Today, I encountered a term on LinkedIn that I had to look up and research. It was a person labeling themselves as “synthograph,” and even if it was more or less clear what they did, I wanted to check myself and answer the question, “What is synthography?”. Artificial Intelligence has forged a new frontier in the realm of creativity. Synthography, a term yet to be etched in the dictionary of artists, is already coloring the canvas of the digital world. But what exactly is synthography, and how is it reshaping the art of visual storytelling?
Synthography stands at the delicate axis of technological prowess and creative flair. It is the art of crafting visual imageries that mimic photographs but with a twist as they are synthesized, not snapped. The term and the practice have far-reaching implications for those who create with pixels and light and for those who seek to redefine the essence of a ‘photo’ in an age where the line between the organic and the artificial grows increasingly blurred.
Defining the word, crafting the soul of synthography
Before plunging into the medium of synthography, it’s pivotal to divine the term itself. A synthographer isn’t just a visual conductor but a composer of the unreal-real; they use AI and machine learning to fabricate scenes not with a lens but with logic gates and algorithms. Think Picasso meets Turing, a marriage of artistic vision with scientific acumen.
The term derives from ‘synthetic’ and ‘photography,’ underscoring its essence, a creation that springs not from the ‘photo’ but from synthesis. While some may scoff at the thought of machine-made art, it’s within these pixels that new forms of expression breed, ones that challenge our preconceptions about what is genuine and what is contrived.
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On Wikipedia, we can find the following proposition around the term itself: “Synthetic media, which includes AI art, was described in 2022 as a major technology-driven trend that will affect business in the coming years. ‘synthography’ is a proposed term for the practice of generating images similar to photographs using AI.” While this is making sense, any or all artists could decide to make use of such a definition or decline it and turn it into something else.
The genesis of synthography and its evolution
The beginnings of synthography are shrouded in the hum of supercomputers rather than the click of a shutter. We trace its lineage to the earliest experiments in AI-driven visuals and the seeds sown by pioneers who dared to envision a world where machines think and dream. The dawn of the 21st century saw a swell in interest in AI arts, and the torrent of digital data fed into neural networks gave rise to new ways of painting, drawing, and, crucially, synthesizing.
In the span of two decades, synthography has evolved from the esoteric backwaters of research labs to the mainstream miasma of social media. No longer the exclusive tool of high-end post-production or digital experimentation, synthography is seeping into the daily fabric of visual culture. Artists and creators are not just consumers of synthetic media but producers, for better or worse.
The techniques and technologies at the core of synthography
In her article’s introduction, Elke Reinhuber, media artist, educator, and researcher, writes, “We state a legitimation crisis for the current usage of the term. This paper is an invitation to consider synthography as a term for a new genre for image production based on AI, observing the current occurrence and implementation in consumer cameras and post-production.” She invites people to review her thoughts but also leaves the door open for further thinking.
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The palette of a synthographer is not laden with oils or pigments; it brims with algorithms and data. To understand the craft, one must parse the toolset. Generative Adversarial Networks (GANs) boast a hegemony within this realm; they play the game of cat and mouse, generator and discriminator, to forge images that can deceive. Style Transfer techniques bend the morphology of images, infusing them with the appearance and ethos of other works or genres.
The cameras of synthography are neural networks. The photographs are just a point of reference; the interpretation is prized. AI ‘sees’ the world not as we do but as it dreams it could be. Within this metamorphosis lies a paradox. For every stroke of ephemeral creativity, a code binds it. The collision of the ambiguous with the algorithmic births the enigma of synthography. Certainly, this scaled beyond what we consider photographic arts and expanded into the world of digital drawing; seeing the output of such work can be heavily impacted by the decision for a particular style or medium in that sense of emulation.
The ethical mire and promise of synthetic arts
The rise of synthography isn’t an unblemished ascension. For every hauntingly beautiful piece that it produces, there exists the specter of misinformation and augmentation. The ethical quandaries of synthetic media cast a long shadow over its creative virtues. Its prowess at deception raises profound questions about the veracity of visual evidence in an age propelled by the mantra of ‘seeing is believing.’
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Yet, the promise it garners is one of the democratization of creativity. Algorithms can be shared and evolved; they are not the private fiefdoms of the elite, guarded by NDAs and enigmatic brilliance. Synthography empowers a new vanguard of artists, those who manipulate data not by virtue of the resources at their disposal but by the ingenuity in their approach. It’s a promise that redefines creative merit, where artists are not merely judged by their canvas but by their craft with code. Following that definition, I would also consider myself a synthograph, even though it could mean more or less of what I dabble with and create.
In the end, we can say that synthography is a thing now. There are artists proudly calling themselves synthographs. Even if there is debate and if things are unclear, this is not uncommon in the world of art and creation. This isn’t about business and processes and achieving a pre-defined output; it’s about inspiration and creativity.
Photo credit: The feature image is symbolic and has been done by Christopher Isak with Midjourney for TechAcute. The embedded examples come from the rAIse Instagram channel.
Source: The sources have been linked directly in the body of the article at their corresponding positions in the text.
