FRONTIER RISKS: CAN AI HELP BUILD A BIOWEAPON?

Most of this series documents harms happening now. This report looks at the other end of the risk spectrum: the “dual-use” danger that the most capable AI models could meaningfully help a bad actor build a biological, chemical, or cyber weapon. It is not science fiction — the leading labs now run formal tests for exactly these capabilities, and they are starting to find early-warning signs.

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What red-teamers test

Before deploying a frontier model, developers such as Anthropic, OpenAI, and Google DeepMind run “dangerous capability” evaluations across a handful of priority domains: biological and chemical weapons, offensive cyber operations, AI’s ability to accelerate its own research, and behaviors linked to deception or loss of control. These red-team exercises probe whether a model will, with enough coaxing, provide genuinely useful help toward catastrophic harm — not just restate textbook facts.

The early-warning signs

The findings are no longer reassuring. Safety researchers report that frontier models are approaching, and in some cases exceeding, undergraduate-level competence in cybersecurity and expert-level knowledge in specific areas of biology. The concern is “uplift”: not whether a model knows dangerous information in the abstract, but whether it lowers the barrier for a motivated non-expert to actually cause harm. Controlled, human-subject studies — comparing what people can do with and without AI help — are the field’s main way of measuring that marginal risk.

“The concern is uplift: not whether a model knows dangerous information, but whether it lowers the barrier for a motivated non-expert to cause harm.”

How the labs respond

In response, major developers have published safety frameworks — variously called Responsible Scaling Policies, Preparedness Frameworks, or Frontier Safety Frameworks — that define capability thresholds and the safeguards (restricted release, added monitoring, or pausing development) that should trigger when a model crosses them. These are a genuine advance over having no plan. But approaches differ, the thresholds are set by the companies themselves, and enforcement is largely a matter of self-commitment.

The accountability gap

That is the crux. The Future of Life Institute’s 2025 AI Safety Index graded leading firms on existential-safety planning and found the field wanting — the strongest grade was around a C+, with several developers scoring D or below. With capabilities advancing faster than governance, independent evaluation, shared standards, and binding requirements remain the missing pieces. The throughline of this series scales up here too: the more powerful the AI, the more its safe use depends on humans deliberately keeping control — and on rules that don’t rely on goodwill alone.

Methodology & sources

• AI safety grading of major developers — Future of Life Institute, AI Safety Index (2025)
• Common elements of frontier safety policies; capability thresholds — METR (2025)
• Dangerous-capability & biorisk red-teaming — Anthropic Frontier Red Team