This MIT report is probably one of the most thoughtful institutional reflections produced so far on the impact of AI on education. It recognizes that the challenge cannot be reduced to academic misconduct or to establish rules for the use of ChatGPT. What is at stake is the very purpose of the University.
The report introduces a particularly apt expression: “cognitive surrender.” Obtaining a correct answer quickly can create an illusion of learning, leading students to hand over to the machine the effort, doubt and resistance through which imagination, judgment and intellectual autonomy are developed.
However, I believe the report is still stronger at protecting education from AI than at imagining a new form of education made possible by AI.
Its dominant question appears to be: How can we preserve genuine learning when machines can already perform much of the cognitive work traditionally required of students?
A second, more ambitious question is missing: What can students now imagine, model and build that would previously have been impossible?
A university prepared for the age of AI should not limit itself to educating competent and responsible users of these tools. It should educate builders capable of combining human intelligence, AI models, agents, simulations, sensors, robots, institutions and natural systems to intervene responsibly in the world.
The fundamental unit of education may therefore gradually cease to be the “AI-aware” discipline and become the Human–Machine–Nature project.
Instead of asking only for answers that a machine can produce, we can challenge students to build living models of an estuary, a city, an organization, an ecosystem, a sports team or a community. These models should integrate data, represent hypotheses, simulate possible futures, make uncertainties explicit, confront different perspectives and, above all, be tested against reality.
In this form of education, the central question of assessment will no longer be only, “What knowledge have you acquired?” It will also ask: What did you imagine? What did you build? Does it work in the real world? What resistance did you encounter? Who benefits? Can you defend your choices and understand their consequences?
MIT correctly identifies the first great imperative: we cannot allow students to surrender their capabilities to AI.
I would add a second: we must use AI to radically amplify the human capacity to imagine, understand and build worlds that neither humans nor machines could create independently.
I am certain that MIT students will do precisely this, benefiting from the programs—particularly UROP, Sandbox and the $100K Competition—and the laboratories available to them.