What Does a Photograph Contain?
AI can generate images, but photography is more than image generation
A recent conversation with the photographer and educator Petros Nikolaidis left me wondering whether we have misunderstood what photographers actually do.
Like many conversations about artificial intelligence, this one began with technology. Generative AI can now produce remarkably convincing images in seconds: portraits, landscapes, editorial visuals, advertising concepts. The familiar question follows almost automatically. What happens to photographers when machines can create the images photographers once had to make?
Yet the conversation kept drifting away from images. For me it turned to the human skills and qualities that have seemed oddly absent from discussions of AI image generation: presence, patience, timing, judgment, context, and interpretation. Petros, a working photographer who also trained as a historian, came at the same subject from the other direction: photography has been through technological upheaval before.
The more we talked, the less the photograph looked like the whole of the work. That observation points to a question larger than photography. When technology reproduces an artifact, what happens to the practice that produced it?
Photography is usually described through its outputs, and the description has the shape of a tautology: photographers take photographs. True as far as it goes, which is not far. But this cliché is obviously incomplete.
A documentary photographer may spend days traveling to a location before taking a single image. A wedding photographer spends the day navigating relationships, expectations, and emotion. A portrait photographer establishes trust before ever pressing the shutter. Of all this, only the image survives. The observing, the waiting, and the judging leave little trace in the frame.
AI forces a distinction that has always existed but rarely needed stating: the difference between an output and a practice. An output is an artifact. A practice is the structured activity behind it, the preparation, attention, judgment, and interpretation that go into making it. Often the two overlap so closely that we stop noticing they are different things.
For most of the history of photography, that distinction hardly mattered. If you wanted a photograph, a photographer had to make one, and the photograph usually served as a proxy for the activity behind it. At first glance a photograph contains only what is visible: light, color, composition, subject matter. Yet we have long read more into it. We look at a war photograph and take it for granted that someone was there. We look at a portrait and assume some exchange took place between photographer and sitter. Until recently those were safe assumptions, because the image and the activity behind it were so difficult to separate.
Technology has often reproduced outputs before it reproduced practices. A convincing image can now be generated without traveling anywhere. A report can be produced without running the consulting project behind it. A set of lecture notes can be written without anyone having taught the class. The output can now appear without the practice, which means it no longer tells us as much as it used to about the activity that produced it.
Petros’s historical training is useful here, because photography has had this experience before. Roll film put the camera in the hands of amateurs. Retouching and darkroom manipulation raised the first disputes about what a photograph could be trusted to show. The move from film to digital displaced a generation of technical craft. Each time, a technology arguably separated part of the visible result from the skill behind it, and photographers had to work out what they were actually offering. How they described their own value at those moments, and what clients went on paying for, is a matter of record. Petros and I are looking at that record more closely, so I will not anticipate what it shows.
So the useful question is whether the picture exhausts the value of the activity that produced it. The answer will differ enormously by genre.
Consider product photography for an e-commerce catalog: five hundred items shot against the same white background, lit to show color, texture, and fit as accurately as possible. There is skill in that work, but the image comes close to exhausting the purpose of the activity. Nobody needs to have traveled anywhere, built trust, or interpreted a complex situation. The photograph is largely the point. It is therefore unsurprising that this segment may be particularly exposed to automation. Even here, though, the image has to answer to something outside itself. A catalog picture must show the particular item on sale, and a plausible object of the same kind will not do, so automating the picture still leaves someone to establish that it matches, and opens the door to errors.
Other kinds of photography are harder to call. Petros’s own answer to what the machine lacks is the one creative people often give: experience, or something close to soul. I am wary of the word, partly because it cannot be tested, but an example of his makes the point more precisely. One of his series connects photographs taken in Norway with themes from Greek mythology. A Norwegian landscape does not obviously suggest a Greek myth. The link comes from Petros, a Greek Cypriot who studied history in Greece, and it is the kind of link any of us might make when a place we are seeing meets an image or a story we carry from somewhere else. People do this so readily that we hardly notice. A machine can be asked to connect a fjord to a myth, and it may do so fluently. What it lacks, at least in the way a person has it, is a biography that makes one connection matter more than another, and so a reason to choose this link, this frame, and this sequence from the many available. That choosing is part of the practice, and in his series it seems to be where much of the value sits.
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Richard Sennett made a version of this argument long before generative AI. In The Craftsman (Yale University Press, 2008), he argued that craftsmanship is more than the production of artifacts. It concerns the relationship between thinking and doing, between judgment and action. Seen this way, photography starts to resemble a practice as much as a product. Generative AI leaves that distinction intact and makes it harder to ignore.
Photography is only a particularly clear example. Consulting has the same structure. A client remembers the deck: the framework, the recommendations, the tidy chart. Yet much of the value may have resided elsewhere, in understanding which recommendation the organization could realistically absorb, and in building enough credibility that an uncomfortable truth could be said aloud. Neither appears on a slide, though both may have shaped every slide.
For decades, we often evaluated consulting through the artifact because the artifact was difficult to separate from the practice. A competent deck can now increasingly be produced from a competent brief. That does not prove the consulting activity was unnecessary. It forces us to ask where the value actually resided, a question I took up from the judgment side in Cheap Execution, Expensive Judgment.
Teaching has a similar structure. The slides are the artifact. The practice is reading a room of students, deciding what to leave out, and changing course halfway through a lecture because the room has told you something.
The larger consequence of generative AI may be that it weakens a relationship we had taken for granted. For a long time, artifacts and practices traveled together. The photograph implied a photographer at work, and the report implied a project behind it. That implication is becoming less reliable.
When technology reproduces the artifact, we are left asking a question that was previously easy to ignore: was the value located primarily in the output, or in the activity that produced it? Once an image can be generated without a camera, the debate is no longer only about images. It becomes a question of whether we treated the artifact as a proxy for the practice all along.
So what does a photograph contain? Light, color, and composition, certainly. Beyond that, it contains what we assume about the person who made it, and for a long time that assumption cost us nothing, because it was usually right. Now it has to be checked, and the answer will vary from one photograph to the next.
Dr. Nicos Rossides is a CEO, educator, and author whose work spans management, education, and artificial intelligence. He is Co-Founder and Chairman of the Advisory Board of listening247, a global insights firm, and Professor of Management at Minjiang University’s International Digital Economy College. His Routledge titles include Engaging the Workforce (2022), Employee Engagement in Startups (2025), and AI-Powered Insight (2026, with Michalis A. Michael).
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