Co-Designing for Transparency: Lessons from Building a Document Organization Tool in the Criminal Justice Domain

Co-Designing for Transparency: Lessons from Building a Document Organization Tool in the Criminal Justice Domain
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共同设计透明度:在刑事司法领域构建文档组织工具的经验教训

DOI:
10.1145/3593013.3594093
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发表时间:
2023
期刊:
ACM
影响因子:
--
通讯作者:
Chasins, Sarah
Chasins, Sarah
中科院分区:
--
文献类型:
--
作者:
Nigatu, Hellina Hailu;Pickoff-White, Lisa;Canny, John;Chasins, Sarah

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调查记者和公设辩护律师负责审查、报道和辩论围绕警察使用武力和不当行为的关键案件。在理想的情况下,他们应该能够访问组织良好的记录,他们可以轻松地导航和搜索。在现实中,记录可能是大的、无组织的数据转储,增加了本已资源有限的团队的负担。在一个由利益相关者和计算机科学家组成的跨学科研究团队中,我们与美国的公设辩护律师和调查记者密切合作,共同设计了一个人工智能增强工具,以应对处理此类数据转储的挑战。我们的文档组织工具(DOT)是一个具有数据清理、提取和组织功能的Python库。我们的协作设计流程让我们深入了解了使用大型数据转储的资源不足团队的需求,例如一些领域专家如何成为自学成才的程序员来自动化他们的任务。为了了解哪种类型的编程范例可以支持我们的目标用户,我们进行了一项用户研究(n=18),比较了可视化编程、逐例编程和传统的基于文本的编程工具。从我们的用户研究中,我们发现,一旦用户通过了最初的学习阶段,他们就可以轻松地使用这三种范式。我们的工作为与资源不足的团队合作的设计师提供了见解,这些团队希望将尖端算法和人工智能技术整合到统一的、富有表现力的工具中。我们认为,以用户为中心的工具设计可以通过支持现有从业者在刑事司法等领域的工作,为更广泛的问责和透明度斗争做出贡献。
Investigative journalists and public defenders conduct the essential work of examining, reporting, and arguing critical cases around police use-of-force and misconduct. In an ideal world, they would have access to well-organized records they can easily navigate and search. In reality, records can come as large, disorganized data dumps, increasing the burden on the already resource-constrained teams. In a cross-disciplinary research team of stakeholders and computer scientists, we worked closely with public defenders and investigative journalists in the United States to co-design an AI-augmented tool that addresses challenges in working with such data dumps. Our Document Organization Tool (DOT) is a Python library that has data cleaning, extraction, and organization features. Our collaborative design process gave us insights into the needs of under-resourced teams who work with large data dumps, such as how some domain experts became self-taught programmers to automate their tasks. To understand what type of programming paradigm could support our target users, we conducted a user study (n=18) comparing visual, programming-by-example, and traditional text-based programming tools. From our user study, we found that once users passed the initial learning stage, they could comfortably use all three paradigms. Our work offers insights for designers working with under-resourced teams who want to consolidate cutting-edge algorithms and AI techniques into unified, expressive tools. We argue user-centered tool design can contribute to the broader fight for accountability and transparency by supporting existing practitioners in their work in domains like criminal justice.
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