
Dieser Preprint setzt sich kritisch mit der MIT-Studie (Kos’myna et al. 2025) auseinander, die eine „kognitive Schuld“ bei der Nutzung von LLMs postuliert. Die Analyse zeigt, dass die Studie fundamentale Konzepte wie das Cognitive Offloading und den Generation Effect als Defizite missinterpretiert. Durch ein fehlerhaftes Aufgabendesign (Bodeneffekt) und mangelnde Qualitätsanreize misst die Studie lediglich die funktionale Entlastung durch das Werkzeug, nicht aber den Verlust kognitiver Fähigkeiten. Der Text bietet zudem eine Synthese der aktuellen Evidenzlage (2024–2026) und diskutiert die Bedeutung von KI als kognitives Scaffolding, insbesondere für neurodivergente Nutzer.
This preprint provides a critical analysis of the MIT study (Kos’myna et al. 2025) which postulates "cognitive debt" in LLM usage. The analysis demonstrates that the study misinterprets fundamental concepts such as cognitive offloading and the generation effect as deficits. Due to flawed task design (floor effect) and a lack of quality incentives, the study merely measures the tool's functional relief rather than a loss of cognitive abilities. The paper also offers a synthesis of current evidence (2024–2026) and discusses the role of AI as cognitive scaffolding, particularly for neurodivergent users.
Artificial intelligence, Neurodivergence, Cognitive Load Theory, Artificial Intelligence, Cognitive Debt, Study Review, Cognitive Offloading
Artificial intelligence, Neurodivergence, Cognitive Load Theory, Artificial Intelligence, Cognitive Debt, Study Review, Cognitive Offloading
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