Accommodating machine learning algorithms in professional service firms

Faulconbridge, James R, Sarwar, Atif ORCID: 0000-0001-5411-0991 and Spring, Martin (2024) Accommodating machine learning algorithms in professional service firms. Organization Studies.

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Official URL: http://dx.doi.org/10.1177/01708406241252930

Abstract

<jats:p> Machine learning algorithms, as one form of artificial intelligence (AI), are significant for professional work because they create the possibility for some predictions, interpretations and judgements that inform decision making to be made by algorithms. However, little is known about whether it is possible to transform professional work to incorporate machine learning whilst also addressing negative responses from professionals whose work is changed by inscrutable algorithms. Through original empirical analysis of the effects of machine learning algorithms on the work of accountants and lawyers, this paper identifies the role of accommodating machine learning algorithms in professional service firms. Accommodating machine learning algorithms involves strategic responses that both justify adoption in the context of the possibilities and new contributions of machine learning algorithms and respond to the algorithms’ limitations and opaque and inscrutable nature. The analysis advances understanding of the processes that enable or inhibit the cooperative adoption of AI in PSFs and develops insights relevant when examining the long-term impacts of machine learning algorithms as they become ever more sophisticated. </jats:p>

Item Type:	Article
Uncontrolled Keywords:	Mental health
Divisions:	Faculty of Humanities and Social Sciences > School of Management
Depositing User:	Symplectic Admin
Date Deposited:	29 Apr 2024 15:24
Last Modified:	11 May 2024 05:58
DOI:	10.1177/01708406241252930
Related URLs:	Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3180624