Though half a century ago, still, the demonstration resonates now. Today, it may seem to many that the cluster of technologies marketed as \u201cAI\u201d is entirely new, and, logically, that objection to it must likewise be unheard-of. But, as the demonstration shows, not only is \u201cAI\u201d not especially new; protesting it has a long history. Inspired by the collective objection represented in this photo<\/a>, we are calling for resistance to the AI industry\u2019s ongoing capture of higher education.<\/p>\n We envision a resistance that is, by its very nature, a repudiation of the efficiencies that automated algorithmic education falsely promises: a resistance comprising the collective force of small acts of friction.<\/p>\n\n There are key differences between the 1971 protest and the growing resistance to AI today. Back then, advanced computational development was directed explicitly toward military purposes. When this research had to pass through university infrastructures, the violence of its purpose was easy to see. And this, in turn, made the potential targets of resistance clear; indeed, it was relatively easy to organize protests in front of large mainframe computers, located in very specific facilities and locations. Now, however, computation is distributed. And this makes the targets to resist so diffuse that the shape of direct action becomes difficult even to conceptualize.<\/p>\n Another difference is who is directing the violence. Once, universities saw their computational power exploited by researchers working for the Department of Defense. Today, universities are being infiltrated by a commercial industry (albeit one that receives a staggering amount of money from defense contracts) that exploits students and faculty as data mines, test subjects, and a perpetual supply depot of future users, all for their own profit.<\/p>\n Universities have accepted the overtures from this industry in a FOMO-driven frenzy without consulting their faculty, collecting empirical data on whether generative AI is pedagogically useful, or pausing to inquire about the long-term impact of AI on the students who have been entrusted to their care. Faculty are at best being coerced\u2014and at worst being forced\u2014to employ generative AI in their teaching, assessment, or advising. Moreover, with the educational mission that they thought they were signing up for undermined, students have no option to resist.<\/p>\n In other words, we have all been left on our own to jury rig workable pedagogical scaffolds while the educational edifice is being bulldozed around us. Individual responses will not suffice; collective action is necessary.<\/p>\n The photograph shows us a moment when students and some faculty resisted the co-optation of university resources in the service of the Department of Defense\u2019s war machine operating thousands of miles away. It was a moment in which human bodies and minds came into conflict: chants were yelled, rocks were thrown, the son of one faculty member was shot, twelve individuals were arrested, and a tenured faculty member fired.<\/p>\n Resistance in 2025, however, demands collective action across a much broader spectrum. The AAUP has released a report<\/a> with a set of excellent recommendations, which we commend. Others have begun making public pledges<\/a> disavowing the use of AI in their classrooms, and we support such endeavors as well.<\/p>\n To these measures, however, we call for even more.<\/p>\n Grandiose promises that technology will improve education are nothing new. Such promises have been a refrain for decades. It is remarkable how little they have changed and how consistently they have failed to deliver. A recent interview with Sal Khan quotes the founder <\/a>and CEO of Khan Academy as imagining the use of \u201cAI teaching assistants \u2026 able to help children when needed and \u2018report back to the teacher.\u2019\u201d For someone allegedly so invested in the future, Khan sounds uncannily like the past. In 1954, the behaviorist B. F. Skinner was promoting his \u201cteaching machines,\u201d writing<\/a>, \u201cIf the teacher is to take advantage of recent advances in the study of learning, she must have the help of mechanical devices.\u201d As Audrey Watters has written in Teaching Machines<\/em><\/a>, \u201cWhat today\u2019s technology-oriented education reformers claim is a new idea\u2014\u2018personalized learning\u2019\u2014that was unattainable if not unimaginable until recent advances in computing and data analysis has actually been the goal of technology-oriented education reformers for almost a century.\u201d And, as Watters shows, similar to the protesters at Stanford, students at the Ohio State University in the 1930s rejected\u2014derided, really\u2014such proposals. Langdon Winner accuses<\/a> educators who fall prey to the blandishments of ed-tech boosters of a \u201cwillingness to forget\u201d that \u201cthere is scant evidence during the decades from Edison to the present day that any of the heavily touted varieties of equipment introduced into schools and colleges over the years has done much to improve education at all.\u201d<\/p>\n In the techno-utopian scenario, generative AI can essentially teach undergraduates many foundational skills. Even elite institutions like the University of Chicago are seriously entertaining the idea that their students will be \u201ctaught\u201d foreign languages by ChatGPT<\/a>. And by now there is a cottage industry<\/a> of essays<\/a> on how teaching college writing<\/a> has been rendered superfluous in the wake of generative AI. Some of these essays betray an exhausted resignation, while others seek to find promise in the incorporation of AI into the college classroom. In different ways, though, both resignation and optimism suggest that the co-optation of education by this technology is inevitable. It is, in some ways, writing as therapy: an effort to maintain contact with the terrain that is shifting under the author\u2019s feet. There\u2019s value in that, but we are not writing for therapy; we are writing for change.<\/p>\n We write from the perspective of 2025. But we also write as historians looking back at a lineage of educators and students who have resisted the incursions of technosolutionism, technocapitalism, and technofascism in higher education. As such, we warn of the possible consequences of inaction; and we hope that action will shape a future for higher education that defends students and faculty\u2019s humanity.<\/p>\n Time and again we have been told that a dire educational crisis demands technological solutions that will improve learning outcomes. So, our question is: Why are we doing this again? What is the crisis? Where is it located? Teaching? Learning? Or society more broadly?<\/p>\n This short essay is not the place for a full diagnosis. Still, we cannot hold this conversation without recognizing that, since the 1980s, state and federal governments have divested from education. Efforts have been made to plug these funding holes with public-private partnerships, bringing into schools technology firms, other industries, and private philanthropy. Yet all these investments have been accompanied, crucially, by a corrosive cultural argument: that public expenditure on education was a wasteful extravagance, anyway, one that can be cleaned up by a new model of technologically led pedagogy.<\/p>\n It is in this context that we must consider the newfound praise of AI in education. AI boosters promise that the technology will find greater efficiencies in education; but this is less about the functionalities of AI itself, and far more about eviscerating the public nature of public education. As the ceaseless ed-tech boom-and-bust cycle of the last century has repeatedly shown, efficiencies are easy to promise, but difficult to realize in the stubbornly human-centered endeavor of education. And that is because education is, by necessity, inefficient. learning is the result of human grappling with the parts of the world that resist us and our capacity to understand.<\/p>\n<\/blockquote>\n<\/figure>\n Within this context, professors and administrators may be tempted to see technology companies as a life raft. Adopting AI, this argument goes, might save professors some time or energy.<\/p>\n Such a temptation must be rejected. Higher ed must, instead, ask the same question Marc Watkins has proposed for secondary education: Who owns the A.I. dividend<\/a>? Technology firms see the university as a gigantic data farm; they are not invested in our students or the learning process, only in harvesting the attention of an entire generation of users, who will be addicted to their product for the rest of their adult lives.<\/p>\n Even worse, these students will be subjected to brutal calculations\u2014based on the data stolen from them in college\u2014to determine their worthiness for job interviews, the validity of insurance claims, or eligibility for parole.<\/p>\n Why, after all, has a consensus so quickly emerged that we have a crisis in teaching<\/em>? Is this not more rightly described as a crisis in learning<\/em>? Or, more aptly, as an attack <\/em>on learning?<\/p>\n Most fundamentally, we believe that learning is the result of human grappling with the parts of the world that resist us and our capacity to understand. This conception of education is antithetical to the transactional and antihuman program of \u201coptimized\u201d and \u201cefficient\u201d delivery of learning outcomes, promised by proponents of AI\u2019s incursion into the space of education.<\/p>\n The most thrilling moments for us as educators come when we see the glint and sparkle of a student having an illumination: anything from finding the best articulation of an idea or making connections between seemingly disparate bodies of knowledge. Those moments underline for us that learning is ultimately a process, and one that is predicated on friction and struggle. Anyone who has taught will have had the experience of watching a student struggle with a complex concept or piece of evidence. Ideas are slippery things, and grasping them more than fleetingly is a challenge. This is the result of epistemological friction, of rubbing our ideas against a world that is recalcitrant and full of other agents who see it differently. At its best, education is similar to C. S. Peirce\u2019s definition, in \u201cThe Fixation of Belief<\/a>,\u201d of inquiry as the \u201cirritation of doubt [which] causes a struggle to attain a state of belief.\u201d That is, we believe, a pretty concise summation of the purpose of higher education: to lead students from doubt into knowledge.<\/p>\n Learning is not a problem to be solved; it\u2019s a process to be undertaken. There are students who feel that they are being robbed<\/a> of an educational experience, because AI has fundamentally shifted the culture of education. Not only do their fellow students seem more apt to use ChatGPT as a \u201cstudy buddy,\u201d they also worry that the faculty are using AI to offer perfunctory assessments of their work. To those students, we say: we see you and we validate your sense of frustration. We teach to you, and we hope that you will learn with us.<\/p>\n And so, we write here as a call to action. We hope that other educators will join us in helping students and professors to pave an exit ramp off the alienating highway of automated education, and we aspire to achieve this in community, rather than as solitary prompt engineers.<\/p>\n![\"\"](\"https:\/\/www.publicbooks.org\/wp-content\/uploads\/2025\/10\/mitchell-luo-gQtUcKahZoQ-unsplash-1000x600.jpg\")
<\/a> <\/figure>\n <\/div>\n\n \n Toward the Next American University: A Roundtable Discussion on the Future of Higher Ed<\/a>\n <\/h5>\n\n
![\"\"](\"https:\/\/www.publicbooks.org\/wp-content\/uploads\/2024\/10\/Dennis-Hogan_dsc8735_Patrick-Montero-1-300x300.jpg\")
<\/a>\n \n Dennis M. Hogan <\/a>\n <\/div>\n \n <\/div>\n <\/div>\n <\/div>\n\n \nA Brief History of Technosolutionism in Teaching<\/h4>\n
A Crisis in Teaching, Or a Crisis in Learning?<\/h4>\n
\n<\/p>\n\n
\nTrump\u2019s federal budget, passed on July 4, 2025, transfers the largest amount of wealth upward from poor to rich ever in the country\u2019s history. In addition, the budget continues in the trend of defunding education in favor of massive tax cuts for the rich and budget infusions for a national anti-immigrant police force. Clearly, in the near term, we cannot rely on a simple reinvestment in public education.<\/p>\n
\nAI ISN\u2019T EDUCATION<\/h4>\n
Centering Humanity through Small Acts of Friction<\/h4>\n