Does AI Cheapen Talk? Theory and Evidence From Global Entrepreneurship and Hiring

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Authors: Bo Cowgill, Pablo Hernández‐Lagos, Nataliya Langburd Wright
Cited by: 1

Abstract

Screening human capital based on signals such as job applications or entrepreneurial pitches is crucial for organizations. Signals are often informative insofar as they require differential knowledge and effort to produce. Generative AI (GAI) complicates screening by lowering the cost of producing impressive signals. We model the informational effects of GAI, showing that applicants' access to GAI can increase - but also decrease - an evaluator's screening mistakes. This result depends on how GAI affects experts' signals compared to non-experts'. Using experiments in hiring and startup investing, we estimate that senders' access to GAI (ChatGPT) lowers screening accuracy by 4-9% for employers and startup investors. Consistent with our model, senders' access to GAI also improves screening accuracy in some settings - in our case, among senders from non-English-speaking countries. These results show that GAI can profoundly shape screening accuracy.

Publication details

Journal / source
CESifo
Publication date
24 February 2026