论文标题
自治，而不是自动化：事实检查器的活动和需求，作为设计以人为本的AI系统的基础
Autonomation, not Automation: Activities and Needs of Fact-checkers as a Basis for Designing Human-Centered AI Systems
论文作者
论文摘要
为了更有效地减轻虚假信息的负面影响，需要开发人工智能（AI）系统来协助事实检查者。然而，缺乏关注这些利益相关者的需求的关注导致他们对自动化整个事实核对过程的自动化有限和持怀疑态度。在这项研究中，我们对中欧事实检查员进行了半结构化的深入访谈。使用迭代内容分析分析了他们的活动和问题。对欧洲事实检查者的调查得以确认最重大的问题，其中我们收集了来自20个国家 /地区的24个回答，即62％的国际事实检查网络（IFCN）的活跃欧洲签署者中有62％。 我们的贡献包括对非英语区域中事实检查工作的可变性进行深入研究，这些差异仍然在很大程度上被发现。通过使他们与先前研究的知识保持一致，我们创建了有助于了解事实检查过程的概念模型。多亏了跨学科的合作，我们将AI研究中的事实检查过程扩展到了其他三个阶段。此外，我们将发现的结果绘制在事实检查者的活动中，并需要针对AI研究的相关任务。为AI研究人员和开发人员确定的新机会对该领域的AI研究重点有影响。
To mitigate the negative effects of false information more effectively, the development of Artificial Intelligence (AI) systems assisting fact-checkers is needed. Nevertheless, the lack of focus on the needs of these stakeholders results in their limited acceptance and skepticism toward automating the whole fact-checking process. In this study, we conducted semi-structured in-depth interviews with Central European fact-checkers. Their activities and problems were analyzed using iterative content analysis. The most significant problems were validated with a survey of European fact-checkers, in which we collected 24 responses from 20 countries, i.e., 62\% of active European signatories of the International Fact-Checking Network (IFCN). Our contributions include an in-depth examination of the variability of fact-checking work in non-English speaking regions, which still remained largely uncovered. By aligning them with the knowledge from prior studies, we created conceptual models that help understand the fact-checking processes. Thanks to the interdisciplinary collaboration, we extend the fact-checking process in AI research by three additional stages. In addition, we mapped our findings on the fact-checkers' activities and needs to the relevant tasks for AI research. The new opportunities identified for AI researchers and developers have implications for the focus of AI research in this domain.
