Which Contributions Deserve Credit? Perceptions of Attribution in Human-AI Co-Creation

要旨

AI systems powered by large language models can act as capable assistants for writing and editing. In these tasks, the AI system acts as a co-creative partner, making novel contributions to an artifact-under-creation alongside its human partner(s). One question that arises in these scenarios is the extent to which AI should be credited for its contributions. We examined knowledge workers' views of attribution through a survey study (N=155) and found that they assigned different levels of credit across different contribution types, amounts, and initiative. Compared to a human partner, we observed a consistent pattern in which AI was assigned less credit for equivalent contributions. Participants felt that disclosing AI involvement was important and used a variety of criteria to make attribution judgments, including the quality of contributions, personal values, and technology considerations. Our results motivate and inform new approaches for crediting AI contributions to co-created work.

著者
Jessica He
IBM Research, Yorktown Heights, New York, United States
Stephanie Houde
IBM Research, Cambridge, Massachusetts, United States
Justin D.. Weisz
IBM Research AI, Yorktown Heights, New York, United States
DOI

10.1145/3706598.3713522

論文URL

https://dl.acm.org/doi/10.1145/3706598.3713522

動画

会議: CHI 2025

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)

セッション: Human-Agent Interaction

Annex Hall F204
7 件の発表
2025-04-29 20:10:00
2025-04-29 21:40:00
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