  As a result of rapidly accelerating AI capabilities, over the past year,
national governments and multinational bodies have announced efforts to address
safety, security and ethics issues related to AI models. One high priority
among these efforts is the mitigation of misuse of AI models. Many biologists
have for decades sought to reduce the risks of scientific research that could
lead, through accident or misuse, to high-consequence disease outbreaks.
Scientists have carefully considered what types of life sciences research have
the potential for both benefit and risk (dual-use), especially as scientific
advances have accelerated our ability to engineer organisms and create novel
variants of pathogens. Here we describe how previous experience and study by
scientists and policy professionals of dual-use capabilities in the life
sciences can inform risk evaluations of AI models with biological capabilities.
We argue that AI model evaluations should prioritize addressing
high-consequence risks (those that could cause large-scale harm to the public,
such as pandemics), and that these risks should be evaluated prior to model
deployment so as to allow potential biosafety and/or biosecurity measures.
Scientists' experience with identifying and mitigating dual-use biological
risks can help inform new approaches to evaluating biological AI models.
Identifying which AI capabilities post the greatest biosecurity and biosafety
concerns is necessary in order to establish targeted AI safety evaluation
methods, secure these tools against accident and misuse, and avoid impeding
immense potential benefits.
