If you stumbled across Terence Broad’s AI-generated artwork (un)stable equilibrium on YouTube, you might assume he’d trained a model on the works of the painter Mark Rothko – the earlier, lighter pieces, before his vision became darker and suffused with doom. Like early-period Rothko, Broad’s AI-generated images consist of simple fields of pure color, but they’re morphing, continuously changing form and hue.
But Broad didn’t train his AI on Rothko; he didn’t train it on any data at all. By hacking a neural network, and locking elements of it into a recursive loop, he was able to induce this AI into producing images without any training data at all – no inputs, no influences. Depending on your perspective, Broad’s art is either a pioneering display of pure artificial creativity, a look into the very soul of AI, or a clever but meaningless electronic by-product, closer to guitar feedback than music. In any case, his work points the way toward a more creative and ethical use of generative AI beyond the large-scale manufacture of derivative slop now oozing through our visual culture.
Broad has deep reservations about the ethics of training generative AI on other people’s work, but …
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