Art-market history was made late last month when a work created using a neural network—one type of technology now commonly, if somewhat reductively, classified as an artificial intelligence—sold at Christie’s auction house in New York for $432,500.

The print was made using a form of machine learning called a Generative Adversarial Network, or a GAN (which you can read more about here). The Christie’s sale wasn’t the first time a work using so-called AI has been sold at auction, but it did mark the first time that a major auction house paid attention to the field—and helped drive the price up to nearly half a million dollars.

The sale has also stirred controversy in the close-knit generative-art community. Many artists working in the field point out that Obvious, the collective behind the AI that made the pricey work, was handsomely rewarded for an idea that was neither very original nor very interesting. The savvy marketers behind the sale seemingly took advantage of the fact that the wider public is not very educated about the sector. Even the Christie’s expert who put the sale together admitted that he first learned about Obvious’s work from an article that appeared on artnet News in April.

As for the other major auction houses, a spokesman for Bonhams, interestingly, told us it is not considering hopping on the algorithmic trend now or in the future. Neither Sotheby’s nor Phillips responded to requests for comment on the matter.

While we wait for the next AI-generated work to hit the block, there’s a lot more to learn. To find out about the interesting work being created with machine learning—and the complex boundaries it’s pushing—we’ve assembled a list of nine pioneering artists to watch.

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