研究人机共创中如何给AI贡献合理署名，发现人类更倾向低估AI贡献。
Which Contributions Deserve Credit? Perceptions of Attribution in Human-AI Co-Creation
- 通过问卷调查分析知识工作者对人机协作贡献的署名认知。
- 相同贡献下，人类比AI获得更高评价，尤其在主动性和创造性方面。
- 适合关注人机协作伦理、知识产权与工作流程设计的研究者。
由大型语言模型驱动的AI系统在写作与编辑任务中可作为得力助手，与人类共同创作作品。在此类协作中，AI会做出原创性贡献。然而，一个核心问题是：应如何为这些贡献赋予适当署名？本研究通过一项包含155名受访者的调查，探讨了知识工作者对署名的看法。结果表明，人们对不同类型的贡献、贡献量以及主动性赋予的信用存在差异。相较于人类伙伴，即使贡献相当，人们仍普遍给予AI更低的署名权重。参与者认为披露AI参与至关重要，并依据贡献质量、个人价值观及技术因素进行署名判断。研究结果为构建新型人机共创成果署名机制提供了理论支持与实践指导。
原文摘要 · Abstract (English)
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.
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。