Can AI cure the corruption and biases that plague boxing?

Ali, the 92-year-olds Don King and Bob Arum remain leading powerbrokers. They work with overlords who operate in the shadows. In this world, oversight is resisted and new tech greeted with suspicion.

At world title fights, judges still fill out scorecards on scraps of paper. They follow four extremely subjective criteria: "effective aggression," "ring generalship," "clean punches," and defence. All these concepts are open to interpretation.

Inevitably, they frequently create controversial decisions. The problem extends to the sport's top analytics tool. Despite the futuristic sheen of the CompuBox name, its stats are manually created by two people tapping keys when they see punches.

The potential for biases and errors is endless. Fans and fighters alike have decried the results for decades. One of them is Allan Svejstrup, a Danish machine learning engineer.

But Svejstrup (pronounced Svar-strop) also had an idea for a solution: computer vision. A boxing aficionado with a PhD in maths, Svejstrup had his brainwave while working at a startup in China. "I also had the CompuBox doubts," he tells TNW on a Zoom call from the Chinese city of Shenzhen.

"I realised I could build a better system myself." He began to train an AI model on real boxing footage. The model then tracked not only the number of punches but also their impact, the fight's flow, and each boxer's movements.

Svejstrup was impressed by the early tests. In 2022, he turned the passion project into a startup: Jabbr. Two y.