Artificial intelligence can write the essay, solve the equation, generate the code, summarize the book—and increasingly perform the very tasks students have traditionally done in order to learn.
So what happens to education?
In a striking new statement, MIT calls the arrival of generative AI a “watershed moment” for higher education. But rather than simply asking whether students should be allowed to use AI, MIT is confronting a much larger question: What should a university actually teach when answers are becoming almost free?
In this episode of The Common Room, we use MIT’s new approach as the starting point for a wider conversation about learning, knowledge and human intelligence.
Why should an engineering student learn calculations that AI can perform instantly? What must we know ourselves before we can judge whether an AI-generated answer is right? Will essays and homework give way to oral examinations, laboratories, design reviews and hands-on projects? Could AI make great individual tutoring available to millions—or create a generation increasingly dependent on machines to think?
And perhaps most importantly:
If a machine can produce the answer, why should a human being learn how to produce it?
Perhaps because education was never merely about producing answers.
It was about forming the person capable of understanding them.
Join us in The Common Room for a conversation about MIT, artificial intelligence, engineering, teaching—and what education is ultimately for.
Stories • Ideas • Wonder
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