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People devalue generative AI’s competence but not its advice in addressing societal and personal challenges
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References

  • 2003User Acceptance of Information Technology: Toward A Unified View144,945 cited
  • 2019Algorithm appreciation: People prefer algorithmic to human judgment2,045 cited
  • 2023Comparing scientific abstracts generated by ChatGPT to real abstracts with detectors and blinded human reviewers1,097 cited
  • 2006Advice taking and decision-making: An integrative literature review, and implications for the organizational sciences1,007 cited
  • 2019A systematic review of algorithm aversion in augmented decision making809 cited
  • 2021Algorithmic bias: review, synthesis, and future research directions767 cited
  • 2021What influences algorithmic decision-making? A systematic literature review on algorithm aversion597 cited
  • 2020Artificial intelligence versus Maya Angelou: Experimental evidence that people cannot differentiate AI-generated from human-written poetry401 cited
  • 2021Consumers Object to Algorithms Making Morally Relevant Tradeoffs Because of Algorithms’ Consequentialist Decision Strategies95 cited
  • 2022Preference for human, not algorithm aversion92 cited

Cited by

  • 2025Third-party evaluators perceive AI as more compassionate than expert humans129 cited
  • 2024The Role of AI Self-Efficacy in Religious Contexts in Public Sector: The Social Cognitive Theory Perspective29 cited
  • 2024Understanding and Perception of Automated Text Generation among the Public: Two Surveys with Representative Samples in Germany

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23 cited
  • 2024People have different expectations for their own versus others' use of AI‐mediated communication tools21 cited
  • 2024Understanding model power in social AI19 cited
  • 2024Evaluating science: A comparison of human and AI reviewers13 cited
  • 2025Can AI-generated news reduce hostile media perceptions? Findings from two experiments11 cited
  • 2026AI aversion? Effects of author disclosure on young people’s perceptions of mental health advice3 cited