The disabled AI is the super AI: disability as a design principle for superintelligence

The prevailing paradigm of artificial intelligence (AI) development measures progress by accumulating capabilities—more parameters, more tasks, more autonomy. This paper argues that this approach is fundamentally misguided. Drawing on three core insights from disability studies—limitation as a fundamental condition of existence, the interdependent nature of subjects, and ability as relational and contextual—I propose that the path to beneficial superintelligence lies not in maximizing ability but in engineering meaningful disability. A truly super-AI would be defined not by what it can do but by its profound understanding of what it cannot do, and its capacity to communicate this limitation to human users. The paper demonstrates how this reframing addresses current AI crises such as hallucination, offers an alternative to the perilous fantasy of autonomous super-agents, and provides a relational framework for evaluating AI capability.