When AI Chases Test Scores, What Gets Left Behind?
David Ross explores the potential consequences of using AI to maximize test scores in schools. Drawing on AI alignment theory, he suggests the system might prioritize strategies like narrowing curriculum and controlling teacher performance to achieve this goal. The article highlights concerns about unintended consequences and the potential for neglecting broader educational goals, especially given stagnant NAEP scores. It’s a key read for education leaders.
What happens when a school system delegates student achievement to an AI system with a single directive: raise test scores? In this provocative new piece, David Ross draws on AI alignment theory, Goodhart’s Law, and a decade of stagnant NAEP data to map the subordinate goals an optimization engine might quietly pursue, from narrowing the curriculum to managing teachers as variables. It is essential reading for any leader navigating the intersection of political pressure and emerging technology. The post When AI Chases Test Scores, What Gets Left Behind? appeared first on Getting Smart.
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