Automated journalism: The effects of AI authorship and evaluative information on the perception of a science journalism article. (January 2023) - Lermann Henestrosa, Angelica; Greving, Hannah; Kimmerle, Joachim
Abstract: Texts produced by artificial intelligence (AI) are becoming increasingly prevalent in digital journalism. Research suggests that these texts do not differ from human-written texts in their perceived credibility or trustworthiness where simple and short text types are concerned. However, it is unclear how AI-written texts beyond simple fact reporting are perceived. Therefore, this research aimed to expand upon the existing literature on automated journalism by investigating the influence of AI authorship (vs. human authorship) and evaluative information presentation (vs. neutral information presentation). The results of three preregistered experimental studies revealed no differences in perceived credibility and trustworthiness between AI-written and human-written texts. However, presenting information in an evaluative way decreased the perception of credibility and trustworthiness. Moreover, the AI was perceived as less anthropomorphic than the human author. The belief in the machine heuristic was stronger for an AI than for a human author, particularly when participants had actually read an article allegedly written by an AI. A pooled analysis across the data of all three studies underpinned the main effect of information presentation. Concluding, we discuss the findings against the background of AI perception theory and suggest implications for future research. Highlights: AI authorship did not decrease credibility and trustworthiness perceptions of a text. A human author was perceived to be more anthropomorphic and intelligent than an AI author. Evaluative information presentation decreased credibility and trustworthiness ratings overall. The general belief in the machine heuristic was stronger when participants had read an article allegedly written by an AI.