{"title":"Ethical governance of artificial intelligence: An integrated analytical framework","authors":"Lan Xue, Zhenjing Pang","doi":"10.1016/j.jdec.2022.08.003","DOIUrl":null,"url":null,"abstract":"<div><p>Emerging technologies have faced ethical challenges, and ethical governance has changed over time managing these technologies. The governance paradigm has gradually changed from scientific rationality to social rationality and ultimately to a higher ethical morality. The trend of seeking higher levels of ethics and morality provides a rich theoretical underpinning for the ethical governance of artificial intelligence (AI), which is a complex and comprehensive project that involves problem identification, path selection, and role configuration. Ethical problems in AI can also be identified in technology, value, innovation, and order systems. In the four major systems, the basic patterns of ethical problems can become uncontrolled risks, behavioral disorders, and ethical disorders. When considering the path selection, AI governance strategies such as ethical embedding, assessment, adaptation, and construction should be implemented within the technology life cycle at the stages of research and development, design and manufacturing, experimental promotion, and deployment and application, respectively. Looking at role configuration, multiple actors should assume different roles, including providing ethical factual information, expertise, and analysis, as well as expressing ethical emotions or providing ethical regulation tools under different governance strategies. This study provides a comprehensive discussion regarding the practical applicability of AI ethical governance using the case of autonomous vehicles.</p></div>","PeriodicalId":100773,"journal":{"name":"Journal of Digital Economy","volume":"1 1","pages":"Pages 44-52"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2773067022000048/pdfft?md5=ca8e18be776a96c3a676a05bad810ab3&pid=1-s2.0-S2773067022000048-main.pdf","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Digital Economy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2773067022000048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Emerging technologies have faced ethical challenges, and ethical governance has changed over time managing these technologies. The governance paradigm has gradually changed from scientific rationality to social rationality and ultimately to a higher ethical morality. The trend of seeking higher levels of ethics and morality provides a rich theoretical underpinning for the ethical governance of artificial intelligence (AI), which is a complex and comprehensive project that involves problem identification, path selection, and role configuration. Ethical problems in AI can also be identified in technology, value, innovation, and order systems. In the four major systems, the basic patterns of ethical problems can become uncontrolled risks, behavioral disorders, and ethical disorders. When considering the path selection, AI governance strategies such as ethical embedding, assessment, adaptation, and construction should be implemented within the technology life cycle at the stages of research and development, design and manufacturing, experimental promotion, and deployment and application, respectively. Looking at role configuration, multiple actors should assume different roles, including providing ethical factual information, expertise, and analysis, as well as expressing ethical emotions or providing ethical regulation tools under different governance strategies. This study provides a comprehensive discussion regarding the practical applicability of AI ethical governance using the case of autonomous vehicles.