TUESDAY, SEPTEMBER 8, 2026|No. 14252
Technology · Economics

Automation Can Undermine Job Satisfaction Even Without Displacement, Study Finds

A new NBER working paper explores how automation can diminish the perceived value of human contribution to work, impacting job satisfaction and potentially accelerating machine adoption.

A robotic arm works alongside human hands in a modern factory setting.
A robotic arm works alongside human hands in a modern factory setting. · Photo by Simon Kadula on Unsplash
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Replaceable but Employed: Automation and the Meaning of Work

Joshua S. Gans

Working Paper 35559

DOI 10.3386/w35559

Issue DateJuly 2026

Can automation harm workers without replacing them? We study jobs in which workers value both producing useful output and knowing that the output depends on their own contribution. A credible machine alternative can weaken that second source of meaning even when the firm retains the worker. Our model shows that this loss raises compensation when wages adjust fully; when they adjust only partly, workers bear some of the loss themselves. It can also make automation more likely. An external developer may profit by publicly demonstrating a machine before licensing it, because the demonstration lowers the value of the human alternative. This "meaning externality" can create demand for the machine and make profitable development socially harmful. Better technical quality and greater public salience have different effects: quality improves output, while salience alone weakens human work. Automation can, therefore, reduce the value of work before it eliminates jobs.

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  • Acknowledgements and Disclosures

Thanks to Refine.ink, ChatGPT 5.6 and Claude Fable 5 for valuable research assistance. Thanks to the SSHRC for funding. Responsibility for all errors remains my own. The views expressed herein are those of the author and do not necessarily reflect the views of the National Bureau of Economic Research.

Joshua S. Gans

Joshua Gans has drawn on the findings of his research for both compensated speaking engagements and consulting engagements. He has written the books Prediction Machines, Power & Prediction, and Innovation + Equality on the economics of AI for which he receives royalties. He is also chief economist of the Creative Destruction Lab, a University of Toronto-based program that helps seed stage companies, from which he receives compensation. He conducts consulting on anti-trust and intellectual property matters with an association with Keystone Strategy and his ownership of Core Economic Research Ltd. He also has equity and advisory relationships with a number of startup firms. Joshua is also a co-founder of All Day TA.

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Joshua S. Gans, "Replaceable but Employed: Automation and the Meaning of Work," NBER Working Paper 35559 (2026), https://doi.org/10.3386/w35559.

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