发表机构
University of Illinois Chicago; CNRS (French National Centre for Scientific Research); Utrecht University; Stuttgart Technical University of Applied Sciences; Universitat Politècnica de Catalunya（伊利诺伊大学芝加哥分校; 法国国家科学研究中心; 乌得勒支大学; 斯图加特应用技术大学; 加泰罗尼亚理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出数据可视化研究应支持对AI的信任与健康怀疑，探讨过度依赖现象及可视化在促进批判性思考中的作用。
AI 中文摘要
历史上，关于人工智能（AI）模型的数据可视化研究一直侧重于通过AI的可视化解释来增强信任。这一关于可信度的工作至少部分建立在一种假设之上，即人类是批判性的用户，不太可能采用AI技术。但越来越清楚的是，人类对AI的信任水平实际上跨度很大，从批判性到过度依赖。目前迫切需要同时支持对AI解决方案的信任和健康的怀疑。我们认为，人类对AI模型的结果以及对此类AI模型的使用采取怀疑态度是健康的。我们分享了对AI模型过度依赖这一日益凸显的现象的看法，使用AI模型的风险与机遇，以及在人类没有动力进行批判性思考的过度依赖情境中，数据可视化所扮演的角色。
英文摘要
Research in data visualization of artificial intelligence (AI) models has historically focused on enhancing trust through visual explanations of AI. The trustworthiness line of work was built at least partially on an assumption that humans were critical users unlikely to adopt AI technology. It is increasingly clear that human trust levels in AI span, in fact, a wide range from critical to over-reliant. There is an urgent need to support both trust and healthy skepticism in AI solutions. We argue that it is healthy for humans to adopt a skeptical view both on the results of AI models and on the use of such AI models. We share our thoughts on the rising phenomenon of over-reliance on AI models, the risks and opportunities in using AI models, and the role of data visualization in over-reliance situations where humans are not motivated to engage in critical thinking.
