The Future of Photography in the Age of AI
Will AI kill the art and business of photography?
Artists have always faced hard labor and mental strain. Photographers, for example, had to endure the hardships of lugging around heavy equipment and developing their own film, traveling to remote locations, and often waiting for the perfect moment to take a picture. To take this photograph of a polar bear in its natural habitat, National Geographic photographer Paula Nirdon had to travel to the Arctic and spend days in subzero temperature waiting for the bear to emerge from its den.
But what if a machine could do all that for her?
Today, emerging AI image synthesizers such as DALLE, Midjourney and Stable Diffusion, are capable of creating stunning, photo-realistic images, and some artists feeling the heat¹.
Now, to be perfectly honest, Paula Nirdon doesn’t really exist, and so does the bear in this photo — it is 100% generated by AI. I’m sorry if I managed to fool you but I was trying to make a point:
What does it mean for the photography industry where creating images that are indistinguishable from reality becomes possible with a machine?
Without doubt, nature photography can not, and should never, be faked by AI. It should be about the real thing. Nature photography is about capturing the beauty of the world around us, and in making a statement about the importance of preserving the earth and its natural resources. If nature photographs are faked by AI, it would destroy the credibility of the genre, and make it just another commercialized, fake product.
Henri Cartier-Bresson, the father of modern photojournalism, explained that photography is not like painting² . There is a decisive moment in photography, which is when the photographer composes and captures the scene in front of them with their camera.
This decisive moment is what separates photography from painting — and from AI art. This it is what makes photography unique. Cartier-Bresson was right. Many types of photography such as photojournalism, sports and street photography cannot be replaced by AI image synthesis because the entire value of these images stems from the fact that they document real, decisive moments.
However, there are other genres of photography where authenticity is not as important. Commercial photographers who focus on generating content for advertising or stock photography are going to be hit the hardest. Today, a full-day of commercial photography typically costs $750-$3,000, but in the very near future, such photographers will have to compete with pixel-perfect AI generated images that cost pennies to create.
This is a difficult situation for commercial photographers, and, the quality of the images produced by AI will only get better, while the price will remain the same. With cutting edge algorithms such as DreamBooth by Google³, and Textual Inversion by Tel Aviv University and NVIDIA⁴, it is now becoming feasible to fine-tune or customize existing Generative AI models, injecting customer’s concepts, people and products — all the ingredients that are needed for producing commissioned work. This could lead to a situation where commercial photographers that fail to adapt to this new world, are unable to make a living.
The bottom line is, just like Photoshop and digital cameras have came into the lives of photographers in the last decades, transforming the way photographs are being made, AI image synthesis is going to have a profound impact on the business of photography. But not all genres would be effected in the same way.
If you are a nature or documentary photographer, keep doing what you are doing. The social importance of your work will not be diminished by the rise of AI, and you will always have an audience that appreciates the unique perspective that you offer.
But if you are a commercial photographer, my advice would be to start investigating how AI can be used in your workflow. Soon, there will be a high demand for photographers who know how to integrate AI in their work, and the first ones to learn how to do this will be able to make a very good living.
After all, producing a powerful, iconic image is your art. The camera is just a tool, and if a new tool comes along that can help you produce an even more incredible image, don’t you want to be one of the first to use it?
 Brand, Aron (2022). Artists Up in Arms Over New AI Model That Can Generate Similar Works.
 Bernstein, Adam (2004). The Acknowledged Master of the Moment. Washington Post.
 Ruiz, N., Li, Y., Jampani, V., Pritch, Y., Rubinstein, M., & Aberman, K. (2022). DreamBooth: Fine Tuning Text-to-image Diffusion Models for Subject-Driven Generation.
 Gal, R., Alaluf, Y., Atzmon, Y., Patashnik, O., Bermano, A., Chechik, G., & Cohen-Or, D.. (2022). An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion.