论文标题
询问AI：为可解释的AI用户体验的设计实践提供信息
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
论文作者
论文摘要
对可解释的AI（XAI）的兴趣激增，导致了有关该主题的大量算法工作。尽管许多人认识到在AI系统中纳入可解释性功能的必要性，但如何满足现实世界中用户了解AI的需求仍然是一个空旷的问题。通过采访20名UX和设计从业人员从事各种AI产品的工作，我们试图确定当前的XAI算法工作与实践之间的差距，以创建可解释的AI产品。为此，我们开发了一个算法的XAI问题库，其中用户对解释性的需求表示为用户可能会询问的有关AI的典型问题，并将其用作研究探针。我们的工作为XAI的设计空间提供了洞察力，为支持该领域的设计实践的努力提供了启示，并确定了未来XAI工作的机会。我们还提供了一个扩展的XAI问题库，并讨论如何将其用于创建以用户为中心的XAI。
A surge of interest in explainable AI (XAI) has led to a vast collection of algorithmic work on the topic. While many recognize the necessity to incorporate explainability features in AI systems, how to address real-world user needs for understanding AI remains an open question. By interviewing 20 UX and design practitioners working on various AI products, we seek to identify gaps between the current XAI algorithmic work and practices to create explainable AI products. To do so, we develop an algorithm-informed XAI question bank in which user needs for explainability are represented as prototypical questions users might ask about the AI, and use it as a study probe. Our work contributes insights into the design space of XAI, informs efforts to support design practices in this space, and identifies opportunities for future XAI work. We also provide an extended XAI question bank and discuss how it can be used for creating user-centered XAI.
