从反思到修复：数据集文档工具的综述回顾
From Reflection to Repair: A Scoping Review of Dataset Documentation Tools
AI总结：
本文通过综述59篇文献，揭示数据集文档工具设计中的四个阻碍因素，并提出转向机构解决方案以促进可持续文档实践。
摘要：
数据集文档被广泛认为是负责任地开发自动化系统所必需的。尽管通过不同种类的艺术品支持文档化的工作不断增长，但关于塑造文档工具设计动机的因素以及阻碍其采用的因素知之甚少。我们呈现了一项系统性回顾，通过混合方法分析59篇数据集文档化出版物，以探讨构建文档工具的动机，作者如何概念化文档实践，以及这些工具如何与现有系统、法规和文化规范连接。我们的分析显示，在数据集文档化概念化中存在四个持续存在的模式，可能阻碍采用和标准化：文档价值的不明确操作化、去情境化的设计、未解决的劳动需求以及将整合视为未来工作的倾向。基于这些发现，我们提出了一种负责任的人工智能工具设计的转变，即从个人解决方案转向机构解决方案，并概述了人机交互社区可以采取的行动，以促进可持续的文档实践。
英文摘要：
Dataset documentation is widely recognized as essential for the responsible development of automated systems. Despite growing efforts to support documentation through different kinds of artifacts, little is known about the motivations shaping documentation tool design or the factors hindering their adoption. We present a systematic review supported by mixed-methods analysis of 59 dataset documentation publications to examine the motivations behind building documentation tools, how authors conceptualize documentation practices, and how these tools connect to existing systems, regulations, and cultural norms. Our analysis shows four persistent patterns in dataset documentation conceptualization that potentially impede adoption and standardization: unclear operationalizations of documentation's value, decontextualized designs, unaddressed labor demands, and a tendency to treat integration as future work. Building on these findings, we propose a shift in Responsible AI tool design toward institutional rather than individual solutions, and outline actions the HCI community can take to enable sustainable documentation practices.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
