Using AI Does Not Make You Less of a Photographer: Francine Marie Bautista on Skill, Tools and Creative Judgment

There is a particular accusation that has become increasingly common in creative spaces: “You used AI.” It is often delivered as though those three words settle everything. The work gets dismissed. The person’s ability gets questioned. A photographer becomes “not a real photographer.” A writer is suddenly “not a real writer.” A designer is accused of having no creativity at all.

When FMB News spoke with Francine Marie Bautista about artificial intelligence, this was the first attitude she wanted to challenge.

Her argument was not that everything made with AI is automatically good. Quite the opposite. Her point was that judging someone’s ability simply because AI appeared somewhere in the process is intellectually lazy. She gave photography as the clearest example. There are people, she explained, who look at a photographer using artificial intelligence and immediately conclude the photographer must not be very good. But what exactly disappeared? Did the photographer suddenly forget composition, lighting, timing, direction, emotion or storytelling? Did they lose the ability to recognize a strong photograph simply because part of the workflow got easier? The question exposes a weakness in a lot of the criticism around AI: we are often judging the tool instead of examining what the human being actually did with it.

Photography, after all, has never existed independently from technology. The camera itself is technology. So are autofocus, digital sensors, image stabilization, RAW processing, Lightroom and Photoshop. Today, mainstream professional creative software includes generative AI functions. Adobe Photoshop, for instance, includes Generative Fill for adding, removing and replacing parts of images using generative AI. Does the presence of that tool automatically invalidate every photographer who touches it? Bautista’s answer is no, for a simple reason: a tool can execute an instruction, but it cannot automatically make the instruction intelligent. A photographer still decides what needs changing. A photographer still determines whether the change improves or damages the photograph. A photographer still decides what belongs in the frame. The tool may shorten part of the process. The creative judgment has not necessarily disappeared.

The conversation got more interesting once we moved past AI itself, because underneath a lot of the criticism is another belief entirely: that if technology makes something easier, the person deserves less credit for it. Imagine two photographers removing the same distracting object from an image. One spends an hour doing it manually, another uses an AI-assisted tool and finishes in seconds. If both arrive at an equally convincing result, is the first photographer automatically more talented because the process took longer? That would mean we are measuring artistry partly by inconvenience, which is a strange standard to hold anyone to. Bautista’s position is that a good photographer should not be required to deliberately use a slower method just to prove they possess skill. Efficiency and incompetence are not synonyms. Sometimes a person works faster because they understand their tools better than the person next to them.

But, and this is where her argument becomes more defensible than the usual AI-optimist line, she is not claiming that access to AI suddenly makes everyone an expert. Give the same AI tool to two people and you can still get radically different work. One accepts the first result the software hands back. The other notices the lighting is inconsistent, the composition has weakened, the skin looks unnatural, the typography does not belong, the visual concept has lost its meaning. The difference is human judgment. AI can generate possibilities; it does not guarantee taste, and taste remains one of the hardest parts of creative work to quantify. Someone still has to know when the output is bad. Someone still has to know what to ask for. Someone still has to decide what deserves to survive the editing process. This is why the growing AI divide may not simply be between people who use AI and people who refuse to. It may increasingly be between people who know how to direct these systems and people who merely know how to access them.

There is a fair version of the “but they did not make it themselves” objection, and Bautista does not dismiss it. There are situations where AI genuinely changes the nature of authorship. If someone generates an image and deliberately presents it as documentary photography they personally captured, that is an honesty problem. If someone imitates another artist and claims the resulting work as entirely their own, questions about authorship and ethics are entirely reasonable. If an AI system performed the central creative act and the human contributed almost no meaningful judgment, it is fair to discuss how much credit belongs to the human. Those are legitimate conversations, but they are very different from saying “you used AI, therefore you have no talent.” One examines what actually happened. The other stops thinking the moment it discovers the tool.

Photography is a particularly useful test case for this whole debate, because the photographer’s most important piece of equipment has never simply been the camera. It is their eye: the ability to notice the moment before it disappears, to understand someone’s face, to know when a subject is uncomfortable, to place light deliberately, to recognize when a technically imperfect photograph is emotionally perfect, to understand what needs to remain untouched. AI can help alter pixels after the shutter has already been pressed. But the photographer still has to decide what photograph is worth making in the first place, and that distinction gets lost every time these debates turn into moral competitions instead of conversations about the actual work.

By the end of that part of our conversation, Bautista’s position could be reduced to something surprisingly simple: do not use the presence of AI as a substitute for evaluating the work. If the photograph is bad, explain why it is bad. If the writing is inaccurate, challenge the accuracy. If the design is generic, criticize the design. If the creator is being dishonest about how something was made, challenge the dishonesty. Those are meaningful criticisms. But “AI was used” is merely a description of part of the process. It is not yet a judgment about quality.

Maybe that is where this whole conversation needs to mature: we should stop asking only whether a tool was used, and start asking what the human being contributed after gaining access to it. A bad photographer can use AI. A brilliant photographer can use AI. A bad photographer can also refuse AI entirely. The software does not settle the question. The work does. And ultimately, so does the judgment of the human being behind it.