Certain biological AI models demand oversight, argue public health and legal professionals from Stanford and John Hopkins University.
hatbots are not the only AI models to have advanced in recent years. Specialized models trained on biological data have similarly leapt forward, and could help to accelerate vaccine development, cure diseases, and engineer drought-resistant crops. But the same qualities that make these models beneficial introduce potential dangers. For a model to be able to design a vaccine that is safe, for instance, it must first know what is harmful.
“We need to plan now,” says Anita Cicero, deputy director at the John Hopkins Center for Health Security and a co-author of the paper. “Some structured government oversight and requirements will be necessary in order to reduce risks of especially powerful tools in the future."over enemy walls, potentially contributing to the spread of the Black Death in Europe.
, and while there are some measures to prevent the purchase of dangerous genetic sequences, they are applied unevenly both within the U.S. and abroad, making them easy to circumvent. “There’s a lot of little holes in the dam, with water spurting out,” Cicero explains. She and her co-authors encourage mandatory screening requirements, but note even these are insufficient to fully guard against the risks of biological AI models.
Cicero explains “there needs to be some kind of floor. At the very minimum, the risk-benefit evaluations and the pre-release reviews of biological design tools and highly capable large language models would include an evaluation of whether those models could lead to pandemic- level risks, in addition to other things.”
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