Lex Ex Machina: Reasons for Algorithmic Regulation

Abstract

A major unanswered question in regulation concerns the application of cognitive diversity and various data as inputs for the creation of general legal rules. The paper claims this diversity can be assured with the help of algorithmic planning. Classical regulation is hence put under question due to its inability to quickly adapt to changing conditions, where relations per se change also intentions, tools and goals. The paper proposes two paths towards a computational simulation of legal situations: with the help of algorithms that can ensure the needed adaptability and relevancy of hidden data correlations, and with collective intelligence based on human inputs where data for algorithms is not available. The aim of this work is to extend the pre-regulatory practice of extracting information from data with the help of algorithms to determine patterns and predict future results and trends (written now as general legal rules). Nowadays, algorithms could be used at least as advice, especially in a prepreparation, draft phase of legal acts.