AI-Generated News Content: The Impact of AI Writer Identity and Perceived AI Human-Likeness
Daniel Chaein Lee, Jihoon Jhang, Tae Hyun Baek
Abstract
As AI-generated news expands with advancing media technology, understanding its impact on consumer engagement becomes increasingly important. This study investigates how readers’ awareness of an article’s AI or human authorship affects their engagement with news content. The findings indicate that AI-generated news content results in lower liking behaviors compared to human-written content, with this effect mediated by the article’s perceived credibility rather than its perceived authenticity. Additionally, the mediating effect of news credibility is moderated by the perceived human-likeness of AI, with the negative impact being weaker when AI is perceived as more human-like. These findings extend the literature on human-computer interaction in journalism by highlighting the negative impact of AI use on consumer engagement, identifying perceived credibility as its underlying mechanism, and introducing a new paradigm focused on AI’s human-likeness. Practically, the findings suggest that careful management of AI authorship and its perceived human-likeness is essential.