Replaceable but Employed: Automation and the Meaning of Work

Replaceable but Employed: Automation and the Meaning of Work 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. 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. 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 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. Citation and Citation Data Copy Citation Joshua S. Gans, "Replaceable but Employed: Automation and the Meaning of Work," NBER Working Paper 35559 (2026), https://doi.org/10.3386/w35559. Copy to Clipboard Download Citation MARC RIS BibTeΧ Download Citation Data MARC RIS BibTeΧ Download Citation Data Related Topics Programs More from the NBER In addition to working papers, the NBER disseminates affiliates’ latest findings through a range of free periodicals—the NBER Reporter, the NBER Digest, the Bulletin on Health, the Bulletin on the Economics of Alzheimer's, and the Bulletin on Entrepreneurship—as well as research spotlights, lectures, and panel videos. Feldstein Lecture Presenter: Mark Duggan Methods Lectures Presenters: Melissa Dell & Ashesh Rambachan Video Presenter: Paul Goldsmith-Pinkham