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

Abstract

Machine learning has entered the world of the professions with differential impacts. Engineering, architecture, and medicine are early and enthusiastic adopters. Other professions, especially law, are late and in some cases reluctant adopters. And in the wider society automation will have huge impacts on the nature of work and society. This paper examines the effects of artificial intelligence and blockchain on professions and their knowledge bases. We start by examining the nature of expertise in general and then how it functions 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 amenable to automation. However, professions are different because they include both indeterminate and technical elements that make pure automation difficult to achieve. We go on to consider the future prospects of AI and blockchain on professions and hypothesise that as the technologies mature they will incorporate more human work through neural networks and blockchain applications such as the DAO. For law, and the legal profession, the role of lawyer as trusted advisor will again emerge as the central point of value.