2023/09/05 by Martin Huschens, Huschens, Martin, Martin Briesch +5 · 2 voices · 24 citations
Computer Science · Mathematics · Medicine · Psychology · Social Sciences · #Artificial Intelligence in Healthcare and Education #Competence (human resources) #Computer science #Content (measure theory) #Credibility #Epistemology #Explainable Artificial Intelligence (XAI) #Internet privacy #Mathematics #Medicine #Misinformation and Its Impacts #Perception #Presentation (obstetrics) #Psychology #Social psychology #Source credibility #Trustworthiness #World Wide Web
paper · pdf · doi:10.48550/arxiv.2309.02524
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2023/09/05 · openalex created_date 2023/09/09 · openalex updated_date 2026/07/30
This paper examines how individuals perceive the credibility of content originating from human authors versus content generated by large language models, like the GPT language model family that powers ChatGPT, in different user interface versions. Surprisingly, our results demonstrate that regardless of the user interface presentation, participants tend to attribute similar levels of credibility. While participants also do not report any different perceptions of competence and trustworthiness between human and AI-generated content, they rate AI-generated content as being clearer and more engaging. The findings from this study serve as a call for a more discerning approach to evaluating information sources, encouraging users to exercise caution and critical thinking when engaging with content generated by AI systems.