Operationalizing Human-Centered Perspectives in Explainable AI

The realm of Artifcial Intelligence (AI)’s impact on our lives is far reaching – with AI systems proliferating high-stakes domains such as healthcare, fnance, mobility, law, etc., these systems must be able to explain their decision to diverse end-users comprehensi- bly. Yet the discourse of Explainable AI (XAI) has been predomi- nantly focused on algorithm-centered approaches, sufering from gaps in meeting user needs and exacerbating issues of algorith- mic opacity. To address these issues, researchers have called for human-centered approaches to XAI. There is a need to chart the domain and shape the discourse of XAI with refective discussions from diverse stakeholders. The goal of this workshop is to examine how human-centered perspectives in XAI can be operationalized at the conceptual, methodological, and technical levels. Encourag- ing holistic (historical, sociological, and technical) approaches, we put an emphasis on “operationalizing”, aiming to produce action- able frameworks, transferable evaluation methods, concrete design guidelines, and articulate a coordinated research agenda for XAI.