2nd Workshop on Exploring the Potential of XAI and HMI to Alleviate Ethical, Legal, and Social Conflicts in Automated Vehicles: Applying HCXAI to Discover User Explainability Needs

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Abstract
As automated vehicles (AVs) are increasingly deployed in real-world environments, users often do not understand what decisions their vehicles are making, or why. Explainable AI (XAI) offers a promising path toward transparency, yet most existing approaches remain algorithm-centric and inaccessible to end users. This workshop explores how Human-Centered XAI (HCXAI) and the Question-Driven Design framework can be used to systematically discover user explainability needs for AVs. Through scenario-based, participatory activities, participants will adopt different stakeholder perspectives and generate the questions they would want an AV to answer in ambiguous driving situations. Building on the prior workshop at AutomotiveUI 2025, this workshop aims to produce an initial taxonomy of AV-specific explanation needs grounded in real user questions, creating a shared resource that can guide future research, UI design, and evaluation of explainable automated driving systems.
Funding Information
  • National Research Foundation of Korea (NRF) funded by the Ministry of Education (RS-2025-25425154)