Granular Legal Norms: Big Data and the Personalization of Private Law
Forthcoming in Vanessa Mak, Eric Tjong Tjin Tai and Anna Berlee (eds), Research Handbook on Data Science and Law, Edward Elgar 2018
17 Pages Posted: 1 Jun 2018
Date Written: March 06, 2018
Against the background of the emerging debate about personalized law, this book chapter explores how Big Data and algorithm-based regulation could fundamentally change the design and structure of legal norms: impersonal law based on typifications could be replaced by a more personalized law, based on "granular legal norms".
We argue that the use of legal typifications which is a hallmark of impersonal law can be conceptualized as the answer to an information problem, a concession to the imperfections of a legal system administered by humans. The emergence of super-human capacities of information-processing through artificial intelligence could make it possible to personalize the law and achieve a level of "granularity" that has hitherto been unachieved. The chapter analyses the benefits of "granular legal norms" as well as possible limitations and objections, in particular privacy concerns and the principle of equality.
Keywords: Algorithms, Big Data, algorithmic regulation, personalized law, granular legal norms, personalization, typifications, privacy, private law
JEL Classification: K00, K10, K11, K12, K13
Suggested Citation: Suggested Citation