Why is AI not a Panacea for Data Workers? An Interview Study on Human-AI Collaboration in Data Storytelling.

Haotian Li, Yun Wang, Q Vera Liao, Huamin Qu
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Abstract

This paper explores the potential for human-AI collaboration in the context of data storytelling for data workers. Data storytelling communicates insights and knowledge from data analysis. It plays a vital role in data workers' daily jobs since it boosts team collaboration and public communication. However, to make an appealing data story, data workers need to spend tremendous effort on various tasks, including outlining and styling the story. Recently, a growing research trend has been exploring how to assist data storytelling with advanced artificial intelligence (AI). However, existing studies focus more on individual tasks in the workflow of data storytelling and do not reveal a complete picture of humans' preference for collaborating with AI. To address this gap, we conducted an interview study with 18 data workers to explore their preferences for AI collaboration in the planning, implementation, and communication stages of their workflow. We propose a framework for expected AI collaborators' roles, categorize people's expectations for the level of automation for different tasks, and delve into the reasons behind them. Our research provides insights and suggestions for the design of future AI-powered data storytelling tools.

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本文探讨了在为数据工作者讲述数据故事的背景下人类与人工智能合作的潜力。讲数据故事可以传播从数据分析中获得的见解和知识。它在数据工作者的日常工作中发挥着至关重要的作用,因为它能促进团队协作和公共交流。然而,要制作一个吸引人的数据故事,数据工作者需要在各种任务上花费巨大精力,包括故事的大纲和样式。最近,一种日益增长的研究趋势是探索如何利用先进的人工智能(AI)来辅助数据讲故事。然而,现有研究更多关注的是数据讲故事工作流程中的单个任务,并没有全面揭示人类与人工智能合作的偏好。为了弥补这一不足,我们对 18 名数据工作者进行了访谈研究,探讨他们在工作流程的规划、实施和交流阶段对人工智能协作的偏好。我们提出了一个预期人工智能协作者角色的框架,将人们对不同任务自动化程度的期望进行了分类,并深入探讨了其背后的原因。我们的研究为未来人工智能驱动的数据讲故事工具的设计提供了见解和建议。
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