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Artificial Intelligence and the future of work: A functional-identity perspective

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posted on 2022-07-05, 12:32 authored by Eva SelenkoEva Selenko, Sarah Bankins, Mindy Shoss, Joel Warburton, Simon Lloyd D Restubog
The impact of the implementation of artificial intelligence (AI) on workers’ experiences remains underexamined. Although AI-enhanced processes can benefit workers (e.g., by assisting with exhausting or dangerous tasks), they can also elicit psychological harm (e.g., by causing job loss or degrading work quality). Given AI’s uniqueness among other technologies, resulting from its expanding capabilities and capacity for autonomous learning, we propose a functional-identity framework to examine AI’s effects on people’s work-related self-understandings and the social environment at work. We argue that the conditions for AI to either enhance or threaten workers’ sense of identity derived from their work depends on how the technology is functionally deployed (by complementing tasks, replacing tasks, and/or generating new tasks) and how it affects the social fabric of work. Also, how AI is implemented and the broader social-validation context play a role. We conclude by outlining future research directions and potential application of the proposed framework to organizational practice.

History

School

  • Business and Economics

Department

  • Business

Published in

Current Directions in Psychological Science

Volume

31

Issue

3

Pages

272 - 279

Publisher

SAGE Publications

Version

  • VoR (Version of Record)

Rights holder

© The Author(s)

Publisher statement

This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access page (https://us.sagepub.com/en-us/nam/open-access-at-sage).

Acceptance date

2022-03-02

Publication date

2022-06-10

Copyright date

2022

ISSN

0963-7214

eISSN

1467-8721

Language

  • en

Depositor

Dr Eva Selenko. Deposit date: 29 June 2022

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