Trust is widely regarded as a critical component to build artificial intelligence (AI) systems that people will use and safely rely upon. As research in this area continues to evolve, it becomes imperative that the HCI research community synchronize their empirical efforts and align on the path toward effective knowledge creation. To lay the groundwork toward achieving this objective, we performed a comprehensive bibliometric analysis of two decades of empirical research measuring trust in AI, comprising 538 core articles and 15'548 cited articles across multiple disciplines. A key insight arising from our analysis is the persistence of an exploratory approach across the research landscape. To foster a deeper understanding of trust in AI, we advocate for a contextualized strategy. To pave the way, we outline a research agenda, highlighting questions that require further investigation.

翻译：信任被广泛认为是构建人们愿意使用并安全依赖的人工智能（AI）系统的关键组成部分。随着该领域研究的不断发展，人机交互（HCI）研究共同体亟需协调其实证工作，并在有效知识创造的路径上达成共识。为实现这一目标，我们对二十年来测量AI信任的实证研究进行了全面的文献计量分析，涵盖来自多学科的538篇核心文章及15,548篇引文。分析得出的关键洞见是，整个研究领域中探索性方法持续存在。为促进对AI信任的更深层次理解，我们倡导一种情境化策略。为开辟道路，我们概述了一项研究议程，突出了需要进一步探究的问题。