{"title":"人工智能训练数据的法律框架——从第一原则到《人工智能法》","authors":"P. Hacker","doi":"10.1080/17579961.2021.1977219","DOIUrl":null,"url":null,"abstract":"ABSTRACT In response to recent regulatory initiatives at the EU level, this article shows that training data for AI do not only play a key role in the development of AI applications, but are currently only inadequately captured by EU law. In this, I focus on three central risks of AI training data: risks of data quality, discrimination and innovation. Existing EU law, with the new copyright exception for text and data mining, only addresses a part of this risk profile adequately. Therefore, the article develops the foundations for a discrimination-sensitive quality regime for data sets and AI training, which emancipates itself from the controversial question of the applicability of data protection law to AI training data. Furthermore, it spells out concrete guidelines for the re-use of personal data for AI training purposes under the GDPR. Ultimately, the legislative and interpretive task rests in striking an appropriate balance between individual protection and the promotion of innovation. The article finishes with an assessment of the proposal for an Artificial Intelligence Act in this respect.","PeriodicalId":37639,"journal":{"name":"Law, Innovation and Technology","volume":"13 1","pages":"257 - 301"},"PeriodicalIF":0.0000,"publicationDate":"2021-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"A legal framework for AI training data—from first principles to the Artificial Intelligence Act\",\"authors\":\"P. Hacker\",\"doi\":\"10.1080/17579961.2021.1977219\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT In response to recent regulatory initiatives at the EU level, this article shows that training data for AI do not only play a key role in the development of AI applications, but are currently only inadequately captured by EU law. In this, I focus on three central risks of AI training data: risks of data quality, discrimination and innovation. Existing EU law, with the new copyright exception for text and data mining, only addresses a part of this risk profile adequately. Therefore, the article develops the foundations for a discrimination-sensitive quality regime for data sets and AI training, which emancipates itself from the controversial question of the applicability of data protection law to AI training data. Furthermore, it spells out concrete guidelines for the re-use of personal data for AI training purposes under the GDPR. Ultimately, the legislative and interpretive task rests in striking an appropriate balance between individual protection and the promotion of innovation. The article finishes with an assessment of the proposal for an Artificial Intelligence Act in this respect.\",\"PeriodicalId\":37639,\"journal\":{\"name\":\"Law, Innovation and Technology\",\"volume\":\"13 1\",\"pages\":\"257 - 301\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Law, Innovation and Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/17579961.2021.1977219\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Law, Innovation and Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/17579961.2021.1977219","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
A legal framework for AI training data—from first principles to the Artificial Intelligence Act
ABSTRACT In response to recent regulatory initiatives at the EU level, this article shows that training data for AI do not only play a key role in the development of AI applications, but are currently only inadequately captured by EU law. In this, I focus on three central risks of AI training data: risks of data quality, discrimination and innovation. Existing EU law, with the new copyright exception for text and data mining, only addresses a part of this risk profile adequately. Therefore, the article develops the foundations for a discrimination-sensitive quality regime for data sets and AI training, which emancipates itself from the controversial question of the applicability of data protection law to AI training data. Furthermore, it spells out concrete guidelines for the re-use of personal data for AI training purposes under the GDPR. Ultimately, the legislative and interpretive task rests in striking an appropriate balance between individual protection and the promotion of innovation. The article finishes with an assessment of the proposal for an Artificial Intelligence Act in this respect.
期刊介绍:
Stem cell research, cloning, GMOs ... How do regulations affect such emerging technologies? What impact do new technologies have on law? And can we rely on technology itself as a regulatory tool? The meeting of law and technology is rapidly becoming an increasingly significant (and controversial) topic. Law, Innovation and Technology is, however, the only journal to engage fully with it, setting an innovative and distinctive agenda for lawyers, ethicists and policy makers. Spanning ICTs, biotechnologies, nanotechnologies, neurotechnologies, robotics and AI, it offers a unique forum for the highest level of reflection on this essential area.