{"title":"Deep Learning Meets Deep Democracy: Deliberative Governance and Responsible Innovation in Artificial Intelligence","authors":"Alexander Buhmann, Christian Fieseler","doi":"10.1017/beq.2021.42","DOIUrl":null,"url":null,"abstract":"Responsible innovation in artificial intelligence (AI) calls for public deliberation: well-informed “deep democratic” debate that involves actors from the public, private, and civil society sectors in joint efforts to critically address the goals and means of AI. Adopting such an approach constitutes a challenge, however, due to the opacity of AI and strong knowledge boundaries between experts and citizens. This undermines trust in AI and undercuts key conditions for deliberation. We approach this challenge as a problem of situating the knowledge of actors from the AI industry within a deliberative system. We develop a new framework of responsibilities for AI innovation as well as a deliberative governance approach for enacting these responsibilities. In elucidating this approach, we show how actors from the AI industry can most effectively engage with experts and nonexperts in different social venues to facilitate well-informed judgments on opaque AI systems and thus effectuate their democratic governance.","PeriodicalId":48031,"journal":{"name":"Business Ethics Quarterly","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2022-01-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Business Ethics Quarterly","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1017/beq.2021.42","RegionNum":2,"RegionCategory":"哲学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BUSINESS","Score":null,"Total":0}
引用次数: 17
Abstract
Responsible innovation in artificial intelligence (AI) calls for public deliberation: well-informed “deep democratic” debate that involves actors from the public, private, and civil society sectors in joint efforts to critically address the goals and means of AI. Adopting such an approach constitutes a challenge, however, due to the opacity of AI and strong knowledge boundaries between experts and citizens. This undermines trust in AI and undercuts key conditions for deliberation. We approach this challenge as a problem of situating the knowledge of actors from the AI industry within a deliberative system. We develop a new framework of responsibilities for AI innovation as well as a deliberative governance approach for enacting these responsibilities. In elucidating this approach, we show how actors from the AI industry can most effectively engage with experts and nonexperts in different social venues to facilitate well-informed judgments on opaque AI systems and thus effectuate their democratic governance.
期刊介绍:
Business Ethics Quarterly (BEQ) is a peer-reviewed scholarly journal that publishes theoretical and empirical research relevant to the ethics of business. Since 1991 this multidisciplinary journal has published articles and reviews on a broad range of topics, including the internal ethics of business organizations, the role of business organizations in larger social, political and cultural frameworks, and the ethical quality of market-based societies and market-based relationships. It recognizes that contributions to the better understanding of business ethics can come from any quarter and therefore publishes scholarship rooted in the humanities, social sciences, and professional fields.