The AI Ghostwriter Effect: When Users do not Perceive Ownership of AI-Generated Text but Self-Declare as Authors

Abstract

Human-AI interaction in text production increases complexity in authorship. In two empirical studies (n1 = 30 & n2 = 96), we investigate authorship and ownership in human-AI collaboration for personalized language generation. We show an AI Ghostwriter Effect : Users do not consider themselves the owners and authors of AI-generated text but refrain from publicly declaring AI authorship. Personalization of AI-generated texts did not impact the AI Ghostwriter Effect , and higher levels of participants’ influence on texts increased their sense of ownership. Participants were more likely to attribute ownership to supposedly human ghostwriters than AI ghostwriters, resulting in a higher ownership-authorship discrepancy for human ghostwriters. Rationalizations for authorship in AI ghostwriters and human ghostwriters were similar. We discuss how our findings relate to psychological ownership and human-AI interaction to lay the foundations for adapting authorship frameworks and user interfaces in AI in text-generation tasks.

Placebo or Assistant? Generative AI Between Externalization and Anthropomorphization

“…The AI ghostwriter effect differs from the placebo effect and the Google effect in that, at least judging from the two studies reported by Draxler et al (2024), people appear to fully be aware of generative AIs being the main driver behind the text output. In contrast to a confusion regarding the source of "googled" information (Siler et al, 2022) and unconscious effects of technology-based augmentation on the judgment of one's own abilities (Villa et al, 2023), letting an AI generate a text seems to be an intentional and conscious action that is cognitively monitored and remembered.…”

“…Another finding related to the failure to correctly attribute AI-generated work consists in the "AI ghostwriter effect" described by Draxler et al (2024). In their studies, an intricate pattern of ownership and authorship of texts emerged.…”

“…Thus, humans still actively contribute to AI-generated content and may not wish to fully assign the credit of a work to an AI, perhaps even fearing that the acknowledgment of any AI assistance will let others believe that they did not contribute anything original to the work themselves. As a potential solution, Draxler et al (2024) suggested to provide the possibility for a more detailed contribution statement describing which tasks were completed by the AI. Furthermore, the aspects of ethics, authorship, copyright, and attribution are in a complex relationship centered around human content creation.…”

“…While external memory stores play a more passive role and simply deliver information on demand, generative AIs (as their name implies) feature a creative element that, until now, was considered uniquely human. These novel capabilities strongly resembling human creative efforts have raised the question of AI authorship (e.g., Draxler et al, 2024;Thorp, 2023) and the ethical use of AI-generated output (e.g., Eaton, 2023;Lund et al, 2023). Most importantly, an emerging field of research investigates the effects of generative AI use on cognition.…”

Generative Echo Chamber? Effect of LLM-Powered Search Systems on Diverse Information Seeking

“…Our study is particularly informed by works that are concerned with the negative effects of language models on people's information consumption and production. In the context of co-writing with LMs, common concerns include over-reliance on AI and automationinduced complacency [45] that can lead to not only sub-optimal writing outcomes [3] but also loss of human agency and perceived ownership of the created content [11]. While over-reliance on AI's suggestions has been studied as a common issue in human-AI interaction, LMs can exert additional informational influence by exposing people to, or making it easier to express, some views more often than others.…”