The whack-a-mole governance challenge for AI-enabled synthetic biology: literature review and emerging frameworks

Trond Arne Undheim
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Abstract

AI-enabled synthetic biology has tremendous potential but also significantly increases biorisks and brings about a new set of dual use concerns. The picture is complicated given the vast innovations envisioned to emerge by combining emerging technologies, as AI-enabled synthetic biology potentially scales up bioengineering into industrial biomanufacturing. However, the literature review indicates that goals such as maintaining a reasonable scope for innovation, or more ambitiously to foster a huge bioeconomy don't necessarily contrast with biosafety, but need to go hand in hand. This paper presents a literature review of the issues and describes emerging frameworks for policy and practice that transverse the options of command-and control, stewardship, bottom-up, and laissez-faire governance. How to achieve early warning systems that enable prevention and mitigation of future AI-enabled biohazards from the lab, from deliberate misuse, or from the public realm, will constantly need to evolve, and adaptive, interactive approaches should emerge. Although biorisk is subject to an established governance regime, and scientists generally adhere to biosafety protocols, even experimental, but legitimate use by scientists could lead to unexpected developments. Recent advances in chatbots enabled by generative AI have revived fears that advanced biological insight can more easily get into the hands of malignant individuals or organizations. Given these sets of issues, society needs to rethink how AI-enabled synthetic biology should be governed. The suggested way to visualize the challenge at hand is whack-a-mole governance, although the emerging solutions are perhaps not so different either.
人工智能合成生物学的 "打地鼠 "治理挑战:文献综述和新兴框架
人工智能支持的合成生物学具有巨大潜力,但也大大增加了生物风险,并带来了一系列新的双重用途问题。由于人工智能支持的合成生物学有可能将生物工程扩展到工业生物制造领域,因此结合新兴技术有望出现巨大的创新,这使得情况变得复杂起来。然而,文献综述表明,保持合理的创新范围或更雄心勃勃地促进巨大的生物经济等目标并不一定与生物安全形成鲜明对比,而是需要齐头并进。本文对这些问题进行了文献综述,并介绍了新出现的政策和实践框架,这些框架跨越了命令与控制、管理、自下而上和自由放任治理等选项。如何实现早期预警系统,以预防和减轻未来来自实验室、故意滥用或公共领域的人工智能生物危害,将需要不断发展,并应出现适应性、互动性的方法。尽管生物风险受到既定治理制度的约束,科学家也普遍遵守生物安全协议,但即使是科学家的实验性合法使用也可能导致意想不到的发展。最近,由人工智能生成的聊天机器人的进步让人们再次担心,先进的生物洞察力会更容易落入恶意个人或组织之手。鉴于这些问题,社会需要重新思考如何管理人工智能支持的合成生物学。将当前挑战形象化的建议方法是 "打地鼠 "式治理,尽管新出现的解决方案可能也没有什么不同。
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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