Explanations--a form of post-hoc interpretability--play an instrumental role
in making systems accessible as AI continues to proliferate complex and
sensitive sociotechnical systems. In this paper, we introduce Human-centered
Explainable AI (HCXAI) as an approach that puts the human at the center of
technology design. It develops a holistic understanding of "who" the human is
by considering the interplay of values, interpersonal dynamics, and the
socially situated nature of AI systems. In particular, we advocate for a
reflective sociotechnical approach. We illustrate HCXAI through a case study of
an explanation system for non-technical end-users that shows how technical
advancements and the understanding of human factors co-evolve. Building on the
case study, we lay out open research questions pertaining to further refining
our understanding of "who" the human is and extending beyond 1-to-1
human-computer interactions. Finally, we propose that a reflective HCXAI
paradigm-mediated through the perspective of Critical Technical Practice and
supplemented with strategies from HCI, such as value-sensitive design and
participatory design--not only helps us understand our intellectual blind
spots, but it can also open up new design and research spaces.Comment: In Proceedings of HCI International 2020: 22nd International
Conference On Human-Computer Interactio