A call for a quantitative report card for AI bioterrorism threat models
Scientists and policymakers have expressed a great deal of concern recently about biosecurity risks posed by frontier artificial intelligence systems, especially large language models like ChatGPT and Claude. Yet these models also promise to accelerate many areas of work, including biotechnology.
Fear of disease is visceral and the need for biosecurity well-founded, especially in the wake of the coronavirus pandemic. But our security strategies must avoid placing limitations on key advances such as mRNA vaccine research, epidemiological surveillance, and synthetic biology, or on more broadly applicable machine learning systems.
In this essay, I review the existing literature at the intersection of biological safety measures and frontier language models, including both qualitative and quantitative explorations of model capabilities. I discuss three AI-misuse threat models (technical, social engineering, and mis/disinformation), and argue that quantifying the technical threat model is the highest priority. Next, I outline existing metrics.
I propose the creation of a quantitative biotechnology and biosecurity report card for frontier language models. The goal of the report card is to provide transparency around the costs and benefits of including biological capabilities in these systems, and to push for accountability around security measures designed to protect the public in AI and in society broadly.