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Generative AI and Perceptual Harms: Who's Suspected of using LLMs?

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arxiv 2410.00906 v3 pith:OVUYPTIV submitted 2024-10-01 cs.HC

classification cs.HC
keywords harmsperceptualtheywritinggroupsharmllmsparticipants
verification ladder T0 review T1 audit T2 compute T3 formal
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Large language models (LLMs) are increasingly integrated into a variety of writing tasks. While these tools can help people by generating ideas or producing higher quality work, like many other AI tools they may risk causing a variety of harms, disproportionately burdening historically marginalized groups. In this work, we introduce and evaluate perceptual harm, a term for the harm caused to users when others perceive or suspect them of using AI. We examined perceptual harms in three online experiments, each of which entailed human participants evaluating the profiles for fictional freelance writers. We asked participants whether they suspected the freelancers of using AI, the quality of their writing, and whether they should be hired. We found some support for perceptual harms against for certain demographic groups, but that perceptions of AI use negatively impacted writing evaluations and hiring outcomes across the board.

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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. Penalizing Transparency? How AI Disclosure and Author Demographics Shape Human and AI Judgments About Writing

    cs.CY 2025-07 conditional novelty 6.0 of 10

    AI disclosure lowers perceived article quality for both human and LLM raters, and only LLM raters show a demographic preference that disappears when AI assistance is disclosed.

  2. The Widespread Adoption of Large Language Model-Assisted Writing Across Society

    cs.CL 2025-02 conditional novelty 6.0 of 10

    LLM-assisted writing rose sharply after ChatGPT's launch and plateaued by 2024, reaching estimated shares of roughly 18% in consumer complaints, 24% in corporate press releases, 14% in UN releases, and up to 15% in sm...

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