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.

数据叙事是一个强大的沟通数据洞察力的工具，但需要人类创建者具备多种技能和相当的努力。最近的研究广泛探讨了人工智能（AI）在支持和增强数据叙事中与人类的合作潜力，然而目前缺乏一个系统性的回顾来理解数据叙事工具从人工智能与人类合作的角度，这阻碍了研究人员对现有合作工具设计的反思，以促进人类和 AI 的优势并缓解它们的不足。本文通过一个框架从两个角度对现有工具进行调查：工具在叙事工作流程中的阶段，包括分析、规划、实施和沟通，以及每个阶段中人类和 AI 的角色，如创建者、助手、优化者和评审者。通过我们的分析，我们识别出现有工具中的常见合作模式，总结了从这些模式中得到的教训，并进一步说明了人工智能与人类在数据叙事中合作的研究机会。