Trajectories of legal work in the context of machine learning AI : conceptualising mediated evolution

Faulconbridge, James (2025) Trajectories of legal work in the context of machine learning AI : conceptualising mediated evolution. International Journal of the Legal Profession. ISSN 0969-5958 (In Press)

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Abstract

This paper explores the impacts of machine learning (ML), as one form of artificial intelligence, on legal work by examining three questions. First, it considers trajectories and how ML is being used in legal work. Actually existing use cases are examined to reveal how ML is changing legal work. Second, it considers questions about the barriers that are standing in the way of different trajectories, with the more rapid adoption of tried and tested forms of ML and some of the more radical changes that have been predicted being contingent on a range of factors. Third, this paper considers how evolution might change spaces of legal work and the legal profession. It examines both what ML might do to reconfigure the role of the lawyer within law firms and other spaces, and how lawyers might respond to this as the professional project adapts to the challenge of artificial intelligence. Through the analysis the paper develops the concept of mediated evolution which is a way of conceptualising change in legal work that is material and meaningful, but which is also path dependent and non-linear and thus needs to be understood through situated analysis of the enactment in practice of change