GoKawiil3. Recommendations
This section details the changes we see as necessary for MIT to prepare our students for a new world. Based on the Institute’s longstanding values, our recommendations are not a checklist of individual initiatives that can be implemented one at a time, bit by bit, but rather a set of substantive changes that must be undertaken in concert.
We recognize that serious change takes time. Given the impacts already affecting our community, however, the required changes should be implemented on two timescales: those that happen immediately, and those that begin immediately, but require further study and planning.
Artificial intelligence – in the form of LLMs and other generative AI technologies – presents MIT with profound challenges and intriguing opportunities.
Already these technologies can produce credible solutions and provide reasonable responses to almost any written assignment in our undergraduate curriculum, including essays, math and science problems, proofs, and coding assignments.
Concerning impacts
Because many students are choosing or feel pressure to shift to learning and problem-solving with AI, in less than three years these technologies have driven major shifts in campus culture, including decreased attendance at office hours, reduced participation in online discussions, and, as we heard anecdotally, a drop in in-person study groups in dorms, libraries, and other study spaces. These issues have presented themselves suddenly and dramatically, creating a clear sense of urgency. They also land at a time when higher education is facing other challenges, and MIT itself is considering broad curricular changes emerging from the findings and recommendations of the Taskforce on the Undergraduate Academic Program (TFUAP).
Intriguing opportunities
While these challenges are pressing, AI also offers exciting opportunities for learning and for creating. Many instructors told us that AI tools help them develop customized, interactive learning tools that allow students to explore subject content with more depth and for instructors to create learning experiences for their students that are new or newly tailored to each student. With a little guidance, even instructors who are not proficient in software development can customize AI agents to support a subject or research project. Students can create large-scale software projects with the limited timeframe of classes that would not have been remotely possible before. They can also use AI to analyze data, conduct research, and build tools to amplify their expertise and pursue projects that benefit them and society at large. The potential of these technologies to augment work across campus is immense.
The recommendations we offer below aim to help the MIT community navigate AI’s challenges and seize its opportunities, while reflecting the principles laid out in Section 2. For instance, Humility means that we must create administrative processes for continuous evaluation and revision rather than assuming any change we make today will be adequate in the future. Boldness requires us not simply to try to patch the existing system to limit or counteract the impacts of AI on our students and systems but instead to redesign learning experiences, assessments, and curricula in ways that help redefine the future of education. Putting humanity front and center means that we will seek uses of AI that strengthen rather than weaken the value of an MIT residential education. Leaning into learning means teaching with intentionality, revisiting what we need students to learn, and aligning assessments with those desired outcomes, to preserve the productive struggle essential to a learning-by-doing education. No one-size-fits-all means that we should develop tailored frameworks for adapting to AI rather than uniform AI rules for all students, instructors, or departments. Augmentation over automation means that we prepare students to use AI fluently and in ways that preserve agency, judgment, integrity, and human connection. Thinking beyond the classroom and the campus requires that we anticipate the skills that our students will need for success in work and life, as community members, future leaders, and creators of the next generation of AI technology.
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