论文标题
最终用户真正想要什么？以人为本的移动健康应用程序调查
What Do End-Users Really Want? Investigation of Human-Centered XAI for Mobile Health Apps
论文作者
论文摘要
在医疗保健中，AI系统在诊断，治疗和监测中为临床医生和患者提供支持，但是许多系统的可解释性差对于实际应用仍然具有挑战性。克服此障碍是可解释的AI（XAI）的目标。但是，可以对解释有所不同，因此不能为每个人解决黑框问题。以人为中心的AI领域通过将AI适应用户来处理此问题。我们提出了一个以用户为中心的角色概念来评估XAI并使用它来调查最终用户在移动健康压力监测应用程序中的各种解释样式和内容的偏好。我们在线调查的结果表明，用户的人口统计和个性以及解释的类型影响了解释偏好，这表明这些是XAI设计的重要功能。我们将结果包含在三个典型的用户角色中：功率 - 随意和面向隐私的用户。我们的见解使一个以人为中心的Xai更接近实际应用。
In healthcare, AI systems support clinicians and patients in diagnosis, treatment, and monitoring, but many systems' poor explainability remains challenging for practical application. Overcoming this barrier is the goal of explainable AI (XAI). However, an explanation can be perceived differently and, thus, not solve the black-box problem for everyone. The domain of Human-Centered AI deals with this problem by adapting AI to users. We present a user-centered persona concept to evaluate XAI and use it to investigate end-users preferences for various explanation styles and contents in a mobile health stress monitoring application. The results of our online survey show that users' demographics and personality, as well as the type of explanation, impact explanation preferences, indicating that these are essential features for XAI design. We subsumed the results in three prototypical user personas: power-, casual-, and privacy-oriented users. Our insights bring an interactive, human-centered XAI closer to practical application.
