Biological AI tools (BAITs) are AI models that are increasingly used to drive advances across biology, from predicting protein structures to designing new molecules. Many are openly released, but some developers choose to release only partial information about a tool's methodology, architecture, and data. This can be driven by a desire to protect commercial value, but also to limit misuse of dual-use tools, where the same capabilities that advance legitimate research can also be deployed in the pursuit of harmful outcomes.

AISI's Chem-Bio team conducts cutting-edge research to understand, evaluate, and mitigate chemical and biological risks associated with frontier AI systems. We assess the extent to which advanced models may enable harmful capabilities, develop methods for evaluating these risks rigorously, and share our findings directly with leading AI companies, UK officials and allied governments to inform deployment, research and policy decisions.

As frontier LLM-based AI agents become more capable at tasks such as research, coding, and scientific reasoning, we expect their ability to reproduce BAITs to improve. If a closed-source BAIT can be reverse-engineered from limited public information, then approaches to safeguard against its misuse may be undermined.