验证你的信息（FYI）：一项用于理解人们如何实际核查数据驱动文章的设计探针
Fact-Check Your Information (FYI): A Design Probe to Understand How People Actually Fact-Check Data-Driven Articles
AI总结：
本研究提出嵌入阅读环境的浏览器扩展FYI作为设计探针，通过含四类工具的探索性研究（N=22），明确了用户核查数据主张的三类工作流，提出事实核查系统需将AI作为补充、强化可视化并支持灵活工作流的建议。
AI中文摘要：
数据驱动新闻与政策报告常依赖基于统计证据的陈述，即数据主张。验证此类主张需将其与底层结构化数据集关联，但现有系统通常将自动事实核查与手动数据探索分离，导致读者在实践中如何协调AI辅助与手动核查证据的方式尚不明确。我们提出FYI，一款嵌入阅读环境的浏览器扩展程序，并将其作为设计探针，研究人们如何针对底层数据集检测、验证及判定数据主张的有效性。FYI提供从全自动化到手动数据探索的四种互补工具。在一项探索性研究（N=22）中，参与者使用FYI核查数据驱动文章中的主张。我们发现参与者采用三种不同工作流原型：先AI后手动确认、先手动后AI补充、并行协同核查，其中可视化是核查AI结论的主要机制。对AI的信任动态变化：当多种工具结果一致时信任增强，当AI输出不一致时信任下降。这些发现表明，事实核查系统应将AI视为人类核查补充而非权威的起点，将可视化提升为核心核查能力，并支持灵活的用户驱动工作流。我们将FYI作为开源软件发布，供进一步研究，网址为this https URL。
英文摘要：
Data-driven journalism and policy reports frequently rely on statements grounded in statistical evidence, referred to as data claims. Verifying such a claim requires connecting it to the underlying structured dataset. However, existing systems typically isolate automated fact-checking from manual data exploration, leaving it unclear how readers coordinate AI assistance with manual inspection of the evidence in practice. We present FYI, a browser extension that embeds fact-checking in the reading environment, and use it as a design probe to study how people detect, verify, and determine the validity of data claims against the underlying dataset. FYI provides four complementary tools spanning the spectrum from full automation to manual data exploration. In an exploratory study (N=22), participants used FYI to fact-check claims in a data-driven article. We find that participants adopted three distinct workflow archetypes---AI-first with manual confirmation, manual-first with AI supplement, and parallel co-review---with visualization serving as the primary mechanism for auditing AI conclusions. Trust in AI shifted dynamically, growing when multiple tools converged and eroding when AI outputs were inconsistent. These findings suggest that fact-checking systems should treat AI as a starting point that human verification complements rather than a definitive authority, elevate visualization as a core verification capability, and support flexible, user-driven workflows. We release FYI as open-source software for further research at https://github.com/DataVisards/FYI.
