Generative AI and career choices
Christian Gschwendt, Martina Viarengo, Thea Zöllner · Graduate Institute Geneva Institutional Repository (Graduate Institute of International and Development Studies) · 1 Jun 2026
Where this sits in the debate
Direction of the finding as read from the abstract by an AI model (AI-written).
Key takeaway AI-written
A discrete-choice experiment with over 7,000 Swiss 15-year-olds on how they value working with generative AI in future jobs. Adolescents are on average averse to GenAI collaboration, girls more than boys, but accept moderate use when it does not raise automation risk, and continuing-education opportunities improve their attitudes.
Abstract
The economic impact of technological change will critically depend on how future workers invest in their human capital. Yet, little is known about how future workers themselves evaluate and choose their educational and occupational paths in light of emerging technologies. This paper examines how adolescents currently at the schoolto-work transition stage value working with generative artificial intelligence (GenAI) in their future occupations, and how automation risk and opportunities for continuing education shape these preferences. We field a discrete-choice experiment among a nationally representative sample of over 7,000 Swiss adolescents aged around 15. We find that adolescents generally exhibit an aversion to collaborating with GenAI at work, with females consistently more averse than males. However, preferences are nuanced: adolescents welcome greater GenAI collaboration, provided that GenAI usage levels remain moderate and that it is not accompanied by increases in jobautomation risk. Finally, continuing education opportunities in occupations improve attitudes towards working with GenAI across genders. Our results challenge simple narratives of technology acceptance or rejection, revealing that adolescents’ willingness to work with GenAI depends on how it is implemented — its intensity, associated displacement risks, and accompanying skill development — rather than the technology itself. Our findings suggest that the way future workers value GenAI collaboration in their career choices critically depends.
About this publication
Academic journal. Published in an academic journal — typically peer-reviewed before publication, though indexing alone doesn't guarantee review depth.
- Published
- 2026 (5 months ago)
- Citations
- 0 (OpenAlex)
0 citations recorded by OpenAlex — too few 2026 papers in this collection for a fair comparison.
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