{"title":"应对人工智能对司法机构的风险:欧盟《人工智能法》下的问责框架","authors":"Irina Carnat","doi":"10.1016/j.clsr.2024.106067","DOIUrl":null,"url":null,"abstract":"<div><div>The rapid advancements in natural language processing, particularly the development of generative large language models (LLMs), have renewed interest in using artificial intelligence (AI) for judicial decision-making. While these technological breakthroughs present new possibilities for legal automation, they also raise concerns about over-reliance and automation bias. Drawing insights from the COMPAS case, this paper examines the implications of deploying generative LLMs in the judicial domain. It identifies the persistent factors that contributed to an accountability gap when AI systems were previously used for judicial decision-making. To address these risks, the paper analyses the relevant provisions of the EU Artificial Intelligence Act, outlining a comprehensive accountability framework based on the regulation's risk-based approach. The paper concludes that the successful integration of generative LLMs in judicial decision-making requires a holistic approach addressing cognitive biases. By emphasising shared responsibility and the imperative of AI literacy across the AI value chain, the regulatory framework can help mitigate the risks of automation bias and preserve the rule of law.</div></div>","PeriodicalId":51516,"journal":{"name":"Computer Law & Security Review","volume":"55 ","pages":"Article 106067"},"PeriodicalIF":3.3000,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Addressing the risks of generative AI for the judiciary: The accountability framework(s) under the EU AI Act\",\"authors\":\"Irina Carnat\",\"doi\":\"10.1016/j.clsr.2024.106067\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The rapid advancements in natural language processing, particularly the development of generative large language models (LLMs), have renewed interest in using artificial intelligence (AI) for judicial decision-making. While these technological breakthroughs present new possibilities for legal automation, they also raise concerns about over-reliance and automation bias. Drawing insights from the COMPAS case, this paper examines the implications of deploying generative LLMs in the judicial domain. It identifies the persistent factors that contributed to an accountability gap when AI systems were previously used for judicial decision-making. To address these risks, the paper analyses the relevant provisions of the EU Artificial Intelligence Act, outlining a comprehensive accountability framework based on the regulation's risk-based approach. The paper concludes that the successful integration of generative LLMs in judicial decision-making requires a holistic approach addressing cognitive biases. By emphasising shared responsibility and the imperative of AI literacy across the AI value chain, the regulatory framework can help mitigate the risks of automation bias and preserve the rule of law.</div></div>\",\"PeriodicalId\":51516,\"journal\":{\"name\":\"Computer Law & Security Review\",\"volume\":\"55 \",\"pages\":\"Article 106067\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2024-10-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Law & Security Review\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S026736492400133X\",\"RegionNum\":3,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"LAW\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Law & Security Review","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S026736492400133X","RegionNum":3,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"LAW","Score":null,"Total":0}
Addressing the risks of generative AI for the judiciary: The accountability framework(s) under the EU AI Act
The rapid advancements in natural language processing, particularly the development of generative large language models (LLMs), have renewed interest in using artificial intelligence (AI) for judicial decision-making. While these technological breakthroughs present new possibilities for legal automation, they also raise concerns about over-reliance and automation bias. Drawing insights from the COMPAS case, this paper examines the implications of deploying generative LLMs in the judicial domain. It identifies the persistent factors that contributed to an accountability gap when AI systems were previously used for judicial decision-making. To address these risks, the paper analyses the relevant provisions of the EU Artificial Intelligence Act, outlining a comprehensive accountability framework based on the regulation's risk-based approach. The paper concludes that the successful integration of generative LLMs in judicial decision-making requires a holistic approach addressing cognitive biases. By emphasising shared responsibility and the imperative of AI literacy across the AI value chain, the regulatory framework can help mitigate the risks of automation bias and preserve the rule of law.
期刊介绍:
CLSR publishes refereed academic and practitioner papers on topics such as Web 2.0, IT security, Identity management, ID cards, RFID, interference with privacy, Internet law, telecoms regulation, online broadcasting, intellectual property, software law, e-commerce, outsourcing, data protection, EU policy, freedom of information, computer security and many other topics. In addition it provides a regular update on European Union developments, national news from more than 20 jurisdictions in both Europe and the Pacific Rim. It is looking for papers within the subject area that display good quality legal analysis and new lines of legal thought or policy development that go beyond mere description of the subject area, however accurate that may be.