相关性(法律)
论证理论
计算机科学
对抗制
法学
审问
法治
人工智能
编码(集合论)
数据科学
政治学
认识论
政治
哲学
集合(抽象数据类型)
程序设计语言
标识
DOI:10.1098/rsta.2017.0355
摘要
In this brief contribution, I distinguish between code-driven and data-driven regulation as novel instantiations of legal regulation. Before moving deeper into data-driven regulation, I explain the difference between law and regulation, and the relevance of such a difference for the rule of law. I discuss artificial legal intelligence (ALI) as a means to enable quantified legal prediction and argumentation mining which are both based on machine learning. This raises the question of whether the implementation of such technologies should count as law or as regulation, and what this means for their further development. Finally, I propose the concept of ‘agonistic machine learning’ as a means to bring data-driven regulation under the rule of law. This entails obligating developers, lawyers and those subject to the decisions of ALI to re-introduce adversarial interrogation at the level of its computational architecture. This article is part of a discussion meeting issue ‘The growing ubiquity of algorithms in society: implications, impacts and innovations'.
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