让乘客看懂自动驾驶决策，提升信任与接受度。
What Do People Want to Know About Artificial Intelligence (AI)? The Importance of Answering End-User Questions to Explain Autonomous Vehicle (AV) Decisions
- 通过用户研究挖掘乘客关心的AI决策问题，设计针对性解释
- 交互式文字解释显著提升用户对自动驾驶决策的理解
- 为普通用户设计可提问的解释系统，适合交通科技产品开发
提升终端用户对人工智能驱动自动驾驶车辆决策的理解，有助于提高其使用率与接受度。然而，当前解释机制主要服务于研究人员和工程师用于调试与监控，难以回应乘客等终端用户在不同场景下对自动驾驶行为的具体疑问。本文通过两次用户研究，调查潜在乘客在乘坐自动驾驶车辆时可能提出的问题，并评估回答这些问题如何提升其对AI决策的理解。初步探索性研究识别出一系列现有解释系统难以覆盖的自动驾驶中关于AI的疑问。第二项研究证实，相较于仅观察车辆决策，交互式文本解释能有效提升参与者对自动驾驶决策的认知水平。研究结果为激发终端用户主动询问并理解人工智能决策背后的逻辑提供了设计依据。
原文摘要 · Abstract (English)
Improving end-users' understanding of decisions made by autonomous vehicles (AVs) driven by artificial intelligence (AI) can improve utilization and acceptance of AVs. However, current explanation mechanisms primarily help AI researchers and engineers in debugging and monitoring their AI systems, and may not address the specific questions of end-users, such as passengers, about AVs in various scenarios. In this paper, we conducted two user studies to investigate questions that potential AV passengers might pose while riding in an AV and evaluate how well answers to those questions improve their understanding of AI-driven AV decisions. Our initial formative study identified a range of questions about AI in autonomous driving that existing explanation mechanisms do not readily address. Our second study demonstrated that interactive text-based explanations effectively improved participants' comprehension of AV decisions compared to simply observing AV decisions. These findings inform the design of interactions that motivate end-users to engage with and inquire about the reasoning behind AI-driven AV decisions.
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