This paper offers evidence-based guidance on integrating AI in education, grounded in cognitive science, neuroscience, and empirical research. It examines chatbot strengths and limitations, their effects on students’ memory, learning habits, and study practices, and the governance structures institutions need to protect academic integrity and learning quality. The paper also considers factual reliability, hallucination risk, environmental and infrastructure costs, copyright and data governance, and the gap between vendor claims and actual performance. Its core argument is that AI should enhance learning as a thinking amplifier, not replace human reasoning, and operate within assessment and governance frameworks aligned with institutional values, offering practical guidance for educators and institutions navigating AI use.
Ken Purnell (Thu,) studied this question.