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MUNK DEBATE ON AI (COMMENTARY) [DAVID FOSTER]

Machine Learning Street Talk (MLST)

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Navigating AI in Education

This chapter explores the dual-edged implications of artificial intelligence in education, addressing both its potential as a learning tool and the risks of diminishing student responsibility. The speakers engage in a nuanced debate about the concept of 'objective-driven AI,' emphasizing the importance of emotional understanding in AI systems while critiquing prevailing theories on alignment and AGI. Through discussions on cognitive skill acquisition and abstract reasoning, they highlight the need for proactive guidance from educational authorities to harness AI's transformative effects.

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