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Users Favor LLM-Generated Content -- Until They Know It's AI

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arxiv 2503.16458 v1 pith:4VOPC2FQ submitted 2025-02-23 cs.HC cs.LGecon.GNq-fin.EC

classification cs.HCcs.LGecon.GNq-fin.EC
keywords contentparticipantsresponseai-generatedeithergeneratedhalfhuman
verification ladder T0 review T1 audit T2 compute T3 formal
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In this paper, we investigate how individuals evaluate human and large langue models generated responses to popular questions when the source of the content is either concealed or disclosed. Through a controlled field experiment, participants were presented with a set of questions, each accompanied by a response generated by either a human or an AI. In a randomized design, half of the participants were informed of the response's origin while the other half remained unaware. Our findings indicate that, overall, participants tend to prefer AI-generated responses. However, when the AI origin is revealed, this preference diminishes significantly, suggesting that evaluative judgments are influenced by the disclosure of the response's provenance rather than solely by its quality. These results underscore a bias against AI-generated content, highlighting the societal challenge of improving the perception of AI work in contexts where quality assessments should be paramount.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. From Forensics to Ecosystems: Rethinking Watermarks for Generative AI Oversight

    cs.CY 2026-08 conditional novelty 5.0 of 10

    Watermarks should be repurposed from forensic identification of individual AI outputs to ecosystem-level measurement of aggregate synthetic content saturation.

  2. Neither Valid nor Reliable? Investigating the Use of LLMs as Judges

    cs.CL 2025-08 conditional novelty 4.0 of 10

    An argument, grounded in social-science measurement theory, that LLM-as-judge adoption has outpaced validity and reliability testing, with an analysis of four underlying assumptions.

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