{"title":"监管算法发挥作用:“欧洲人工智能方法”的教训","authors":"Jeremias Adams-Prassl","doi":"10.1177/20319525211062558","DOIUrl":null,"url":null,"abstract":"This article scrutinises the potential of the existing regulatory apparatus in Union law to tackle the social, technical, and legal challenges inherent in deploying automated systems in high-risk settings such as the workplace, with a view to setting out key lessons for the proposed EU Artificial Intelligence Act. Surveying data protection and discrimination rules as well as the social acquis, it highlights key areas for further development, from coherence between different regulatory regimes to the role of social partnership in shaping key standards and monitoring their implementation.","PeriodicalId":41157,"journal":{"name":"European Labour Law Journal","volume":"13 1","pages":"30 - 50"},"PeriodicalIF":1.9000,"publicationDate":"2022-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"Regulating algorithms at work: Lessons for a ‘European approach to artificial intelligence’\",\"authors\":\"Jeremias Adams-Prassl\",\"doi\":\"10.1177/20319525211062558\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article scrutinises the potential of the existing regulatory apparatus in Union law to tackle the social, technical, and legal challenges inherent in deploying automated systems in high-risk settings such as the workplace, with a view to setting out key lessons for the proposed EU Artificial Intelligence Act. Surveying data protection and discrimination rules as well as the social acquis, it highlights key areas for further development, from coherence between different regulatory regimes to the role of social partnership in shaping key standards and monitoring their implementation.\",\"PeriodicalId\":41157,\"journal\":{\"name\":\"European Labour Law Journal\",\"volume\":\"13 1\",\"pages\":\"30 - 50\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2022-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Labour Law Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1177/20319525211062558\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"LAW\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Labour Law Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/20319525211062558","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"LAW","Score":null,"Total":0}
Regulating algorithms at work: Lessons for a ‘European approach to artificial intelligence’
This article scrutinises the potential of the existing regulatory apparatus in Union law to tackle the social, technical, and legal challenges inherent in deploying automated systems in high-risk settings such as the workplace, with a view to setting out key lessons for the proposed EU Artificial Intelligence Act. Surveying data protection and discrimination rules as well as the social acquis, it highlights key areas for further development, from coherence between different regulatory regimes to the role of social partnership in shaping key standards and monitoring their implementation.