People are skeptical of headlines labeled as AI-generated, even if true or human-made, because they assume full AI automation

The rise of generative AI tools has sparked debates about the labeling of AI-generated content. Yet, the impact of such labels remains uncertain. In two preregistered online experiments among US and UK participants (N = 4,976), we show that while participants did not equate “AI-generated” with “False,” labeling headlines as AI-generated lowered their perceived accuracy and participants’ willingness to share them, regardless of whether the headlines were true or false, and created by humans or AI. The impact of labeling headlines as AI-generated was three times smaller than labeling them as false. This AI aversion is due to expectations that headlines labeled as AI-generated have been entirely written by AI with no human supervision. These findings suggest that the labeling of AI-generated content should be approached cautiously to avoid unintended negative effects on harmless or even beneficial AI-generated content and that effective deployment of labels requires transparency regarding their meaning.

Publication Details

Journal
Zurich Open Repository and Archive (University of Zurich)
Published
2024-10-01
DOI
https://doi.org/10.5167/uzh-265738
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

People are skeptical of headlines labeled as AI-generated, even if true or human-made, because they assume full AI automation

Zurich Open Repository and Archive (University of Zurich)
Ethics and Social Impacts of AI
article

People are skeptical of headlines labeled as AI-generated, even if true or human-made, because they assume full AI automation

article en

Abstract

The rise of generative AI tools has sparked debates about the labeling of AI-generated content. Yet, the impact of such labels remains uncertain. In two preregistered online experiments among US and UK participants (N = 4,976), we show that while participants did not equate “AI-generated” with “False,” labeling headlines as AI-generated lowered their perceived accuracy and participants’ willingness to share them, regardless of whether the headlines were true or false, and created by humans or AI. The impact of labeling headlines as AI-generated was three times smaller than labeling them as false. This AI aversion is due to expectations that headlines labeled as AI-generated have been entirely written by AI with no human supervision. These findings suggest that the labeling of AI-generated content should be approached cautiously to avoid unintended negative effects on harmless or even beneficial AI-generated content and that effective deployment of labels requires transparency regarding their meaning.

Zurich Open Repository and Archive (University of Zurich)
Openalex Percentile: Top 50%
Ethics and Social Impacts of AI
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