{"title":"The whack-a-mole governance challenge for AI-enabled synthetic biology: literature review and emerging frameworks","authors":"Trond Arne Undheim","doi":"arxiv-2402.00312","DOIUrl":null,"url":null,"abstract":"AI-enabled synthetic biology has tremendous potential but also significantly\nincreases biorisks and brings about a new set of dual use concerns. The picture\nis complicated given the vast innovations envisioned to emerge by combining\nemerging technologies, as AI-enabled synthetic biology potentially scales up\nbioengineering into industrial biomanufacturing. However, the literature review\nindicates that goals such as maintaining a reasonable scope for innovation, or\nmore ambitiously to foster a huge bioeconomy don't necessarily contrast with\nbiosafety, but need to go hand in hand. This paper presents a literature review\nof the issues and describes emerging frameworks for policy and practice that\ntransverse the options of command-and control, stewardship, bottom-up, and\nlaissez-faire governance. How to achieve early warning systems that enable\nprevention and mitigation of future AI-enabled biohazards from the lab, from\ndeliberate misuse, or from the public realm, will constantly need to evolve,\nand adaptive, interactive approaches should emerge. Although biorisk is subject\nto an established governance regime, and scientists generally adhere to\nbiosafety protocols, even experimental, but legitimate use by scientists could\nlead to unexpected developments. Recent advances in chatbots enabled by\ngenerative AI have revived fears that advanced biological insight can more\neasily get into the hands of malignant individuals or organizations. Given\nthese sets of issues, society needs to rethink how AI-enabled synthetic biology\nshould be governed. The suggested way to visualize the challenge at hand is\nwhack-a-mole governance, although the emerging solutions are perhaps not so\ndifferent either.","PeriodicalId":501219,"journal":{"name":"arXiv - QuanBio - Other Quantitative Biology","volume":"44 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - QuanBio - Other Quantitative Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2402.00312","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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.