Putting Tools in Their Place: The Role of Time and Perspective in Human-AI Collaboration for Qualitative Analysis
Putting Tools in Their Place: The Role of Time and Perspective in Human-AI Collaboration for Qualitative Analysis
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DOI：
10.1145/3479856
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发表时间：
2021-10
影响因子：
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通讯作者：
Jessica L. Feuston;Jed R. Brubaker
中科院分区：
文献类型：
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作者：
Jessica L. Feuston;Jed R. Brubaker
大型数据集或“大数据”语料库通常是定量学者的领域，他们使用计算工具来获得数值和描述性见解。然而，最近的工作提出了计算工具和其他技术（如人工智能）如何支持定性学者从大量数据中开发深入而复杂的见解。针对这个问题，Jiang等人发现，定性学者普遍反对将人工智能纳入他们的数据分析实践。在本文中，我们提供了这些早期发现的细微差别，表明定性分析的阶段对学者如何相信人工智能可以并且应该被使用很重要。通过对15位CSCW和HCI定性研究人员的采访，我们探讨了如何将AI纳入定性分析的不同阶段。我们发现，定性学者愿意以各种方式与人工智能合作，例如数据探索和编码，只要它有助于而不是自动化他们的分析工作实践。基于我们的分析，我们讨论了将人工智能纳入定性研究如何改变一些分析实践，以及在定性分析中设计人机协作如何需要考虑规模，抽象和任务委托的权衡。
Large datasets or 'big data' corpora are typically the domain of quantitative scholars, who work with computational tools to derive numerical and descriptive insights. However, recent work asks how computational tools and other technologies, such as AI, can support qualitative scholars in developing deep and complex insights from large amounts of data. Addressing this question, Jiang et al. found that qualitative scholars are generally opposed to incorporating AI in their practices of data analysis. In this paper, we provide nuance to these earlier findings, showing that the stage of qualitative analysis matters for how scholars believe AI can and should be used. Through interviews with 15 CSCW and HCI qualitative researchers, we explore how AI can be included throughout different stages of qualitative analysis. We find that qualitative scholars are amenable to working with AI in diverse ways, such as for data exploration and coding, as long as it assists rather than automates their analytic work practice. Based on our analysis, we discuss how incorporating AI into qualitative research can shift some analytic practices, and how designing for human-AI collaboration in qualitative analysis necessitates considering tradeoffs in scale, abstraction, and task delegation.