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Recent advances in artificial intelligence have introduced automated systems into domains traditionally governed by human judgment, including the evaluation of student writing. Public discussion of AI-assisted grading has largely focused on familiar concerns such as algorithmic bias, fairness, and the capacity of machines to assess human expression. While important, these concerns address only part of a deeper institutional dynamic. This essay proposes that debates surrounding AI grading can be better understood through the concept of institutional time constants. Educational institutions operate as complex decision systems in which authority, evaluation, and feedback form interconnected loops regulating behavior among students, instructors, and administrative structures. These loops evolve under particular temporal assumptions about how quickly information can be processed, judgments rendered, and decisions reviewed. Advances in artificial intelligence alter the temporal environment in which these institutional mechanisms operate. When technologies dramatically shorten the time required to generate evaluative judgments, long-established institutional procedures—designed for slower cycles of human review—may become the slowest component in the system. The resulting mismatch between technological and institutional time scales can produce structural tension within educational governance. Situating the discussion within a broader systems perspective, the essay interprets recent debates about automated grading not simply as questions of fairness or authority, but as manifestations of a deeper shift in the temporal structure of institutional decision-making. In this sense, contemporary developments in educational technology may be viewed as part of a wider pattern observed in modern societies, where rapid technological change reshapes the temporal contours of social institutions.