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The School of Visual Arts has taught graduate photography through the arrival of Photoshop, digital cameras, smartphones, and social media. Artificial Intelligence may prove a more difficult transition.
The New York art school will close its MFA in Photography, Video, and Related Media after the Class of 2028 graduates, bringing a program established in 1988 to an end in its 40th year. Current students will be able to finish their degrees, but no subsequent cohort will take their place.
AI makes an obvious headline, but it would be innacurate to blame the closure on technology alone. SVA Provost, Jason Koth, attributed the decision to the school's financial difficulties, declining enrolement in graduate photography programs across the United States and wider federal policy and financial pressures. SVA's overall registration has reportedly fallen 34 per cent since 2019, while the institution is facing a $22 million structural budget deficit this year. These figures explain why a program might close, however, they do not entirely explain why photography education is struggling to attract students in the first place.
For decades, technological change expanded what photographers could do without removing the photographer. Film gave way to digital sensors, darkrooms were joined by editing software, photographs moved onto websites, phones and social platforms. Those tools changed dramatically, but someone still had to make the image.
Generative AI interferes with that relationship. An image can now be produced without a camera recording the world in front of it. In commercial photography, where the purpose of an image might simply to be to illustrate a product, concept, or campaign, that difference has immediate economic consequences. AI-generated imagery can complete with work that once required photographers, equipment, locations, models, and production teams.
That places photography schools in an uncomfortable position. Students considering an expensive graduate degree are entering an industry in which some of the work traditionally used to build a career is being automated or replaced. Falling enrolment therefore cannot be separated entriely from the changing professional value of image-making, even though there is no evidence AI alone caused SVA's decline.
Charlie Traub, the program's founding chair, sees another possibility. Speaking to Hyperallergic, he argued that the closure might have been avoided through stronger coordination and a more aggressive rethink of how the program would respond to AI.
Traub makes a point as SVA's photography program was initially built around technological change. The MFA developed an expansive approach to photography, video, and digital practice long before those boundaries became commonplace. SVA's own graduate material still describe Photography, Video, and Related Media alongside an extensive group of programs spanning digital photography, design, film, and contemporary visual practices.
There is also a contradiction in allowing AI to weaken the case for photography education. As synthetic images become easier to produce and harder to distinguish at a glance, understanding how images are constructed, manipulated, circulated, and interpreted becomes more important. Photography eduction does not have to compete with AI by pretending the technology doesn't exist. It can teach students to understand the visual culture AI is producing alongside the photographic traditions it is disrupting.
But, this does not solve SVA's immediate financial problem. A culturally relevant program still needs enough students and institutional support to remain viable. The photography MFA is also not the school's only casualty. SVA has announces the end of its graduate curatorial practice program as it deals with wider financial pressures.
The closure therefore belongs to two stories at once. One concerns an art school under considerable economic strain. The other concerns a medium whose professional and cultural boundaries are being rewritten unusually quickly.
Photography survived the arrival of digital technology because photographers found new reasons to use it. AI presents a different challenge because it can produce the appearance of photography without the act of photographing. For schools teaching the medium, the task now is not simply preserving traditional photographic practice. It is giving students a reason to study images seriously when making one has never been easier.
