Compendium
Transformations & Generations: Artificial Intelligence and Ecology
March 2026
Ruminating
How do I engage with nature?
I often look at the bucolic green perfection of Japanese Aquascapes on Instagram. "That isn't REAL nature", I think to myself.
There was a jar of algae in my room in India. For five long years, dried leaves decomposed into a thin crust of algae on a rock. I never trimmed it, I never added fertilizers. I forgot about it, for years at a stretch.
Algae in a jar. Nature, perhaps. circa 2025
Artificial Intelligence has a tendency to create a massive Ouroboros-like feedback loop; when prompted to generate nature, it draws up the most common (and sometimes, wrong) idea of nature, based on what general users of the service generate.
My approach to using AI models in generating any visual is (sometimes) a brute force, "throw-everything-at-the-wall-see-what-sticks" method.
Mostly, however, it is a recursive, repetitive, circular fine-tuning of what I want the model to generate for me.
My own mini-Ouroboros.
Using specific images to drive the generation of alternative heightmaps, with a recursive process: an example of how I use multiple passes of generations to get the result I want. (Project: Noise Geographies)
Sometimes, my workflows involve stringing together multiple passes at image generation, Style-training, prompting and generations. Even while using tools like Fuser: the Styles are trained on images generated through combinations and permutations of satellite images on Midjourney. (Project: The Real and the Unreal)
