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

Angelica Lermann Henestrosa, Joachim Kimmerle

2024Journalism and Media37 citationsDOIOpen Access PDF

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.

Topics & Concepts

PerceptionPsychologyInformation retrievalCognitive psychologyComputer scienceNeuroscienceArtificial Intelligence in Healthcare and EducationAI in Service InteractionsTopic Modeling