This article aims to reconcile the technical and epistemic dimensions of Explainable AI (XAI) with its ethical components. I argue that XAI’s validity is comprised of its model application and verification from a technical viewpoint in AI design. However, this concept and methodology also serve ethical aims by examining algorithmic calculations a posteriori, which can produce computationally generated inequities towards marginalized groups. By linking its epistemic and ethical goals, I examine how XAI’s models can be improved through a political, social, and epistemological framework centered on the knowledge production of discriminated groups. Feminist standpoint theory highlights the context in which knowers situate themselves and inform their cognitive contents with their social locations and experiences. Emphasizing social contexts in the case of XAI allows me to expand its technical validity to subjective experiences of oppression that are structurally sustained in the Global North. By doing this, I argue that rethinking the use of XAI would ultimately enhance the field of AI ethics.