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

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arxiv 2502.18357 v1 pith:S5TDSLWY submitted 2025-02-25 cs.HC cs.AIcs.CY

classification cs.HCcs.AIcs.CY
keywords contributionsattributioncreditpartnerassigneddifferenthumanacross
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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.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Rethinking Citation of AI Sources in Student-AI Collaboration within HCI Design Education

    cs.HC 2025-06 conditional novelty 6.0 of 10

    Undergraduate design students mostly cite AI tools informally (51% general mention without version or date), and the paper argues this variability reveals the need for reflective, process-aware citation models in HCI ...

  2. What Shapes Writers' Decisions to Disclose AI Use?

    cs.HC 2025-05 conditional novelty 3.0 of 10

    A literature synthesis identifies 12 procedural, social, and personal factors that may shape writers' decisions to disclose AI use.

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