The Effects of Assumed AI vs. Human Authorship on the Perception of a GPT-Generated Text

Author:

Lermann Henestrosa Angelica1ORCID,Kimmerle Joachim12ORCID

Affiliation:

1. Knowledge Construction Lab, Leibniz-Institut für Wissensmedien, 72076 Tübingen, Germany

2. Department of Psychology, Faculty of Science, Eberhard Karls University, 72076 Tübingen, Germany

Abstract

Artificial Intelligence (AI) has demonstrated its ability to undertake writing tasks, including automated journalism. Prior studies suggest no differences between human and AI authors regarding perceived message credibility. However, research on people’s perceptions of AI authorship on complex topics is lacking. In a between-groups experiment (N = 734), we examined the effect of labeled authorship on credibility perceptions of a GPT-written science journalism article. The results of an equivalence test showed that labeling a text as AI-written vs. human-written reduced perceived message credibility (d = 0.36). Moreover, AI authorship decreased perceived source credibility (d = 0.24), anthropomorphism (d = 0.67), and intelligence (d = 0.41). The findings are discussed against the backdrop of a growing availability of AI-generated content and a greater awareness of AI authorship.

Funder

Leibniz-Institut für Wissensmedien

Publisher

MDPI AG

Reference23 articles.

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3. Knowledge, Attitude, and Practices of General Population Toward Utilizing ChatGPT: A Cross-Sectional Study;Bodani;SAGE Open,2023

4. People Devalue Generative AI’s Competence but Not Its Advice in Addressing Societal and Personal Challenges;Reiter;Communications Psychology,2023

5. Brown, Tom, Mann, Benjamin, Ryder, Nick, Subbiah, Melanie, Kaplan, Jared, Dhariwal, Prafulla, Neelakantan, Arvind, Shyam, Pranav, Sastry, Girish, and Askell, Amanda (2020). Language Models Are Few-Shot Learners. arXiv.

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