Since we first heard inklings about generative AI and its impact on teaching and learning a few years ago, the topic has dominated seemingly every conversation in higher education, from the informal conversations we have before a committee meeting to formal presentations at conferences. I recall that those first conversations were “will I or won’t I” / “should we or shouldn’t we” types of discussions. While some faculty welcomed this new technology into the classroom, others pressed their full metaphorical weight against the door in an effort to keep it out for just a little longer.
Last school year, the conversations evolved as we accepted that, for better and worse, AI is here to stay. We moved out of the binary and began to discuss how we were adding AI statements to our syllabi and collaborating on ways to model ethical use of AI in our classes. We shared with one another the rules and policies we were enacting in response to AI, and we debated the use of AI detection tools. We were running behind AI with our pockets full of prompts and policies, but it never felt like our actions were making a difference.
This fall, AI discourse is shifting yet again. Instead of leaving instructors in higher education to carve out their own individual response to AI’s impact on education, institutions like MIT and Stanford are calling for sweeping changes to campus culture and assessment of learning in order to ensure that the contract between institution and students guaranteeing a quality education remains unbroken.
In July, Stanford published the white paper titled A roadmap for responsible student assessments in the AI era, and in August, MIT, which by its own words has “deep ties to the birth and development of AI and – through our researchers and our graduates – to its future evolution” published a report created by the MIT Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training.
In these reports, MIT and Stanford both call for an overhaul of higher education in response to AI. MIT notes that “Getting the right answer from a chatbot can create the illusion of learning – but it can also trigger ‘cognitive surrender,’ where students fall back on AI at the first hint of struggle.” Further, both reports independently concluded that the underlying problem presented by AI isn’t about permission–should we allow AI? Should we not allow AI?–but it is that final-product assessment no longer measures what it used to.
So what do these institutions propose as the path forward?
MIT’s report encourages educators to foster a culture that values “leaning into learning” and “productive struggle.” The committee explicitly argues against the use of AI detectors and lockdown browsers, as they are unreliable and corrosive to trust. Instead, the report points instructors toward assessments that are harder for AI to shortcut: for example, oral exams and oral check-ins, portfolios and staged/check-pointed projects, in-class writing paired with out-of-class drafting. In short, we must rethink what authentic learning looks like, and collectively, we must overhaul how we assess learning.
Gauchos, instead of asking “should AI be a part of my classroom?” let’s ask ourselves, “what do I actually need my students to know, what struggles must they undertake to learn that, and how might I best assess their learning?” Then, let us move beyond conversation and work together to change the way we assess learning in this new educational landscape.
Further Reading
Luo, M. (2026, September 10). Columbia prohibits electronic devices in all Literature Humanities, Contemporary Civilization sections. Columbia Daily Spectator. https://www.columbiaspectator.com/news/2026/09/10/columbia-prohibits-electronic-devices-in-all-literature-humanities-contemporary-civilization-sections/
MIT Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training. (2026, August 13). AI and education: Report of MIT’s Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training. Massachusetts Institute of Technology. https://aiandeducation.mit.edu/report/
Schmelzer, R. (2026, August 25). MIT says AI is forcing a rethink of college itself. Forbes. https://www.forbes.com/sites/ronschmelzer/2026/08/25/mit-says-ai-is-forcing-a-rethink-of-college-itself/
Stanford Report. (2026, July 23). A roadmap for responsible student assessments in the AI era. Stanford University. https://news.stanford.edu/stories/2026/07/white-paper-responsible-student-assessments-in-the-ai-era
The Tech. (2026, September 17). MIT AI report takes first step towards an Institute-wide response. https://thetech.com/2026/09/17/ai-committee-report
