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

Fiona Draxler, Anna Werner, Florian Lehmann, Matthias Hoppe, Albrecht Schmidt, Daniel Buschek, Robin Welsch

Research output: Contribution to journalArticleScientificpeer-review

10 Citations (Scopus)
73 Downloads (Pure)

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.
Original languageEnglish
Article number25
Pages (from-to)1-40
JournalACM Transactions on Computer-Human Interaction
Volume31
Issue number2
Early online date2023
DOIs
Publication statusPublished - 5 Feb 2024
MoE publication typeA1 Journal article-refereed

Keywords

  • Additional Key Words and Phrases Ownership
  • authorship
  • large language models
  • text generation

Fingerprint

Dive into the research topics of 'The AI Ghostwriter Effect: When Users Do Not Perceive Ownership of AI-Generated Text But Self-Declare as Authors'. Together they form a unique fingerprint.

Cite this