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How will Generative AI impact Communication?

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  • Joshua S. Gans

Abstract

This paper examines the impact of Generative AI (GAI) on communication through the lens of salience and signalling models. It explores how GAI affects both senders' ability to create salient messages and receivers' costs of absorbing them. The analysis reveals that while GAI can increase communication by reducing costs, it may also disrupt traditional signalling mechanisms. In a salience model, GAI generally improves outcomes but can potentially reduce receiver welfare. In a pure signalling model, GAI may hinder effective communication by making it harder to distinguish high-quality messages. This suggests that GAI's introduction necessitates new instruments and mechanisms to facilitate effective communication and quality assessment in this evolving landscape.

Suggested Citation

  • Joshua S. Gans, 2024. "How will Generative AI impact Communication?," NBER Working Papers 32690, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:32690
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    Cited by:

    1. Anais Galdin & Jesse Silbert, 2025. "Making Talk Cheap: Generative AI and Labor Market Signaling," Papers 2511.08785, arXiv.org.
    2. Breisinger, Clemens & Karachiwalla, Naureen & Keenan, Michael & Kim, MinAh & Koo, Jawoo & Mwangi, Christine, 2024. "Man vs. machine: Experimental evidence on the quality and perceptions of AI-generated research content," IFPRI discussion papers 2321, International Food Policy Research Institute (IFPRI).

    More about this item

    JEL classification:

    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives

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