AI记者来了：它写的新闻每句话都能查证
你看到的新闻可能很快就不再是记者一个人写的了。这篇论文做了一个叫 Data2Story 的 AI 系统，它像一个虚拟编辑部：有角色负责找数据、做分析、选角度、设计图表，最后生成一篇带交互地图、音频的多媒体文章。最特别的是，它写的每一句话——每个数字、每个结论——都链回原始数据或代码，你可以点开验证。研究者拿它和人类记者写的18篇真实报道对比，发现AI在透明度和可查证性上更强，但人类在创意和叙事角度上仍有优势。它不是你明天就能用的工具，但它展示了一个方向：未来的新闻可能不再是“信不信由你”，而是“不信你就查”。
📄 原文摘要(英文)
Data tells stories that shape society; the data journalist's job is to turn raw information into stories non-experts can trust. A high-quality news feature takes a newsroom team weeks: hunting for context, running statistics, choosing an angle, and designing visuals. Recent agents handle individual steps well: data-science agents close the analysis loop, while design agents synthesize beautiful websites. But can an agent serve as a data journalist end to end? We introduce Data Journalist Agent (Data2Story), a multi-agent framework that orchestrates specialized roles into a single virtual newsroom. Data2Story contributes two innovations. (i) Claims are evidence-grounded: an Inspector links every number, angle, and asset back to data, code, or an external reference. (ii) Articles are multimodally generative: rather than defaulting to plain text and static charts, Data2Story reasons about what readers will want to see, then deploys multimodal tools, such as interactive maps for geography and audio for music. We evaluate Data2Story on 18 articles, each paired with the originally published expert piece, along four axes: (a) human-agent angle coverage; (b) rubric evaluation with 53 participants across five dimensions; (c) computer-use agents as judges, a cost-saving proxy for how readers navigate interactive articles; and (d) verifiability, where a coding verifier re-executes statements against the data and checks claims against references. Data2Story produces competitive, evidence-traceable multimedia stories, with particular strength in transparency and auditability. Human articles retain an edge in editorial angle, creative design, and presentation. We position Data2Story as a collaborator for journalists, enabling more evidence-based, transparent, and verifiable reporting. Code and demos are available at https://data2story.github.io.