Our prevailing legal paradigm for digital interactions stems from an overly simplistic and antiquated view of the digital universe without considering the impact of an increasingly complex digital realm. This piece explores how we might more equitably rebuild these relationships.

As machines are increasingly used to replicate and supplement human decision-making, it is imperative to understand the consequences. This paper develops an analytical framework that seeks to understand the relationships between intentions and outcomes in human and machines.

In recent years, machine readability has become a popular topic in law and technology circles. This piece walks through the creation of X2RL and explores the possibilities that emanate from drafting rules as code in semantic languages, as opposed to syntactic languages.