  We grapple with the question: How, for whom and why should explainable
artificial intelligence (XAI) aim to support the user goal of agency? In
particular, we analyze the relationship between agency and explanations through
a user-centric lens through case studies and thought experiments. We find that
explanation serves as one of several possible first steps for agency by
allowing the user convert forethought to outcome in a more effective manner in
future interactions. Also, we observe that XAI systems might better cater to
laypersons, particularly "tinkerers", when combining explanations and user
control, so they can make meaningful changes.
