可解释人工智能（XAI）在自动化事实核查中的作用？收益有限，且不存在通用的解释方案
XAI in Automated Fact-Checking? The Benefits Are Modest and There's No One-Explanation-Fits-All
AI总结：
本研究通过180人参与的用户实验探究XAI在自动化事实核查中的作用，发现其对用户认同预测结果和分享意愿影响有限，但能推动用户形成一致判断，且用户对其偏好两极分化，为相关设计提供参考。
摘要：
海量在线信息与虚假信息问题推动了自动化事实核查领域的活跃研究。与人类专家开展的事实核查工作类似，自动化事实核查工具不能仅追求准确性，还需能够告知用户并使其信服其预测结果的有效性，而可解释人工智能（XAI）让这一目标具备了可行性。本研究开展了一项涉及180名参与者的XAI事实核查工具用户研究，探究XAI如何影响用户针对新闻的行为以及他们对解释内容的态度。研究结果表明，XAI对用户认同自动化事实核查工具的真实性预测、以及用户的新闻分享意愿的影响较为有限；但XAI会推动用户对新闻真实性形成更一致的判断，这一现象表明用户依赖于解释内容。此外，研究还发现用户对XAI的偏好存在两极分化，并就此提出了若干设计层面的考量方向。
英文摘要：
The massive volume of online information along with the issue of misinformation has spurred active research in the automation of fact-checking. Like fact-checking by human experts, it is not enough for an automated fact-checker to just be accurate, but also be able to inform and convince the user of the validity of its predictions. This becomes viable with explainable artificial intelligence (XAI). In this work, we conduct a study of XAI fact-checkers involving 180 participants to determine how users' actions towards news and their attitudes towards explanations are affected by the XAI. Our results suggest that XAI has limited effects on users' agreement with the veracity prediction of the automated fact-checker and on their intent to share news. However, XAI nudges users towards forming uniform judgments of news veracity, thereby signaling their reliance on the explanations. We also found polarizing preferences towards XAI and raise several design considerations on them.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
