Puutio took a different approach than outlawing the instruments that made it. He now mandates that students use AI in all of their assignments. This decision, which he described in an essay for Business Insider in March 2026, is based on a set of guidelines intended to do something that most university AI policies aren’t yet capable of: differentiate between AI that does the thinking and AI that supports the thinking.

The distinction seems straightforward. In reality, it is the whole issue. Undergraduate students at Harvard are as aware of this as their professors are, and in some ways, they have been more openly dealing with its complexity. Developed through interviews with seven faculty members and 27 HGSE graduate students, a guide released by the Harvard Graduate School of Education in January 2025 paints a picture of students who are considering AI in ways that aren’t always reflected in institution-wide policy documents. These students aren’t attempting to get away with anything. They are students who have already incorporated AI into their work processes and are now, quite understandably, requesting that their teachers catch up.

Even though it seems hard to deliver, what they want is not complicated. Instead of the ambiguous language about “responsible experimentation,” which Harvard’s general AI policy currently offers, they want explicit policies that specify exactly what constitutes authorized use in each course. Instead, they want actual guidance from the instructor who is grading their work. Professor Karen Brennan, who co-wrote the guide and oversees the Creative Computing Lab at HGSE, compares the fear surrounding AI to the “moral panic” that followed the development of the pocket calculator. This fear proved to be partially justified, partially misguided, and primarily resolvable through careful integration rather than outright prohibition. Similar statements were made by the students in her study. When instructors explained why they were assigning a certain task, they said it was actually helpful because it made it easier for them to decide what to give to AI and what to keep for themselves.

The HGSE guide quotes a student who said, “Really think about what you want at this moment,” which seems to have more wisdom than most institutional policy statements. Do you want to learn or just finish the task at hand? Perhaps that question ought to be at the top of every American course syllabus at the moment. The students who are inquiring are aware of the limitations of AI. They cautioned one another about the challenging learning curve, the need for several rounds of quick refinement to produce meaningful results, and the moment one student, six hours into a session that should have taken two, realized that sometimes using your own skills is just more efficient than battling the machine.

One example of this in action is the framework Puutio employs in his own classroom. AI for research and synthesis, AI as an editor and critic once the argument has been developed, but never AI creating the argument itself. The student must be the one who thinks. When that line is clearly drawn, the assignment’s nature is altered without giving up on technology. It’s difficult to ignore how different that is from the binary decisions that the majority of universities continue to make: either completely prohibit it or say nothing helpful and hope for the best.

Fundamentally, what Harvard students are requesting is honesty. They are aware of the existence of AI. Regardless of policy, the majority of them use it in every course. They want academics who are prepared to confront this reality head-on, not act as though it will disappear or treat every discussion of AI as a disciplinary issue, but rather sit with the true complexity of a technology that, depending on how it is applied, can either enhance or detract from learning. This is already being figured out by the students. Whether their institutions will advance fast enough to be beneficial is the question.

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Students, trainees, and apprentices have the opportunity to test their skills in competitions that are in line with WorldSkills international standards thanks to Skills Competition Wales, which is supported by the Welsh Government and offered through a network of colleges and work-based learning providers throughout the nation. The competitions have been going on for years, but something about their recent trajectory suggests the program has found a second gear. This includes the participants’ direct advancement into higher education, the aspirations of the students they are producing, and the expansion of disciplines in 2026 to include Textiles and Surface Pattern, Ceramics, and Sustainable Agriculture.

Ellie Vaughan, a Swansea native, was introduced to UWTSD through the competition prior to her official enrollment. She had finished her Foundation Year in Art and Design at Gower College Swansea, and the competition provided her with access to the resources and educational setting that she would eventually decide to pursue. Before she arrived, she was aware of the live briefs, the international travel, and the studio spaces. That is not a minor issue. The discrepancy between what universities describe in their prospectuses and what students actually find when they arrive is one of the recurring problems in higher education recruitment. Honestly and practically, the competition closes that gap.

Eva Kingston-Gharaati recounts a similar tale, pointing out that the briefs she was given at UWTSD were sufficiently expansive to permit real experimentation while still requiring in-depth investigation of global artists and designers. This combination of freedom and rigor is more difficult to attain in a curriculum than it may seem, and it indicates a deliberate aspect of the programs’ design. Another competition pathway alumna, Thea Wakeford, went one step further and, with university support, started a small business in addition to her studies. This is either an early indication of an exceptionally entrepreneurial student or proof that her surroundings made it seem reasonable to try. Most likely both.

The competition program is framed by Dr. Mark Cocks, Dean of UWTSD’s Wales Institute of Science and Art, in terms of confidence and access, two things that are often lacking for students making the transition from further education to university, especially those who are the first in their family to consider it. Institutional leaders frequently use the term “widening access” in ways that are stubbornly abstract. The pathway is made tangible, repeatable, and concrete by the Skills Competition Wales model. As competitors, students enter the studio once. A few of them choose to return as students. It appears that some emerge as professionals.

Here, the larger context is important. It is easy for outsiders to underestimate the consistency with which Wales has been developing its infrastructure for creative education. For many years, the Creative Learning Through the Arts program of the Arts Council of Wales has assisted schools in creating innovative approaches to curriculum design, integrating artistic practice into subjects ranging from citizenship to mathematics. The Welsh Government’s Future Wales 2025 initiative, a collaboration between Pact and Creative Wales, is expanding that reach into new creative sectors and the screen industry. These are not stand-alone projects. Wales seems to have been putting together something cohesive in the field of creative education, albeit slowly, quietly, and increasingly successfully.

It’s still unclear if students enrolled in the Skills Competition Wales pathway will compete at the top international levels or if the program’s goals will expand beyond its current scope to include all of Wales’ colleges. Something is clearly working, as evidenced by the Swansea studios and the students’ own accounts of how they got there.

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The course, which has been offered at Montclair State since 2012, started out as a direct reaction to an unsettling finding in American educational statistics. A seminal study conducted in 2010 found that children’s creative thinking test scores had been steadily declining for the previous twenty years. The results were quiet in the same way that some uncomfortable facts are often quiet; they were acknowledged, briefly mentioned, and then mainly ignored while academic institutions continued to teach in the same manner. Montclair State took a different approach. It created a course centered on the issue and asked a few genuinely unlikely partners to teach it together.

Professor of physics Ashuwin Vaidya, who led sessions in 2012 and 2014 and contributed to the curriculum’s development, talks about wanting students to think and ask questions independently rather than just absorb information. That seems simple until you consider how infrequently it occurs in a traditional lecture hall, where the room’s layout—rows of seats facing a single speaker—has been subtly arguing the same point about authority and knowledge transfer for 200 years. That architecture is upended by the Creative Thinking course. Professors and visiting artists are added to the curriculum. The next day, students sit in the same room as the artists and ask questions after attending rehearsals for performances by visiting choreographers. Liz Queler, a Grammy-nominated singer-songwriter, stopped by and talked about her process. In 2013, musician and performer Laurie Anderson shared her thoughts on creativity. These are not guest lectures added to an already-existing curriculum. They are the framework.

Mika Munakata, a math professor, asked students to draw parallels between math and a dance performance by the Brazilian group Companhia Urbana de Dança. Her goal was to help students see mathematics as a means of observing pattern, proportion, and movement in the world rather than as an end in and of itself. Kirk McDermid, a philosophy professor, describes creativity in terms of exploration, making it clear that this process is dangerous, prone to failure, and difficult to measure. Just this recognition distinguishes the course from the majority of university programs, where the grading system tends to subtly discourage the kind of unrestricted intellectual risk-taking that results in truly novel ideas.

Reading about this course and the faculty’s descriptions of their own teaching experiences gives me the impression that modeling is more crucial than actual instruction. By working with individuals who have different perspectives, venturing outside of their fields, and letting their students witness their uncertainty, the professors themselves are taking chances. In higher education, where expertise is frequently performed as confidence and admitting ignorance can feel costly from a professional standpoint, that is less common than it should be.

It is worthwhile to trace the intellectual lineage that runs beneath the course. Paul Baker, a 1950s educator and artist whose curriculum thinking was decades ahead of most current discussions about interdisciplinary learning, planted the seed. Furthermore, the link to Matthew Lipman’s Philosophy for Children program at Montclair State College—where Australian philosopher Philip Cam received his training and went on to create inquiry-based teaching strategies that are currently employed in classrooms throughout several nations—indicates that Montclair has been quietly considering how to teach thinking for a longer period of time than the current discourse tends to recognize.

It’s still unclear if the Creative Thinking course can be replicated on a large scale or if it requires a certain mix of institutional support, willing faculty, and the unique creative energy that seems to congregate around programs that have found their purpose. The idea that a student who learns to view a tree through the simultaneous lenses of language, mathematics, dance, philosophy, and science has gained knowledge that no single discipline, taught in isolation, could have imparted seems more difficult to dispute.

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The physical division between the arts wing and the science corridor is intentional. It reveals a deeper aspect of the way American schools have been set up for many years and how they have subtly taught pupils how to organize themselves. You may or may not be a STEM person. You are either analytical or creative. Students are affected for years after they graduate from school, and the categories solidify early.

Ashley Labodda, a Ph.D. candidate in philosophy at the University of Rochester with a degree in biochemistry, has witnessed this unfold in real time from both sides for years. As a teaching assistant for ethics and chemistry classes, she has witnessed biology majors enter introductory philosophy classes believing they will fail before they have written a single sentence. She has witnessed journalism students approach a logic course, which is offered as a substitute for a math requirement, with the express purpose of identifying the least mathematical option. The defeatism is not sporadic. According to her observations, it is persistent, pervasive, and subtly harmful.

Teachers have long been aware of what Labodda describes, but they have struggled to institutionally address it. The documented history of the STEM-humanities divide dates at least to 1959, when British scientist and novelist C.P. Snow published The Two Cultures and the Scientific Revolution, cautioning that the humanities and sciences were becoming so dissimilar that they could no longer meaningfully communicate with one another. This seemed risky to Snow. The argument is still very much relevant sixty-six years later, and the school day schedule has changed remarkably little in response to it.

As a workable solution to this issue, the STEAM movement—the intentional addition of Arts to the STEM acronym—has been gaining traction for years. According to the Institute for Arts Integration and STEAM, it uses science, technology, engineering, the arts, and mathematics as interconnected access points for directing student inquiry rather than being a straightforward combination of subjects. The difference is important. A biology lesson followed by a drawing exercise is not what STEAM is all about. In this type of project-based, interdisciplinary learning, students must simultaneously comprehend engineering principles and aesthetic choices when designing a structure; data visualization necessitates both mathematical literacy and true design thinking; and the question under investigation cannot be resolved by a single discipline.

Nyiramukama Diana Kashaka of Kampala International University conducted research in October 2024 that looked at the historical connection between STEM and arts education and consistently found evidence that integrating artistic processes into scientific learning enhances student motivation, engagement, and creative thinking. Anyone who has witnessed a student come to life in a project that required them to use more of their brain simultaneously will not be surprised by the findings. The institutional machinery’s slow reaction to that evidence is a little more startling.

As the STEAM discourse spreads throughout university departments and school districts, there’s a sense that the true challenge was cultural rather than pedagogical. Standardized testing, tracking systems, college admissions pressures, and career counseling that reduces the diversity of human potential to a single employability metric all contribute to the deeply ingrained belief in American education that a serious student chooses a lane and stays in it. Labodda compares general skills, such as critical thinking, problem-solving, and the capacity to formulate and evaluate an argument, to a tool belt, with specific skills serving as the tools. She contends that when students are asked to use their tools in unfamiliar situations, across the divide rather than safely within one side of it, that belt becomes stronger.

It’s still unclear if schools that sincerely commit to STEAM integration are creating something long-lasting or if the term will be absorbed into current structures with little to no underlying change. With regard to education reform, that has previously occurred. However, when a student who described herself as “completely STEM-brained” finds that writing a rigorous argument and testing a hypothesis require more of the same thinking than she anticipated, something truly changes in the classrooms where it is actually working. It turns out that the gap is smaller than claimed. It was always the case.

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It doesn’t appear dramatic. After a macroeconomics lecture, a Chicago college sophomore opens ChatGPT and asks it to explain the same idea from the perspective of her grandmother’s Guadalajara small business. An AI is asked to suggest books that cover the same literary themes but truly represent his world by a junior in high school in Atlanta who is dissatisfied with a set reading list. Using a language model, a Boston graduate student condenses a 400-page reading list into a series of focused questions, which he then uses to delve deeper than the syllabus ever required. To be precise, none of them are cheating. However, none of them are also adhering to the script.

Houman Harouni, a former classroom teacher and Harvard Graduate School of Education lecturer, has been observing this change for a longer period of time than most. It doesn’t completely frighten him. He is more concerned about the lack of guidance surrounding the tools than the tools themselves. He has observed that although students are already experimenting on their own, they require assistance in doing so in an ethical manner. According to his framing, the educator’s role is to recognize the opportunities that still exist in addition to technology, not to act as though it doesn’t exist.

Compared to what the majority of school administrators are currently providing, that framing seems more truthful. Institutions have traditionally banned AI tools, used plagiarism detection software, and hoped the issue would go away on its own. Dr. Dorottya Sallai and her colleagues at the London School of Economics adopted an alternative strategy by actually observing what students were doing. They discovered something unsettling but not unexpected among 220 students enrolled in seven courses: students were primarily using generative AI to manage workloads rather than necessarily to deepen understanding. They were creating first drafts, summarizing readings, and completing conceptual gaps. In other words, they were managing a system that had not yet adapted to their environment.

The irony in this situation is difficult to ignore. For the remainder of their careers, the same students who are being punished for using AI will be expected to collaborate with it, oversee it, and engage in critical thought. The curriculum, which was developed during a time when knowledge was hard to come by and access to specialists was restricted, has not kept up with the ability of a student in rural Mississippi to ask an AI to mimic a Harvard lecture. For institutions whose power has always rested, at least in part, on controlling what is taught and how, this democratization of access is genuinely significant and unsettling.

Beneath all of this is a deeper question that is rarely posed directly. The curriculum has never been an impartial document. It has always represented decisions about what knowledge is important, whose knowledge is important, and what kind of person graduates are expected to become. Students are not merely being efficient when they hack that curriculum, asking AI to reveal indigenous knowledge systems that their textbook overlooked or to explain the same scientific concept from five different cultural frameworks. They are debating legitimacy. Sometimes what appears to be academic laziness is actually more akin to intellectual self-defense.

This does not imply that all AI-assisted shortcuts are justifiable. Students who turn in AI-generated work that they haven’t really thought through aren’t actually changing their education; they’re just avoiding it. The distinction is important, and neither outright prohibitions nor unquestioning acceptance are able to make a strong impression. The most sincere educators appear to be those who choose to sit with the ambiguity instead of making hasty decisions.

Observing all of this, it is most evident that the students who are most thoughtfully utilizing AI are not taking the place of their critical thinking. They are the ones who use AI to determine what they genuinely want to think about, and then they go beyond what any standardized curriculum would have allowed. Education is not in danger because of that. Perhaps this is what education was meant to be.

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The figures underlying that discomfort are not conjectural. According to the International Civil Aviation Organization, the aviation sector will require an extra 2.5 million workers worldwide by the early 2040s. GE Aerospace, which employs about 13,000 people in 18 countries in Europe alone, has found that vacancy rates for important engineering and technical positions can reach 20% in some areas of the industry. By 2044, Airbus projects that a total of 2.35 million new aerospace professionals will be required. Doing the math is not difficult. The more difficult question is how the industry develops those individuals rather than just hoping they show up, and where they come from.

A loose network of apprenticeship programs, university partnerships, reskilling academies, and early outreach initiatives that are all attempting to accomplish essentially the same goal from various perspectives is starting to take shape and could be referred to as the aerospace educational pipeline. One of the more comprehensive depictions of this in action is provided by GE Aerospace’s methodology.

Louise Collins was named Scotland’s Apprentice of the Year in 2025 thanks to the company’s apprenticeship program with Ayrshire College in Scotland, which pairs students directly with seasoned technicians maintaining cutting-edge jet engines. For those who might not have thought of a career in aerospace, Poland’s XEOS Academy, a joint venture between GE Aerospace and Lufthansa Technik, offers a structured pathway. Pawel Wika, one of its graduates, worked in corporate settings for twenty years before the Academy assisted him in retraining to become a certified aircraft engine technician in his forties. His perspective is straightforward: learning something new is never too late.

It is simple to write off such a story as anecdotal, but it contains a structurally significant element. For a considerable amount of time, the aerospace industry has been fishing in a relatively small pool of recent engineering graduates from a limited number of universities, the majority of whom are men. It became evident from the discussion at the 2025 RAeS President’s Conference in London that this strategy is not functioning at the necessary scale. Only 6.2% of flight deck positions are held by women, according to IATA data, a slow increase from 4.6% in 2021. EasyJet received 2,000 pilot job applications overnight as a result of two female pilots posting on TikTok. From that, the industry is making inferences. Draw them slowly.

With these figures, there’s a sense that the aerospace industry is coming to a fairly obvious realization a little later than it should have. As Sophie Jones of the CAA noted at the conference, young people’s career interests are formed by the time they are five years old. However, the majority of industry outreach has traditionally been directed at college students who have already made their decisions. Nowadays, primary schools are being considered as serious engagement targets rather than merely courteous gestures. The issue of whether the approximately 140 aviation and aerospace charities in the UK need to work together to create something more cohesive, or if individual company visits are sufficient, is also now openly discussed.

Whether these initiatives will close the gap before the retirements hit hardest is still up in the air. Even though the apprenticeship route is becoming more and more popular, there is a real bottleneck: easyJet, for example, currently has no problem finding candidates for apprenticeships but is unable to locate training providers with sufficient capacity to accept them. The aerospace design students at Cranfield University are now questioning cockpit norms; last year’s cohort created a wheelchair-accessible airliner cockpit, which reveals an intriguing trend in the instincts of the next generation. They don’t want to spend a lot of time in a field that doesn’t represent who they are.

To put it simply, the pipeline is being built in real time with genuine urgency and inconsistent results. The establishments exist. The number of programs is increasing. The next ten years will determine whether the industry can scale them quickly enough and whether it can actually open its doors to the diverse range of people it now sorely needs.

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Although the question of whether MFA and creative writing programs are limiting British fiction is not new, it has become much more acute as these programs have grown in number. Ian McEwan and Kazuo Ishiguro received their training at the University of East Anglia, which used to be somewhat of an outlier in the British university system. Numerous universities across the nation now offer postgraduate programs in creative writing, each of which uses a unique workshop model that was mostly imported from American universities like Iowa. Critics and authors alike are increasingly concerned that this model subtly encourages one type of story while discouraging another.

This conversation frequently refers to the “MFA voice.” It characterizes writing that is technically sound (clean prose, controlled point of view, emotionally readable scenes) but inert in some way. Tales that seem processed. sentences that have been modified to make them safer. The workshop setting, which is based on peer review, seems to erode the unfamiliar edges of a writer’s intuition. Confusion is the result of experimentation. Density is referred to as inaccessibility. Critics contend that this leads to fiction that is simpler to defend in a seminar than it is to recall six months after reading.

The programs themselves might not be the true motivator in this case, but rather their surroundings. The MFA community and British publishing are not wholly distinct ecosystems. Many editors and agents attend the same festivals, go through the same schools, and are familiar with the same professors. The loop tightens in ways that are difficult to see from within when a workshop teaches students to write toward what is publishable, which is partially defined by those who share the workshop’s aesthetic. Writing with the market in mind is nothing new, but having an institutional framework that codifies this inclination is.

However, the case against homogenization is strong, and it would be unjust to reject it too soon. For authors without the social ties that have traditionally fueled British literary culture, MFA programs have provided avenues for publication. Particularly, Goldsmiths has been linked to formally adventurous fiction, which purposefully defies the polish-and-submit paradigm. Finding program graduates whose novels are truly bizarre, genre-defying, or structurally restless is not difficult. Supporters are correct when they claim that the criticism occasionally confuses the publishing industry’s transgressions with those of the curriculum.

The fact that the majority of classic British authors of the 20th century, including Penelope Fitzgerald, Muriel Spark, and Graham Greene, developed outside of any kind of workshop structure is still worth considering. They never presented their formal risks, eccentricities, or tonal quirks to a group of twelve peers using rubrics. It’s difficult to ignore the fact that those writers’ textures seem, in some way, less negotiated, even though it’s unclear whether the lack of institutional shaping resulted in better literature. less polished.

Fundamentally, the homogenization debate is about what literature loses when it turns into a field of study with measurable results. Most likely, craft can be taught. The voice is more difficult. Furthermore, the kind of literary carelessness that results in a truly original sentence may be subtly incompatible with the institutional pressure to produce work that pleases a committee, even a thoughtful, well-intentioned one. There have always been peculiar aspects to British fiction. It is worthwhile to inquire as to whether the workshop model is contributing to the difficulty in locating those corners.

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The current wave of AI tools is starting to address that exact moment, which is repeated annually in millions of classrooms. By quietly taking on the burden of the work that was never really teaching in the first place, rather than by replacing teachers.

Teachers who use AI tools on a weekly basis report recovering an average of almost six hours per week, according to Gallup data. For six hours. That’s a full workday returned to someone who truly needed it, not a rounding error. Platforms like Gradescope, which manages rubric-based grading with instant feedback, and MagicSchool AI, which provides more than fifty tools for lesson planning, student support, and communication, are doing something subtly important: they’re enabling teachers to once again be teachers.

It’s important to understand what automating the routine in education really entails. It’s not a theoretical increase in efficiency. A third-grade teacher in Ohio used to spend Sunday afternoons creating differentiated worksheets for four reading levels; today, she uses Diffit to create them in a matter of minutes while spending the remainder of the afternoon outside. An AI assistant now manages routine parent communications, saving a Texas high school history teacher from writing the same attendance email for the fifth time in a month. The hours are redirected rather than disappearing.

Perhaps the more intriguing aspect of the story is what educators do with that time that has been reclaimed. Teachers who have embraced these tools are beginning to feel that their professional identities are changing. When lesson plans are created on demand and grading is automated, what’s left is the fundamentally human aspect of the work: the student who seems to be withdrawing lately, the class discussion that, with careful guidance, could go somewhere amazing, and the mentorship relationship that, given enough time, could flourish. The majority of educators are aware that these are things that no algorithm can duplicate.

However, treating this shift as completely simple would be naive. Large-scale dataset-trained AI systems run the risk of embedded bias, which includes assessments that aren’t equally fair to all learner types or content that may subtly favor one cultural context over another. The truth is that neither researchers nor educators have completely figured out what responsible implementation entails. Data privacy is a serious issue, especially when platforms gather information about student performance. These are not justifications for rejecting the tools. They are justifications for using them carefully and judiciously, which is, ironically, precisely what excellent educators have always done.

This historical pattern is noteworthy. It was once thought that mathematical thinking would end with the invention of the calculator. Schools were supposed to become obsolete due to the internet. Each time, the role of the teacher changed rather than vanished, and technology became a tool rather than a substitute. Though the rate of adoption feels different this time around—more urgent, more pervasive, and more thoroughly ingrained in the day-to-day operations of the job—AI appears to be following the same trajectory.

What’s emerging appears to be a collaboration that was perhaps long overdue rather than a competition between humans and machines. A teacher is not being replaced when they can rely on an AI assistant to transcribe a staff meeting, identify a student whose test scores have been steadily dropping for three weeks, and produce a preliminary lesson plan for Thursday. They are being set free. The student in the back row, who hasn’t spoken in a week, caught my attention. liberated to create a project-based learning unit that genuinely engages a group of twelve-year-olds. In other words, liberated to pursue the activity that initially attracted the majority of them to education.

As this develops, it’s difficult to ignore the fact that teaching students may not be the most beneficial use of AI in education. It’s returning the opportunity for educators to serve as mentors. That subtle shift from paperwork to personhood may prove to be the most significant advancement in education in a generation.

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They were advocating for a bilingual creative education partnership, which is the kind of program that links kids to language, art, drama, and music instruction in ways that the standard curriculum, which is increasingly shaped by exam metrics and league table pressures, has methodically squeezed out. It had taken years to develop the program. instructors who supported it. connections with cultural organizations and partner schools. Quietly, there was a waiting list for families who were interested. And now that there are rumors that the partnership that made it possible will be discontinued, the parents have done what West London parents usually do when they believe something worth protecting is in danger. They made plans.

My London’s February 2026 story focused on a named program, a named threat, and a named set of parents, but it is part of a much bigger and more concerning issue. For more than ten years, the creative curriculum has been declining throughout England. Between 2010 and 2024, the percentage of GCSE entries in the arts decreased from 13.4% to 7.1%. Last year, over 40% of English state schools had no students enrolled in GCSE Music or Drama. These are not slight decreases. They are the outcome of a school accountability system that, whether intentionally or unintentionally, rewards narrow academic performance and has made it structurally challenging for head teachers to safeguard creative subjects during tight budgets and impending Ofsted inspections.

Even though they don’t always express it in those terms, the parents fighting in West London are aware of this context. They discuss their kids—the ones who came to life in the art classroom, who gained self-assurance during a performance, and who developed new listening skills when music was taught as more than just extracurricular noise. They discuss how things are changing, and not in a positive way. When parents describe these struggles, there’s a sense that their motivation comes from real concern about what their kids are losing rather than nostalgia for a particular program.

They also have some leverage. The policy response may not accurately reflect public opinion on this issue. According to research done in the summer of 2025, 82% of UK adults, regardless of age, demographics, or political views, think that all children should regularly have access to high-quality creative activities in school. The generation that is currently at the bottom of the state school system, Gen Z, was the most outspoken in stating that their resilience and self-assurance were shaped by their access to the arts in school. In this way, the parents fighting in West London are advocating for the opening of a door that the majority of the nation wants.

Whether the partnership they are defending will endure is still up in the air. Parental campaigns don’t always succeed in overcoming the finality of local authority decisions regarding school program funding, particularly when the numbers being cited and the budgetary pressures are real. However, there is something noteworthy about the campaign itself: the letter-writing, the presence, and the refusal to acknowledge that the choice had already been made before they sat down. It wasn’t by accident that these schools produced the students who are currently pursuing careers in theater, music, film, and design. They arrived because, at some point, someone—a parent, a teacher, or a leader—decided that this was important enough to fight for.

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Due to alleged antisemitism on campus, the Trump administration suspended over $2.2 billion in federal grants to Harvard. Harvard filed a lawsuit. The restoration of funds was mandated by a federal judge. The government filed an appeal. The funds were in legal limbo, and administrators at the Faculty of Arts and Sciences, which houses the humanities, social sciences, and arts, were using spreadsheets to conduct scenario analyses that no one wanted to see. The budget for the arts and humanities alone suffered a direct loss of almost $2 million. The number of PhD admissions in the sciences was reduced to a quarter of what it used to be. Emergency meetings were held by faculty. Suddenly, the organization that had spent decades fostering the notion of intellectual permanence was preparing for unforeseen circumstances.

The $53 billion endowment, which is the largest university endowment in the world, is the number that is always brought up in these situations. It is typically used to support the claim that Harvard should just quit whining and spend its way out of trouble. Almost all of the pertinent information about how the money actually functions is hidden by that figure. Economist John Y. Campbell, who reimagined FAS’s endowment management in 2021 and served on the board of the Harvard Management Company for seven years, has been making this point with meticulous precision. Approximately 80% of the endowment is donor-restricted, which means that it can only be used for the particular uses that each donor has specified, such as building maintenance, financial aid, professorships in specific fields, and specific research areas. Under the direct control of university leadership, less than 5% of the total is truly unrestricted money. It is evident that the $53 billion is not a war chest. According to Campbell, it’s a collection of particular pledges made to particular donors that result in yearly distributions that are already mostly devoted to paying for Harvard’s operating budget, which enables the university to operate at all.

In this context, the arts are especially vulnerable. When institutions are under budgetary pressure, creative programs—visual arts, theater, music, and the humanities that support them all—tend to suffer the most because their worth is more difficult to measure using the metrics that funding agencies, both public and private, typically favor. The Faculty of Arts and Sciences at Harvard made a cautious announcement in April 2026 that it was getting ready for a major administrative reorganization. In comparison to their already small budgets, the arts and humanities were facing a reduction that was disproportionately large.

In February 2026, an uncommon kind of reaction emerged into this landscape. As part of a challenge to raise $100 million by June, a group of alumni donors led by Alfred and Rebecca Lin of the 1994 class announced a $50 million donation toward an endowment fund for PhD students across FAS and SEAS. The Research Accelerator Challenge, as it was called, was specifically created to provide PhD candidates with the kind of financial security that enables them to pursue high-risk, high-reward research without relying on the now-unreliable federal grants. In a sense, it was a workaround. This is an attempt to shield the institution’s intellectual work from political weather rather than a solution to the political issue.

It’s difficult to ignore the unique aspect of that gesture—wealthy alumni essentially taking over the role of the federal government by providing funding for the prerequisites for scholarships. Harvard’s own economists would likely respond cautiously to the question of whether this is a sound model for academic funding. According to Campbell’s framework, short-term relief can be obtained at the expense of long-term capacity by spending endowment distributions above the planned rate. To put it another way, generosity has a budget. Watching all of this unfold from a position that feels uncomfortably exposed for an institution of this size and prestige are the arts and humanities programs that make Harvard what it is, the ones that send students into the world with the capacity to think critically about human experience.

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