Linking artificial intelligence job exposure to expectations: understanding AI losers, winners, and their political preferences

Green, Jane, Grant, Zack, Evans, Geoffrey and Inglese, Gaetano (2025) Linking artificial intelligence job exposure to expectations: understanding AI losers, winners, and their political preferences. Research and Politics, 12 (2). ISSN 2053-1680

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Abstract

The rapid expansion of Artificial Intelligence (AI) in the workplace has significant political implications. How can we understand perceptions of both personal job risks and opportunities, given each may affect political attitudes differently? We use an original, representative survey from Great Britain to reveal; (i) the degree to which people expect personal AI-based occupational risks versus opportunities, (ii) how much this perceived exposure corresponds to variation in existing expert-derived occupational AI-exposure measures; (iii) the social groups who expect to be AI winners and AI losers; and (iv) how personal AI expectations are associated with demand for different political policies. We find that over 1-in-3 British workers anticipate being an AI winner (10%) or loser (24%) and, while expectations correlate with classifications of occupational exposure, factors like education, gender, age, and employment sector also matter. Politically, both self-anticipated AI winners and losers show similar support for redistribution, but they differ on investment in education and training as well as on immigration. Our findings emphasise the importance of considering subjective winners and losers of AI; these patterns cannot be explained by existing occupational classifications of AI exposure.

Item Type:	Article
Additional Information:	© 2025 The Author(s)
Divisions:	Government
Subjects:	H Social Sciences > HD Industries. Land use. Labor T Technology > T Technology (General) H Social Sciences > HB Economic Theory
Date Deposited:	03 Jun 2025 08:18
Last Modified:	21 Jun 2025 19:09
URI:	http://eprints.lse.ac.uk/id/eprint/128289

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