The X Games' Owl AI Just Re-Judged The Women’s Olympic Slopestyle Contest

More than a week removed from the Olympics, and people are still debating whether or not the judges got it right.

Mari Fukada won her first gold medal in the women’s slopestyle contest. She threw a switch 1260, but also included two 720s in her run. It scored higher than Zoi Sadowski-Synnott’s run that included a switch backside 900 and back-to-back 1080s, and Kokomo Murase’s, which had a Cab 900, a 1260, and a 1080.

Fukada won gold, Sadowski-Synnott won silver to become the winningest women’s snowboarder in Olympic history, and Murase won bronze, her second medal in as many events in the games. Many viewers disagreed.

Apparently, those same conversations were being held by Jeremy Bloom and the X Games folks as well, and as the only organization with an artificial intelligence-run judging system. Owl AI re-judged the contest. The model disagreed with the Olympic judges.

Owl AI determined what thousands of others in the Instagram comments section did: Sadowski-Synnott deserved the top spot because of the difficulty of her tricks.

“Progression is a core judging criterion, but it wasn’t properly accounted for in the competition,” the video posted says. “Zoi pushed the sport forward with highly technical 1080s while Mari played it safe with 720s, yet received near-perfect execution scores. Inherently a 720 is easier to stomp than a 1080. A perfect older trick basically beat a great progressive trick.”

The program also determined that Fukada and Sadowski-Synnott spent the same amount of time on the rails, but Kokomo Murase spent .37 seconds less time on the rails, which resulted her in getting a lower score, despite her impressive bag of tricks on the jump section. That kept her score from advancing.

“This is not meant to take anything away from the athletes who stood on the podium. They won on that day under the system in place, and that deserves respect,” Bloom said in a press release. “But in our relentless pursuit of bringing more objectivity to sport, we have to be willing to open the black box of judging. As a society, we should engage in this conversation and work toward a system that is more transparent and more fair — for every athlete who dedicates their life to the pursuit of excellence.”

The AI model used thousands of hours of competition footage, machine learning models based on official judging criteria, and the same scoring framework used in Milan.

“Owl AI’s mission is simple: reduce human bias, increase transparency, and help judged sports evolve with the tools now available in the modern era. The technology does not replace judges. It empowers them,” the company said in a press release. “It provides real-time feedback, data-backed analysis, and a second layer of accountability that can elevate sport for athletes and fans alike. Because in elite competition, the margin between gold and silver is often measured in tenths — and every tenth matters.”