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.

翻译：我们探讨以下问题：可解释人工智能（XAI）应如何、为谁以及为何旨在支持用户的能动性目标？具体而言，我们通过案例研究和思想实验，以用户为中心的分析视角审视能动性与解释之间的关系。研究发现，解释作为实现能动性的若干可能初始步骤之一，使用户能够在未来交互中以更有效的方式将预先思考转化为结果。我们还观察到，当结合解释与用户控制时，XAI系统可能更好地服务于非专业用户（尤其是“改进型用户”），使其能够做出有意义的改变。