One Thursday last month, 19-year-old Robbie Barrat woke to a fusillade of messages on his phone. “I was half asleep but saw they all contained the same number,” he says. “Then I fell back asleep for a few hours. I didn’t really want to believe.”

The number in those messages was $432,500—the winning bid at Christie’s New York on a ghostly portrait created using artificial intelligence, following a recipe Barrat posted online not long after graduating high school. Barrat was shocked, because Christie’s had previously estimated the portrait would sell for $7,000 to $10,000. He already felt ripped off by the sale, because he wasn’t credited. He probably won’t receive a cent.

Edmond de Belamy, from La Famille de Belamy, as the portrait is called, was created by a Parisian art collective that goes by the name Obvious. It appears to have made only minor tweaks to Barrat’s methodology to produce the portrait. The incident has triggered a debate about authorship and ethics in the nascent field of AI art.

Obvious and Christie’s did not respond to requests for comment. Barrat says he posted his code to help and inspire others but that Obvious went too far by profiting from re-creating his work. “It’s a very awful situation,” he says.

Barrat and some sympathizers in the small world of AI art are also disappointed that their rapidly evolving movement’s first big flash of public attention revolved around what they consider a derivative work, far from the field’s cutting edge. “People have been doing nearly identical stuff since 2016,” Barrat says. Adds Marian Mazzone, an art historian who studies AI art at College of Charleston: “It doesn’t look like they did anything very new or interesting with what they took.”

People have made art with computers for more than 50 years. Barrat and Obvious are part of a recent movement of creative coding piggybacking on the hottest technology in Silicon Valley.

Google, Facebook, and other tech companies have turned an area of AI research known as machine learning into an intensely competitive arena. The technology lets computers figure out tasks like recognizing objects in images for themselves by digesting example data. A rejuvenated technique called neural networks has given the approach impressive new power. While corporate labs direct that power to uses such as helping autonomous cars navigate traffic, some artists direct it to generate images.