Nature took millions of years to design proteins. AI can generate meaningful protein sequences in seconds. While there are good reasons to develop AI technology for biological design, there are also risks to such efforts that scientists in the field don’t appear to have weighed. AI could be used to design new bioweapons or toxins that can’t be detected.
Ricin, for example, a toxin made from castor beans, was likely used by Bulgarian agents in London in 1978 in the well-documented umbrella-assassination of Georgi Markov, a Bulgarian dissident. Another example is the botulinum neurotoxin; it’s 100,000 times more toxic than the nerve agent sarin and has been a staple of state bioweapons arsenals. If the technology for developing and producing protein toxins improved, say by making it easier to design novel toxins or improving on existing ones, that could pose a high risk.
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One way to address potential misuse is to follow a simple code: stop, look, and listen. If you are developing a new generative AI technology or application, stop and consider the potential for dual-use. Look at what other scientists have done to address this in their software. And listen when other scientists warn you of the potential for your technology to be misused.
