A central argument of the article is that how we define disability at the outset of AI design shapes every step that follows. Definitions guide what data are collected, how labels are assigned, and what outcomes the system is meant to optimize. These definitional choices are rarely transparent (lending themselves to what researchers call the "black box" nature of AI systems). Yet, they embed value judgments that determine whether AI technologies reproduce ableist assumptions or move toward more inclusive design.