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When seeing is not believing: self-efficacy and cynicism in the era of intelligent media

Author

Listed:
  • Qiang Liu

    (University of Shanghai for Science and Technology)

  • Lin Wang

    (University of Shanghai for Science and Technology)

  • Mengyu Luo

    (University of Shanghai for Science and Technology)

Abstract

The rise of deep synthesis technology has garnered significant attention with the advancement of artificial intelligence (AI). Social media platforms are increasingly populated with news content featuring AI-generated images. When browsing fragmented online information, it remains uncertain whether users pay attention to the source of this content. This study examines AI self-efficacy and user cynicism, exploring users’ cognitive and perceptual attitudes, as well as their behavioural tendencies toward news images generated by deepfake technology. The results of two experiments (N = 1826) suggest that when AI self-efficacy is lowered, users display greater cynicism toward the authenticity of news. Furthermore, differences in information processing strategies were observed depending on the content features of the news. Specifically, users with reduced AI self-efficacy were more likely to express cynicism toward high-relevance news compared to low-relevance news. Similarly, they were more likely to question the authenticity of low-risk news compared to high-risk news.

Suggested Citation

  • Qiang Liu & Lin Wang & Mengyu Luo, 2025. "When seeing is not believing: self-efficacy and cynicism in the era of intelligent media," Palgrave Communications, Palgrave Macmillan, vol. 12(1), pages 1-13, December.
    • Handle: RePEc:pal:palcom:v:12:y:2025:i:1:d:10.1057_s41599-025-04594-5
    DOI: 10.1057/s41599-025-04594-5
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    References listed on IDEAS

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    2. Ángel Vizoso & Martín Vaz-Álvarez & Xosé López-García, 2021. "Fighting Deepfakes: Media and Internet Giants’ Converging and Diverging Strategies Against Hi-Tech Misinformation," Media and Communication, Cogitatio Press, vol. 9(1), pages 291-300.
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