TY - CHAP A1 - Mucha, Henrik A1 - Robert, Sebastian A1 - Breitschwerdt, Ruediger A1 - Fellmann, Michael T1 - Interfaces for Explanations in Human-AI Interaction: Proposing a Design Evaluation Approach T2 - Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA N2 - Explanations in Human-AI Interaction are communicated to human decision makers through interfaces. Yet, it is not clear what consequences the exact representation of such explanations as part of decision support systems (DSS) and working on machine learning (ML) models has on human decision making. We observe a need for research methods that allow for measuring the effect different eXplainable AI (XAI) interface designs have on people’s decision making. In this paper, we argue for adopting research approaches from decision theory for HCI research on XAI interface design. We outline how we used estimation tasks in human-grounded design research in order to introduce a method and measurement for collecting evidence on XAI interface effects. To this end, we investigated representations of LIME explanations in an estimation task online study as proof-of-concept for our proposal. KW - Human-AI Interaction Y1 - 2021 UR - https://doi.org/10.1145/3411763.3451759 SP - 327 ER -