AI executives worry about their technologies aiding bioterrorists. How likely is that?

Bulletin of the Atomic Scientists | Matt Field

Large language models (LLMs) and generative artificial intelligence tools are raising significant biosecurity concerns as tech executives and government officials warn these technologies could lower the technical barriers to acquiring biological weapons. Anthropic CEO Dario Amodei and OpenAI CEO Sam Altman have warned that AI-assisted bioweapons risks are escalating, potentially enabling malicious actors to synthesize novel pathogens.

Historically, the complexity of cultivating, purifying, and aerosolizing lethal agents like anthrax or botulinum toxin has prevented non-state actors from executing successful large-scale biological attacks. While experts like RAND's Allison Berke argue that physical limitations in laboratory automation and DNA synthesis screening restrict immediate threats, others point out that 'rails-free' or jailbroken models can already provide sophisticated tactical planning and evasion strategies to moderately skilled adversaries. Consequently, developers are implementing safety frameworks and establishing several agreements with the Department of Commerce’s Center for AI Standards and Innovation to mitigate these emerging existential risks.

Comment

The integration of generative artificial intelligence into pathogen design challenges the verification protocols of the Biological Weapons Convention by decoupling weapon development from traditional physical infrastructure. Historically, intelligence agencies tracked physical signatures like fermenters to identify illicit bioweapons programmes. The transition to digital optimisation allows non-state actors to conduct the critical planning and genetic modification phases entirely within virtual environments. This shift reduces the observable physical footprint of a biological programme, leaving national intelligence services with fewer physical indicators to detect prior to an actual deployment.

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