Which Contributions Deserve Credit? Perceptions of Attribution in Human-AI Co-Creation
Jessica He, Stephanie Houde, Justin D. Weisz
摘要
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.
问问这篇 Paper
智能体会读完全文。
Lune 把这篇 Paper 索引到了每一个公式,引用它的顶会 Paper 也一样。你提问,回答直接引用原文。
引用它的顶会 Paper14
- Current and Future Use of Large Language Models for Knowledge WorkMichelle Brachman, Amina H. El-Ashry, Casey Dugan, Werner GeyerCSCW 2025 · 被引用 10 次
- Frankentext: Stitching random text fragments into long-form narrativesChau Minh Pham, Jenna Russell, Dzung Pham, Mohit IyyerACL 2026 · 被引用 7 次
- How Do Human Creators Embrace Human-AI Co-Creation? A Perspective on Human Agency of ScreenwritersYuying Tang, Jiayi Zhou, Haotian Li, Xing Xie 等CHI 2026 · 被引用 6 次
- Co-Designing Collaborative Generative AI Tools for FreelancersKashif Imteyaz, Michael Muller, Claudia Flores-Saviaga, Saiph SavageCHI 2026 · 被引用 4 次
- The AI Memory Gap: Users Misremember What They Created With AI or WithoutTim Zindulka, Sven Goller, Daniela Fernandes, Robin Welsch 等CHI 2026 · 被引用 4 次
它引用的顶会 Paper12
- To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-assisted Decision-makingZana Buçinca, Maja Barbara Malaya, Krzysztof Z. GajosCSCW 2021 · 被引用 962 次
- The Stable Signature: Rooting Watermarks in Latent Diffusion ModelsPierre Fernandez, Guillaume Couairon, Hervé Jégou, Matthijs Douze 等ICCV 2023 · 被引用 370 次
- CoAuthor: Designing a Human-AI Collaborative Writing Dataset for Exploring Language Model CapabilitiesMina Lee, Percy Liang, Qian YangCHI 2022 · 被引用 340 次
- RADAR: Robust AI-Text Detection via Adversarial LearningXiaomeng Hu, Pin-Yu Chen, Tsung-Yi HoNeurIPS 2023 · 被引用 315 次
- Novice-AI Music Co-Creation via AI-Steering Tools for Deep Generative ModelsRyan Louie, Andy Coenen, Cheng Zhi Huang, Michael Terry 等CHI 2020 · 被引用 265 次
相关 Paper
- LLM or Human? Perceptions of Trust and Quality in Research SummariesNil-Jana Akpinar, Sandeep Avula, Chia-Jung Lee, Brandon Dang 等CHI 2026 · 被引用 2 次
- How Does the Disclosure of AI Assistance Affect the Perceptions of Writing?Zhuoyan Li, Chen Liang, Jing Peng, Ming YinEMNLP 2024 · 被引用 8 次
- The Value, Benefits, and Concerns of Generative AI-Powered Assistance in WritingZhuoyan Li, Chen Liang, Jing Peng, Ming YinCHI 2024 · 被引用 78 次
- Partnering with Generative AI: Experimental Evaluation of Model-Led and Human-Led Interaction in Human-AI Co-CreationSebastian Maier, Manuel Schneider, Stefan FeuerriegelCHI 2026 · 被引用 5 次
- The Effects of Perceived AI Use On Content PerceptionsIrene RaeCHI 2024 · 被引用 38 次
