A call for built-in biosecurity safeguards for generative AI tools

IF 33.1 1区生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

Nature biotechnology Pub Date : 2025-04-28 DOI:10.1038/s41587-025-02650-8

Mengdi Wang, Zaixi Zhang, Amrit Singh Bedi, Alvaro Velasquez, Stephanie Guerra, Sheng Lin-Gibson, Le Cong, Yuanhao Qu, Souradip Chakraborty, Megan Blewett, Jian Ma, Eric Xing, George Church

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Abstract

Generative AI is changing biotechnology research, and accelerating drug discovery, protein design and synthetic biology. It also enhances biomedical imaging, personalized medicine and laboratory automation, which enables faster and more efficient scientific advancements. However, these breakthroughs have also raised biosecurity concerns, which has prompted policy and community discussions^1,2,3,4.

The power of generative AI lies in its ability to generalize from known data to the unknown. Deep generative models can predict novel biological molecules that might not resemble existing genome sequences or proteins. This capability introduces dual-use risks and serious biosecurity threats — such models could potentially bypass the established safety screening mechanisms used by nucleic acid synthesis providers⁵, which presently rely on database matching to identify sequences of concerns⁶. AI-driven tools could be misused to engineer pathogens, toxins or destabilizing biomolecules, and AI science agents could amplify risks by automating experimental designs⁷.

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呼吁为生成式人工智能工具提供内置生物安全保障

生成式人工智能正在改变生物技术研究，加速药物发现、蛋白质设计和合成生物学。它还增强了生物医学成像、个性化医疗和实验室自动化，从而实现更快、更有效的科学进步。然而，这些突破也引起了人们对生物安全的担忧，这引发了政策和社区的讨论1,2,3,4。生成式人工智能的强大之处在于它从已知数据推广到未知数据的能力。深度生成模型可以预测可能与现有基因组序列或蛋白质不相似的新生物分子。这种能力带来了双重用途风险和严重的生物安全威胁——这种模型可能潜在地绕过核酸合成供应商使用的既定安全筛选机制，这些机制目前依赖于数据库匹配来识别关注的序列。人工智能驱动的工具可能被滥用于设计病原体、毒素或破坏稳定的生物分子，人工智能科学代理可能会通过自动化实验设计来放大风险7。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Nature biotechnology 工程技术-生物工程与应用微生物

CiteScore

63.00

自引率

1.70%

发文量

382

审稿时长

3 months

期刊介绍： Nature Biotechnology is a monthly journal that focuses on the science and business of biotechnology. It covers a wide range of topics including technology/methodology advancements in the biological, biomedical, agricultural, and environmental sciences. The journal also explores the commercial, political, ethical, legal, and societal aspects of this research. The journal serves researchers by providing peer-reviewed research papers in the field of biotechnology. It also serves the business community by delivering news about research developments. This approach ensures that both the scientific and business communities are well-informed and able to stay up-to-date on the latest advancements and opportunities in the field. Some key areas of interest in which the journal actively seeks research papers include molecular engineering of nucleic acids and proteins, molecular therapy, large-scale biology, computational biology, regenerative medicine, imaging technology, analytical biotechnology, applied immunology, food and agricultural biotechnology, and environmental biotechnology. In summary, Nature Biotechnology is a comprehensive journal that covers both the scientific and business aspects of biotechnology. It strives to provide researchers with valuable research papers and news while also delivering important scientific advancements to the business community.