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The AI Ghostwriter Effect : When Users Do Not Perceive Ownership of AI-Generated Text But Self-Declare as Authors

Title data

Draxler, Fiona ; Werner, Anna ; Lehmann, Florian ; Hoppe, Matthias ; Schmidt, Albrecht ; Buschek, Daniel ; Welsch, Robin:
The AI Ghostwriter Effect : When Users Do Not Perceive Ownership of AI-Generated Text But Self-Declare as Authors.
In: ACM Transactions on Computer-Human Interaction. Vol. 31 (2024) Issue 2 . - 25.
ISSN 1557-7325
DOI: https://doi.org/10.1145/3637875

Official URL: Volltext

Project information

Project title:
Project's official title
Project's id
AI Tools - Continuous Interaction with Computational Intelligence Tools
No information

Abstract in another language

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.

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: text generation; large language models; authorship; ownership
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IX > Chair Applied Computer Science - Univ.-Prof. Dr. Daniel Buschek
Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IX
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
Date Deposited: 18 Jan 2024 09:54
Last Modified: 08 Feb 2024 13:03
URI: https://eref.uni-bayreuth.de/id/eprint/88273