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Do people trust humans more than ChatGPT?

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  • Buchanan, Joy
  • Hickman, William

Abstract

We explore whether people trust the accuracy of statements produced by large language models (LLMs) versus those written by humans. While LLMs have showcased impressive capabilities in generating text, concerns have been raised regarding the potential for misinformation, bias, or false responses. In this experiment, participants rate the accuracy of statements under different information conditions. Participants who are not explicitly informed of authorship tend to trust statements they believe are human-written more than those attributed to ChatGPT. However, when informed about authorship, participants show equal skepticism towards both human and AI writers. Informed participants are, overall, more likely to choose costly fact-checking. These outcomes suggest that trust in AI-generated content is context-dependent.

Suggested Citation

  • Buchanan, Joy & Hickman, William, 2024. "Do people trust humans more than ChatGPT?," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 112(C).
    • Handle: RePEc:eee:soceco:v:112:y:2024:i:c:s2214804324000776
    DOI: 10.1016/j.socec.2024.102239
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    References listed on IDEAS

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    More about this item

    Keywords

    Artificial intelligence; Machine learning; Trust; Belief; Experiments;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty

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