09637214221091823.pdf (188.26 kB)
Download fileArtificial Intelligence and the future of work: A functional-identity perspective
journal contribution
posted on 2022-07-05, 12:32 authored by Eva SelenkoEva Selenko, Sarah Bankins, Mindy Shoss, Joel Warburton, Simon Lloyd D RestubogThe 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 ScienceVolume
31Issue
3Pages
272 - 279Publisher
SAGE PublicationsVersion
- 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
2022-03-02Publication date
2022-06-10Copyright date
2022ISSN
0963-7214eISSN
1467-8721Publisher version
Language
- en