Sana Zakaria, Timothy Marler, Mark Cabling, Suzanne Genc, Artur Honich, Mann Virdee, Sam Stockwell
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Consideration of technology advancements and policies in different geographic regions, and involvement of multiple organisations further confound this complexity. As the impact of ML and GE expands, forward looking policy is needed to mitigate risks and leverage opportunities. Thus, this study explores the technological and policy implications of the intersection of ML and GE, with a focus on the United States (US), the United Kingdom (UK), China, and the European Union (EU). Analysis of technical and policy developments over time and an assessment of their current state have informed policy recommendations that can help manage beneficial use of technology advancements and their convergence, which can be applied to other sectors. This study is intended for policymakers to prompt reflection on how to best approach the convergence of the two technologies. 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引用次数: 0
摘要
人工智能(AI)与生物技术的融合虽然处于起步阶段,但也带来了巨大的机遇和风险,因此需要制定积极的政策来管理这些新兴技术。虽然人工智能将继续产生重大而广泛的影响,但当它与其他新兴技术相结合时,其相关性和复杂性将进一步放大。机器学习(ML)是人工智能的一个子集,它与基因编辑(GE)的结合尤其能带来巨大的利益,同时也会带来从伦理道德到国家安全的巨大风险。这些复杂的技术对农业、医药、经济竞争和国家安全等多个领域都有影响。考虑到不同地理区域的技术进步和政策,以及多个组织的参与,进一步加剧了这种复杂性。随着 ML 和 GE 影响的扩大,需要制定前瞻性政策来降低风险和利用机遇。因此,本研究以美国(US)、英国(UK)、中国和欧盟(EU)为重点,探讨了 ML 和 GE 交叉领域的技术和政策影响。随着时间的推移,对技术和政策发展的分析以及对其现状的评估为政策建议提供了依据,这些建议有助于管理技术进步及其融合的有益利用,并可应用于其他部门。本研究报告旨在帮助政策制定者思考如何以最佳方式实现两种技术的融合。技术从业人员可能也会发现,本研究作为一种资源,对于考虑利益相关者参与的信息和政策类型很有价值。
Machine Learning and Gene Editing at the Helm of a Societal Evolution.
The integration of artificial intelligence (AI) and biotechnology, whilst in its infancy, presents significant opportunities and risks, and proactive policy is needed to manage these emerging technologies. Whilst AI continues to have significant and broad impact, its relevance and complexity magnify when integrated with other emerging technologies. The confluence of Machine Learning (ML), a subset of AI, with gene editing (GE) in particular can foster substantial benefits as well as daunting risks that range from ethics to national security. These complex technologies have implications for multiple sectors, ranging from agriculture and medicine to economic competition and national security. Consideration of technology advancements and policies in different geographic regions, and involvement of multiple organisations further confound this complexity. As the impact of ML and GE expands, forward looking policy is needed to mitigate risks and leverage opportunities. Thus, this study explores the technological and policy implications of the intersection of ML and GE, with a focus on the United States (US), the United Kingdom (UK), China, and the European Union (EU). Analysis of technical and policy developments over time and an assessment of their current state have informed policy recommendations that can help manage beneficial use of technology advancements and their convergence, which can be applied to other sectors. This study is intended for policymakers to prompt reflection on how to best approach the convergence of the two technologies. Technical practitioners may also find it valuable as a resource to consider the type of information and policy stakeholders engage with.