When AI Does the Work: Does Attribution Shape Meaning and Effort?

Milena Nikolova (), Viliana Milanova and Feicheng Wang ()
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Milena Nikolova: University of Groningen
Feicheng Wang: University of Groningen

No 18784, IZA Discussion Papers from IZA Network @ LISER

Abstract: This paper provides the first causal evidence that merely attributing identical creative work to AI rather than to a human affects how much meaning people derive from a task and how much effort they are willing to contribute. We conducted a preregistered survey experiment in nationally representative samples from the United States (N = 1,511) and the Netherlands (N = 2,117). Participants evaluated identical public health campaign slogans that were randomly attributed either to an AI system or to a human professional, allowing us to isolate the causal effect of AI attribution while holding the creative output constant. AI attribution reduced perceived task meaning modestly and made participants 13% less likely to contribute a slogan of their own, indicating lower voluntary effort. These findings suggest that AI can influence work not only by changing productivity but also by altering the perceived value of human contribution itself.

Keywords: Artificial intelligence (AI); meaning; effort; survey experiment (search for similar items in EconPapers)
JEL-codes: C91 I30 J01 O33 (search for similar items in EconPapers)
Date: 2026-07
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