Julien Bonet

Description

This photo is from a series of 20 images exploring the relationship between creativity and violence in the French suburbs, the fascination they exert and the idea of "zone". It will be published in the coming months, along with a video. In the Middle Ages, the word banlieue referred to the area within one league of a city, under its authority. The term ban referred to a power of command, and gave rise to words like banal, to banish, and the expression to put someone under a ban. In the 19th century, Paris was fortified, and the strip of land beyond the city walls became a military zone where construction was forbidden — it was known as La Zone. It soon became home to marginalized populations. Up to 30,000 people lived there before it was dismantled in the 1950s, replaced by the boulevard périphérique, which cemented the boundary between Paris and its suburbs. Between the two wars, the first housing projects emerged but it was primarily after the second world war that the "large housing estates" emerged, built to accommodate immigrant populations, an essential workforce for reconstruction. From 1959, these areas became Priority Urbanization Zones (ZUP), then Sensitive Urban Zones (ZUS), Urban Revitalization Zones (ZRU), and finally Urban Free Zones (ZFU). In 2014, the term "zone" was abandoned in favor of Priority Neighborhoods of the City Policy (QPV), making the word "neighborhood" a metonym and a euphemism, a social marker.

Process

In 2023, in the suburbs of Paris, a teenager was shot at point-blank range by a police officer during a traffic stop that turned violent. This event triggered eight days of riots, affecting 516 municipalities across France. Since the 1980s, there have been more than 40 episodes of riots, often triggered by police violence.These "neighborhoods" are most often publicized and addressed by politicians through the prism of security, trafficking, or radicalization. Suburban culture attracts with its creativity as much as everyday events can provoke rejection with their violence. The two are linked, of course; wearing streetwear or adopting the language of rap is a way of experiencing a bit of the protest spirit of the banlieues. It's doubtful that this appropriation always serves the original claim, but I find that a protest energy is always welcome, and that if the fashions emerging from the suburbs radiate so much, it's not only because of their creativity but also because they resonate with many of us with the need for dissent. It's this tension between violence and creativity that I wanted to explore through a series exalting the energy of the suburbs: electrifying, proud, inventive, and funny. Against the backdrop of the riots, I also wanted to bring out what I really love: the jokes, the accent, the bullshit, the style, the excesses, the impertinence, the insubordination, a constant snub to the elites and academicism.

Tools

This photo, and the series it is part of, are primarily the result of historical and sociological research on the suburbs. I also drew inspiration from government reports on the riots, early 20th-century photographs from La Zone de Paris, anecdotes that I saw in the suburbs or news items noted in the press. This series is still ongoing and will span several months of work. It was created with a set of AI tools tailored to the needs of each image: Midjourney, Krea, Magnific, Firefly. I always work my images in a fairly raw way, trying to reduce the intervention of AI to photorealistic arrangement, I neutralize as much as possible any influence of style and any reference to other images. Each final photo requires the generation of several thousand images before achieving the desired result. I try to find a use of AI that is specific to it, that another medium could hardly produce, a realistic but impossible photograph, thus questioning the very nature of photography: is it the material used that makes the photo or the final rendering?

Description

Kintsugi Format 4:5 / 1186 iterations In Japan, the term “Kintsugi”, which could be translated as “gold joint”, refers to a technique for repairing ceramic objects. Traces of dish repair using vegetable lacquers can be found throughout Asia, but Japan has added the specificity of a gold finish. In Kintsugi, the aim is no longer to hide the traces of repair but, on the contrary, to enhance them with gold powder. The accident becomes the starting point for a new life, and the golden ramifications underline the object’s past. I wanted to see if this technique could also repair a divided territory. The Middle East was the most obvious terrain, with over a century of conflict, occupation and interference. The scars there seem to be inscribed forever, like gold in broken ceramics. This technique raises the question of the capacity of a territory to be repared, as well as the difficulty of recreating points of contact after decades of conflict.

Process

AI is based on “archetypes”, common figures that the software can easily represent. In the end, AI gestures are fairly close to reality: we work with what we know, as if we only had real materials on hand. It’s more difficult to create unusual things, or you have to do it by hijacking archetypes. After my theoretical research, I always start with a general idea of the mise en scène and a list of materials. I then propose an initial prompt to the AI, which is then refined over several days and thousands of iterations. My prompts are fairly precise, with around 200 words describing the different shots in the image, the set elements, the main subject, the time of shooting, the light, the colors and the focal length. I leave the AI as little leeway as possible on ideas or style; to this end, I neutralize all functions aimed at stylizing the image, and I make no reference to visual trends or artists. With the exception of secondary elements such as a background, I don’t formulate generalizations about the staging; instead, I give the AI a sum of precise elements and let it propose an initial arrangement, which I then refine by adjusting the prompt. This often results in rather unsightly, chaotic images. It’s as if, at the outset, we weren’t speaking the same language, but by dint of repetition, the AI integrates the words and manages to create a harmonious object. As you refine and refine the request, there usually comes a point where the prompt becomes too dense for the AI. Certain initial materials disrupt the image because the AI is unable to represent them correctly. I then purge the prompt of all parasitic requests. When the main elements of the image are more or less settled, usually after the first thousand or so iterations, I can focus on the mood and feelings conveyed by the image. Little by little, I fix the light, the hue of a sky, the attitude of a character and anything else that will convey the desired feeling. Statistics and chance also play a part in the process, with the most relevant prompts being repeated hundreds and hundreds of times to push the AI’s layout possibilities. This is truly a collaborative work. The last phase of the process, which is extremely satisfying but rather heartbreaking, consists of selecting a small number of really relevant images, and then, by comparison, keeping just one. Finally, the selected photo is enlarged on a second AI, its details fine-tuned, colorimetric processing and textures retouched for a large-format print.

Tools

Midjourney + magnific + Firefly + Photoshop