Professions and Expertise: How Machine Learning and Blockchain Are Redesigning the Landscape of Professional Knowledge and Organization

Authors

John Flood, Griffith University
Lachlan Robb, Griffith University

Abstract

Machine learning has entered the world of the professions with differential impacts. Automation will have huge impacts on the nature of work and society. Engineering, architecture, and medicine are early and enthusiastic adopters of automation. Other professions, especially law, are late and, in some cases, reluctant adopters. This Article examines the effects of artificial intelligence (“AI”) and Blockchain on professions and their knowledge bases. We start by examining the nature of expertise in general and the function of expertise in law. Using examples from law, such as Gulati and Scott’s analysis of how lawyers create (or don’t create) legal agreements, we show that even non-routine and complex legal work is potentially susceptible to automation. However, professions are different from other occupational groups because they include both indeterminate and technical elements that make pure automation difficult to achieve. We consider the future prospects of AI and Blockchain on professions and hypothesize that as the technologies mature, they will incorporate more human work through neural networks and Blockchain applications, such as the distributed autonomous organization (“DAO”). We argue that in the law and the legal profession, the role of lawyer as trusted advisor will again emerge as the central point of value.

Recommended Citation

John Flood and Lachlan Robb, Professions and Expertise: How Machine Learning and Blockchain Are Redesigning the Landscape of Professional Knowledge and Organization, 73 U. Mia. L. Rev. 443 (2019)
Available at: https://repository.law.miami.edu/umlr/vol73/iss2/6