threshold applies everywhere, so involve the relevant institutional biosafety and biosecurity officers and follow applicable legal and regulatory oversight.
What does a biosecurity assessment of an AI release cover?
It is a documented review of whether sharing research materials could make biological information, technology, or capability available in ways that create foreseeable harm, and of how to reduce that risk while preserving legitimate scientific and public benefit. It should cover deliberate misuse as well as accidental exposure, and it should examine the complete release package rather than only the model file or dataset.
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The World Health Organization’s Laboratory biosecurity guidance (2024) describes a whole-value-chain approach: “The WHO laboratory biosecurity guidance follows and complements the revision of the Laboratory biosafety manual, fourth edition and provides principles and measures to prevent lapses and incidents throughout the whole value chain of handling high-consequence biological material, technology and information.” For an AI project, that means considering creation, storage, documentation, transfer, access, reuse, and later changes—not just the moment a download link is posted.
Biosecurity and biosafety are related but distinct. WHO’s guidance addresses potential deliberate misuse of biological material, technology, and information. Biosafety is concerned with accidental exposure or release. A release assessment should consider both where relevant, rather than assuming that a project with no physical laboratory work has no biosecurity implications: WHO’s guidance includes information security and emerging technologies such as AI among its considerations.
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The review is about decisions and controls, not a prediction that a particular person will misuse a particular artifact. WHO calls for consequence-driven assessment, while UK government guidance on frontier-AI safety says to consider possible low-probability, high-consequence risks alongside benefits. That supports careful examination of plausible outcomes without treating uncertain possibilities as established facts.
How do I assess biosecurity risks before sharing an AI model?
Use a staged process: describe the purpose and release package, screen for relevant concerns, investigate higher-risk cases in more depth, compare release options, and document mitigations and approval. This adapts the staged approach in NTI’s 2025 Guidance for Assessing Biosecurity and Biosafety Risks; it is a practical decision process, not a universal scoring system or substitute for institutional review.
- Write down the purpose and benefit. Identify the scientific or public-interest value of sharing, who is expected to benefit, and why release is needed for that benefit. Compare those benefits with reasonably foreseeable harms instead of assuming that openness is automatically beneficial or that restriction is automatically safer. Explain whether the same benefit could be achieved with a less detailed artifact, a narrower audience, or a delayed release.
- Inventory the whole release. Describe the model, dataset, documentation, examples or other accompanying information, and proposed access method. Include interfaces, model cards, evaluation reports, notebooks, prompts, metadata, and packaging when they are part of what recipients will receive. Consider what the items reveal in combination: a dataset, a model trained on it, and explanatory documentation may expose different information separately than they do as one package. OECD responsible-AI due-diligence guidance considers risk at the data level, model level, and where those risks intersect.
- Screen the context and plausible consequences. Ask who could obtain the material under the proposed arrangement, what relevant information or capability it could make available at a high level, and what accidental exposure or deliberate misuse could mean. Consider recipient expertise, institutional setting, geographic and legal context, and whether onward sharing is possible. Record uncertainties and the assumptions behind the screen; do not turn an unsupported guess into a precise risk score.
- Escalate when the initial screen warrants it. Route proposals with unresolved or potentially high-consequence concerns to qualified institutional biosafety or biosecurity reviewers and relevant domain experts for a detailed assessment. NTI’s funder framework uses rapid screening followed by detailed review of higher-risk proposals and mitigation. It explicitly excludes AI-enabled biological design, synthesis, or optimization that could lead to physical biological outputs, so it is not a complete framework for those cases.
- Compare release paths. Consider public release, controlled access, staged disclosure, withholding sensitive portions, or not releasing. Evaluate each path against the benefit it enables, the information exposed, the intended audience, the feasibility and limits of safeguards, and whether access can be monitored or revised.
- Choose mitigations and an accountable decision. Select safeguards that are feasible for the proposed path, assign decision owners, record residual uncertainty, and state what changes would require review again. If important risks cannot be addressed to the satisfaction of the responsible reviewers, delay, narrow, or withhold the release rather than treating approval as inevitable.
What questions belong in the initial screen?
A short screen should be consistent enough that similar proposals receive comparable attention, while leaving room for expert judgment. Ask what biological information or capability is represented; whether the release could expose information unintentionally through documentation, metadata, or examples; who the intended and realistically reachable audiences are; and what consequences could follow from accidental disclosure, deliberate misuse, or uncontrolled onward distribution. Note whether the proposed audience, access method, or combination of files differs from the setting in which the material was developed.
The screen should also identify matters that require escalation rather than attempting to resolve them. Examples include uncertainty about what a model can enable, disagreement among reviewers, a proposed audience with no practical access controls, or a connection to AI-enabled biological design, synthesis, or optimization that could lead to physical biological outputs. A concise explanation of why a question is unresolved is more useful than an invented numerical rating.
Should I release the dataset, the model, or both?
Assess the dataset and model as related parts of one information package, then decide separately whether each component—and their combination—should be shared. A model-only release is not automatically safe, and a dataset-only release is not automatically low risk; the relevant question is what information the combined release makes available in its actual context.
For each component, document what it contains or enables at a high level, who would receive it, and what additional context accompanying materials provide. Then assess the intersection: whether access to one part changes what a recipient can learn or do with another. OECD guidance highlights data-level, model-level, and intersection risks and recommends tailoring disclosure to the audience. This argues against applying a single blanket release decision to every file in a project.
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Where the value of sharing differs by component, consider releasing less sensitive portions or using different access arrangements for different materials. Staged disclosure can preserve some collaboration or scrutiny while limiting broad access to information that warrants more review. The appropriate boundary is context-dependent; the guidance does not establish a universal rule for which component must always be released first.
Which release option should I choose?
There is no universally safest or best option. Public access can support transparency and collaboration, while broad availability can also spread sensitive information or capability; controlled and staged approaches may limit exposure but depend on safeguards that have practical limits. The comparison below is an editorial decision aid synthesized from OECD and UK guidance, not a standardized rubric.
| Release path | Access and information exposed | Controls and trade-offs to examine |
|---|---|---|
| Public release | Broadest access; the released materials and their documentation are generally available without recipient-specific selection. | Can support transparency, scrutiny, and collaboration. Consider the consequences of making potentially dangerous capability information broadly available; after public disclosure, the source guidance does not establish a way to reliably withdraw it. |
| Controlled access | Access is limited to selected recipients under an access arrangement. | Consider how recipients are selected, what information each receives, and whether access can be monitored or revised. Safeguards have feasibility limits and should not be treated as a guarantee against misuse or further disclosure. |
| Staged disclosure | Information is shared in phases or at different levels of detail, rather than all at once. | Can tailor disclosure to the audience and preserve some benefits of collaboration. Define who decides whether a later stage is appropriate and what new information or review supports that decision. |
| Withhold sensitive portions | Some parts are shared while other portions remain undisclosed or under tighter access. | Can reduce the information exposed while allowing a narrower release. Assess whether the shared pieces, documentation, or combination still reveal information that changes the risk. |
| Do not release | No external access to the proposed material under the current decision. | Avoids exposure through that release, but forgoes the proposed public or scientific benefits. Record the rationale and any conditions under which the decision could be reconsidered. |
For each option, compare six questions: how broad is access; how sensitive and detailed is the information exposed; what recipient context and access controls apply; can access be monitored or revised; what scientific or public benefit is expected; and are the safeguards feasible given their limits? These axes help make the trade-off explicit, but they do not produce a validated numerical threshold. OECD describes openness and restriction as an ongoing governance challenge, and the UK guidance cautions against public release of dangerous capability and production details.
How should safeguards be matched to the release?
Safeguards should be tied to the specific exposure the chosen path creates. For a controlled or staged release, define the eligible audience, the information each audience receives, the responsible access decision-maker, and how changes in audience or scope are handled. For a partial release, check that omitted portions are not effectively reconstructed from the remaining files, examples, or explanatory material. For any path, document what monitoring or traceability is possible and where it ends.
Do not describe an access agreement, review committee, or monitoring process as eliminating risk. OECD’s due-diligence approach and UK safety practice emphasize continuing governance, while practical controls can fail, be bypassed, or become obsolete when a model, dataset, or context changes. State those limits explicitly and identify the residual uncertainty accepted by the decision owner.
What should the written review record?
A review record should let another responsible reviewer understand the decision, its reasoning, and the conditions that would change it. The following checklist turns the guidance into a usable record; it is not a claim that every institution uses an identical form.
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- Purpose and beneficiaries: the scientific or public-interest value, who benefits, why the proposed sharing is relevant, and why a less exposed alternative would or would not suffice.
- Release inventory: model, dataset, documentation, other accompanying information, access method, intended audience, and the information the combined package could make available.
- Risk context: plausible accidental exposure and deliberate misuse, relevant audiences, potential consequences at a high level, assumptions, and unresolved uncertainty.
- Screening and escalation: the initial questions considered, issues sent to deeper review, experts consulted, and any limits on the framework used.
- Options considered: public, controlled, staged, partial, or no release, with the expected benefit and exposure trade-off for each option considered.
- Mitigations and limits: chosen safeguards, who is responsible for them, how they will be checked, and what they cannot reliably prevent.
- Accountability: the decision owner, reviewers consulted, approval or escalation status, and any conditions on the decision.
- Review triggers: material changes to the model, dataset, documentation, access arrangement, audience, or relevant context that would prompt reassessment.
State uncertainty plainly. A review should distinguish what is known about the proposed package from what is uncertain, identify where expert judgment is needed, and preserve dissenting views when they affect the decision. Unsupported precision can obscure rather than clarify the decision.
Common mistakes that weaken a release decision
- Reviewing only the model weights: documentation, examples, metadata, and the dataset can change what the package reveals.
- Equating no wet-lab work with no biosecurity concern: WHO includes information and emerging technologies in biosecurity management.
- Treating openness as an automatic benefit: collaboration and scrutiny matter, but broad availability can also spread sensitive capability.
- Using one binary gate: screening, escalation, mitigation, and a choice among several release paths are more informative than a simple publish-or-stop rule.
- Borrowing a framework outside its scope: NTI’s funder guidance does not cover every AI-biology case, especially AI-enabled design, synthesis, or optimization linked to physical biological outputs.
- Ignoring residual uncertainty: a lack of evidence is not evidence that a release is harmless; record what remains unknown and who accepted that uncertainty.
- Failing to revisit approval: a new model version, added documentation, changed audience, or changed access method can alter the assessment.
When should an approved release be reassessed?
Reassess when the material or the context materially changes, and do not treat the initial decision as permanent. UK frontier-AI safety guidance recommends lifecycle assessment and continual monitoring; WHO’s 2024 guidance places biosecurity in a lifecycle approach across handling of high-consequence biological material, technology, and information.
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Who should review the decision, and what rules apply?
Involve your institution’s biosafety and biosecurity committee or designated officers, qualified subject-matter experts, and legal or regulatory advisers as appropriate to the work and jurisdiction. The WHO guidance directs readers to national and international legislation and regulatory oversight; requirements vary by location, institution, research context, and materials.
Research leaders and funders should ensure that reviewers have enough information to evaluate the actual release package, not merely a project abstract. Developers should explain model and dataset changes in terms that nontechnical biosafety reviewers can assess, while domain experts should clarify biological context without adding unnecessary sensitive detail to broadly circulated records. Assign one person or body authority to approve, condition, defer, or reject the release, and make that authority explicit.
NTI’s 2025 framework is intended as practical decision support for research funding review, not as a comprehensive release framework for every AI-biology case. In particular, its stated exclusion for AI-enabled design, synthesis, or optimization that could lead to physical biological outputs means those proposals require additional applicable expertise and review. Do not use that framework’s screening steps as a substitute for the institutional and regulatory processes relevant to such work.
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The UK government’s Emerging processes for frontier AI safety says, “Risk assessments are valuable, as they can lead to responsible decisions – including decisions made deliberately in advance of capability advancements – and ultimately mitigate risk.” That principle is useful here: make release decisions before a change creates pressure to share, and preserve a clear record of the rationale and limits. WHO likewise directs organizations to work within national and international oversight rather than relying on an informal internal judgment alone.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How can a team make the process proportionate?
Proportionality does not mean skipping review for a small file or a familiar collaboration. It means matching the depth of analysis and controls to the plausible consequences, uncertainty, audience, and exposure created by the package. A low-concern proposal may need a concise documented screen and named approval. A proposal with unresolved high-consequence possibilities, broad public access, or difficult-to-reverse disclosure warrants deeper expert review, comparison of narrower paths, and explicit residual-risk acceptance.
Keep the record understandable to future reviewers. Define technical terms, link each conclusion to the component or access condition it concerns, and separate facts from assumptions. If the team cannot explain why the expected benefit requires the proposed level of access, that is a reason to reconsider the release design, not a reason to add unsupported assurances.
Frequently Asked Questions
Is biosecurity the same as biosafety in AI life-sciences research?
No. WHO’s 2024 laboratory biosecurity guidance focuses on preventing deliberate misuse involving biological material, technology, and information; biosafety addresses accidental exposure or release. A project can need consideration of both, depending on its context.
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Does NTI’s 2025 framework cover every AI-for-biology release?
No. NTI states that its funder-oriented framework excludes AI-enabled biological design, synthesis, or optimization that could lead to physical biological outputs. Those cases need additional applicable expertise and review.
Is there a universal risk score that tells me whether a model is safe to publish?
The cited WHO, OECD, UK, and NTI guidance does not establish a globally applicable release score or threshold. Applicable requirements and oversight vary by jurisdiction, institution, research context, and materials.
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What if reviewers disagree about whether a release is acceptable?
The guidance supports escalation and proportionate review rather than assuming a single automatic answer. Record the unresolved uncertainty and decision ownership, consult the appropriate institutional officers and advisers, and consider a narrower or delayed release while the issue is assessed.
Should a public paper and its code or data receive the same decision?
Not necessarily. Assess the paper, code, model, dataset, documentation, and access method as one package, then decide whether different components need different audiences, detail levels, or release timing. The combination may reveal more than any single item.
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Are controlled-access safeguards a guarantee against misuse?
No. Selection, agreements, monitoring, and traceability can reduce exposure, but they have practical limits and may not prevent misuse or onward disclosure. Record those limits and the residual uncertainty accepted by the decision owner.
What changes should trigger a new review?
Reassess after material changes to the model, dataset, documentation, audience, access method, or relevant context, and when new information changes earlier assumptions. Lifecycle monitoring should be planned when the original decision is made.
Who has final responsibility for approving release?
Name a decision owner or authorized institutional body, and document the reviewers consulted. Biosafety or biosecurity officers, subject-matter experts, and legal or regulatory advisers should be involved as appropriate; responsibility and requirements vary by institution and jurisdiction.
The Bottom Line
Assess the model, dataset, documentation, and access arrangement as one information package. Screen first, escalate uncertain or potentially high-consequence cases, compare public, controlled, staged, partial, and no-release options, and record benefits, safeguards, limits, residual uncertainty, decision ownership, and review triggers. Reassess when the material or context changes, and use institutional and regulatory oversight for decisions that exceed a general screening framework.
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