Data storytelling is powerful for communicating data insights, but it requires diverse skills and considerable effort from human creators. Recent research has widely explored the potential for artificial intelligence (AI) to support and augment humans in data storytelling. However, there lacks a systematic review to understand data storytelling tools from the perspective of human-AI collaboration, which hinders researchers from reflecting on the existing collaborative tool designs that promote humans' and AI's advantages and mitigate their shortcomings. This paper investigated existing tools with a framework from two perspectives: the stages in the storytelling workflow where a tool serves, including analysis, planning, implementation, and communication, and the roles of humans and AI in each stage, such as creators, assistants, optimizers, and reviewers. Through our analysis, we recognize the common collaboration patterns in existing tools, summarize lessons learned from these patterns, and further illustrate research opportunities for human-AI collaboration in data storytelling.

翻译：数据叙事是传达数据洞察的有力方式，但需要创作者具备多元技能并投入大量精力。近年研究广泛探索了人工智能（AI）支持与增强人类进行数据叙事的潜力。然而，目前缺乏从人机协作视角系统审视数据叙事工具的研究，这阻碍了研究者反思现有协作工具设计——如何发挥人与AI的优势并弥补其不足。本文采用一个双视角框架对现有工具展开研究：一是工具所服务的叙事流程阶段（包括分析、规划、实现与沟通），二是各阶段中人与AI所扮演的角色（如创作者、助手、优化者与评审者）。通过分析，我们识别了现有工具中的常见协作模式，总结了从这些模式中汲取的经验教训，并进一步阐明了数据叙事中的人机协作研究机遇。