AI, microwaves, and other things you don’t understand
While some people are still busy writing thinkpieces about how “using AI is just microwaving frozen food instead of cooking,” other people quietly moved on and started doing something terrifyingly adult: they study what actually happens when humans create with machines.
That’s the part the anti-AI kids never touch. They’re fluent in culinary metaphors, allergic to data. They can tell you that “real art” must be hand-made, but they can’t be bothered to look at what changes when you put a generative model into the creative loop and watch the process instead of moralizing about it.
One of my favorite phrases to come out of this research landscape is brutally simple: the future belongs to symbiants — humans who know how to co-create with AI instead of larping as monks guarding the last analog brush. Not “prompt monkeys”, not passive consumers of machine output, but people who treat these systems as volatile, powerful collaborators and learn to direct them.
And when you actually look at the findings, the picture is even more offensive to the “microwave” crowd than any corporate marketing could ever be.
First: AI doesn’t just amplify the already-brilliant elite. It disproportionately lifts up people with mid-level or uneven skills. The ones who have taste but lack speed; who have ideas but not enough technique; who can see the direction but can’t brute-force their way there by hand in time. Give them generative tools, and suddenly their floor rises. Their work becomes usable, presentable, competitive. The “natural talents” are no longer the only ones allowed to speak.
Of course the gatekeepers hate that. If your entire status rests on the fact that you survived a long, expensive initiation ritual, nothing is more threatening than a tool that lets the uninitiated bypass half the corridor and start experimenting at a higher level on day one.
Second: generative systems don’t kill imagination, they pour gasoline on it. Anyone who has actually done iterative work with these models knows the pattern: you start with one idea, get a batch of outputs, and instead of “being done”, your brain lights up with ten new directions you never would have reached alone. You branch, remix, refine, collide outputs against each other. The process becomes less linear and more combinatorial; you stop worshipping the first idea that came to you just because it was expensive to execute.
The part that makes me laugh is this: people who have never gone through that loop — idea → generation → surprise → new idea → iteration — speak with enormous confidence about what AI “does” to creativity. They talk like priests describing a demon they’ve never seen, only heard about from other anxious priests. Meanwhile, the actual symbiants are too busy building to argue on whether a neural net is a “real oven” or not.
If you want to have an opinion on “what AI does to art”, you can’t stay at the level of kitchen analogies. You have to look where it hurts: at the way co-creation reshapes who gets to play, how fast we can iterate, and what happens to people whose only claim to legitimacy was “I got here first and suffered longer.
