A philosophy of technology for computational law
Mireille Hildebrandt · 2020
This chapter confronts the foundational challenges posed to legal theory and legal philosophy by the rise of computational ‘law’. Two types will be distinguished, noting that they can be combined into hybrid systems. On the one hand, the use of machine learning in the legal realm will be addressed under the heading of data-driven ‘law’. On the other hand, knowledge- or logic-based expert systems, self-executing contracts or regulation on a blockchain and Rules as Code will be addressed as code-driven ‘law’, which underlies much of automated decision-making. Data-driven ‘law’ raises problems due to its autonomic operations and the ensuing opacity of its reasoning. Code-driven ‘law’ presents us with a conflation of regulation, execution and adjudication. Though such implications are very different, both types of computational ‘law’ share the assumption that legal practice and legal research are computable. Before addressing the implications of these assumptions, the chapter will investigate the affordances of current, text-driven law, explaining how they relate to the core tenets of the Rule of Law and the kind of legal protection it offers. This will be followed by an enquiry into what computational law would afford in terms of legal protection, assuming that one of the core functions of law and the Rule of Law is to protect what is not computable.