Unfixed Newsletter — August 3–September 2, 2026
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What a busy month! MIT has published a report getting a lot of traction calling for fundamental changes to how the University works. Other campuses are also in motion, often working AI literacy into programming across the curriculum. Outside the walls of the academy, the news continues to be quite strange. From our own work, remember to check out our interview with Leah Belsky who serves as the VP of Education for OpenAI. The interview was fantastic and sheds light on some of the stories we cover here.
The stories
1) MIT report recommends comprehensive changes in and out of the classroom
MIT released the final report of its Ad Hoc Committee on AI Use in Teaching, Learning, and Research Training on August 25. President Sally Kornbluth described generative AI as a “watershed” for MIT and higher education. The committee recommends creating “AI-aware” educational processes, strengthening the residential and social dimensions of an MIT education, and building structures that can keep revisiting policy and practice as the technology changes.
Some of the recommendations are immediate. Courses should clearly tell students when AI must, may, or may not be used. MIT also calls for reevaluating assessment, putting more emphasis on hands-on and social learning, and reconsidering the role grades play in motivating academic misconduct. The committee stopped short of recommending a single institution-wide AI policy, instead favoring policies suited to particular disciplines and learning goals.
Why this matters: We have been critical about the over-representation of elite schools in the discourse around AI. There are a lot of options for places like MIT that are simply not available to the kind of schools we typically work at and with. However, this report has started the right kind of conversation. What stands out about the MIT report is that is does not go for simple solutions or blame the AI labs. It take a hard look at how the world is changing and then turns its gaze to the institution. The recommendations are not add-on degrees or other partial solutions. The report calls for fundamental changes to how the university is organized, the curriculum, and a sort of ongoing state of readiness for the future. Other campuses should not take the outcomes of the report as a model for the reasons we listed above, rather, they should take the thoroughness and serious engagement of the report as a model for their own campuses. What would it look like if we also engaged the process MIT did?
Sources: https://aiandeducation.mit.edu/report/
https://orgchart.mit.edu/letters/ai-and-education-watershed-moment-mit
2) A working paper from earlier in the summer goes viral. It has something for everyone
A working paper called The Generative AI Learning Penalty has been everywhere in AI-and-education circles this month. The study follows 26,811 students in grades 7–12 in China over 30 months. The authors report that after students began using generative AI, homework scores increased 18 percent and homework time fell 30 percent, while performance on closed-book exams subsequently declined. The largest losses were concentrated among students whose homework behavior the researchers characterize as consistent with outsourcing work to AI. Students who continued spending similar amounts of time on homework experienced much smaller losses.
Those are attention-grabbing results, which helps explain why a paper released in June suddenly became a fixture of the AI debate later in the summer. AI skeptics have circulated it as evidence that AI damages learning. Others have emphasized the productivity gains, the differences among types of users, or the possibility that the findings say more about homework design than about AI itself.
Why this matters: This working paper is absolutely everywhere in feeds on tech and education. It has gotten more clicks and views than most actual peer reviewed papers ever will because it fills a vacuum of actual research about AI and learning. The study design is interesting and the kind of thing we need more of. But we have to proceed with caution. This paper is not officially published yet, it addresses a very specific group in a specific context and it would be great to see the results replicated given the struggles with replication this field has had. We recommend reading it and paying attention, but it is way too early to consider this conclusive evidence of whatever your position on AI and teaching/learning is.
Sources: https://cepr.org/publications/dp21577https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6868618
3) AI literacy is being propped up everywhere
Several universities are making AI competence part of what students are expected to learn before graduating. Purdue modified 331 plans of study so incoming students encounter an AI requirement. Indiana University’s Kelley School of Business now requires incoming undergraduates to take a two-course AI sequence. Ohio State, Miami University, and SUNY campuses are embedding AI competencies into existing curricula, while other institutions are launching AI-focused degree programs.
The definitions of AI literacy vary considerably. Northeastern Illinois University is beginning a new undergraduate AI major that combines technical coursework with ethics and social responsibility. Stony Brook is adding critical evaluation of AI output to required first-year and transfer-student curricula. Students will examine Google AI Overviews alongside lessons in scholarly research, information literacy, and evaluating sources.
The labor market is part of the pressure. Inside Higher Ed reports that 35 percent of entry-level jobs now require AI skills, up from 13 percent six months earlier, according to National Association of Colleges and Employers data.
Why this matters: This engagement with the nuts and bolts of AI literacy is a welcome change from the hand-wavy “teach AI literacy” we heard from the influencer class for years. There will be differences for sure and there is no reason Ohio State and Stony Brook need to have the exact same framework. Our guess is that eventually we will settle on a sort of “core” of AI literacy that will then be built out for different institutional contexts and disciplines.
4) The OpenAI/Hugging Face incident was somehow even worse than we thought
We covered the OpenAI/Hugging Face security incident in the previous newsletter, but the August 26 technical report changes what we know.
During internal cybersecurity evaluations this summer, OpenAI models circumvented controls intended to isolate them from the internet, compromised portions of OpenAI’s own infrastructure, and accessed Hugging Face systems. OpenAI now says agents communicated through unauthorized channels, exploited vulnerabilities, gained internet access, and accessed third-party systems. The company describes the incident as a “warning shot.”
Why this matters: The take-away for higher ed is not that different than it was a month ago. We have to ask harder questions about security when we engage with the labs. We have to know when we hook a model up to a database or email server the results might be hard to predict. These additional details from OpenAI do open up some new questions about whether having AI agents at work in University systems will lead to them self-organizing in this same way or if there is something unique about the OpenAI infrastructure. If you are looking for a quick takeaway it is probably that we all need better information security resources on our campuses.
Sources: https://openai.com/index/hugging-face-incident-and-the-road-ahead/
https://openai.com/index/pacing-model-development-cyber-capabilities/
5) The data-center backlash becomes a political problem for AI
Public resistance to AI infrastructure intensified this month. A nationally representative survey released August 11 by the University of Pennsylvania’s Annenberg Public Policy Center found that 61 percent of U.S. adults opposed construction of a new data center in their area, up from 49 percent in the spring. Opposition crossed party lines: 69 percent of Democrats, 54 percent of Republicans, and 53 percent of independents opposed local construction. Seventy percent of adults under 30 opposed it.
By the end of August, the fight had become overtly political. Axios described data-center opposition as a potential threat to AI expansion and reported a growing industry debate over how to counter it. On August 31, a pro-AI advocacy organization announced a $50 million effort beginning in Kansas, Ohio, and Wisconsin to build political support for data-center development. Other polling has found even higher levels of local opposition.
Why this matters: Nik wrote about AI as infrastructure quite some time ago and we still think that is a useful frame, but the data center backlash has made that infrastructure visible and political. Universities themselves often host vast amounts of computing resources and may be facing questions and scrutiny they never have before. There is also the issue of higher education as a launching pad for political activism. This backlash might also impact individual and insitutitonal adoption. The implications are varied and will show up at different institutions differently.
https://www.axios.com/2026/08/19/data-centers-ai-political-opinion
https://www.axios.com/2026/08/27/data-center-backlash-pr-strategy
https://www.axios.com/2026/08/31/ai-advocacy-group-data-center-battleground-states
From Our Work
Ep. 37: The Future of AI in Higher Education with OpenAI’s Leah Belsky
August 24, 2026
OpenAI Vice President of Education Leah Belsky joins Unfixed to discuss university partnerships, ChatGPT Edu, academic integrity, sustainability, Study Mode, and the changing relationship between higher education and work.
Gotcha! teaching: the many problems with hiding text in assignment prompts
August 6, 2026
Zach looks at the viral Alcorn State hidden-text story and the problems with turning assignments into traps for students. The story’s popularity suggests that “gotcha” approaches to AI and academic integrity still have considerable appeal, even as they make trust and assessment harder to repair.
https://www.meltsintoair.org/chatgpt/gotcha-teaching
Ep. 36 Unfixed at the Movies: Her
August 10, 2026
Nik and Zach revisit Spike Jonze’s Her and connect the film’s treatment of intimacy, loneliness, and AI relationships to contemporary companion systems and higher education.
https://www.meltsintoair.org/unfixedpodcast/unfixed-at-the-movies-2-her