Sophie Grosfield
New York City, USA
As we enter a new era in sports defined by technological advancements, regulatory bodies have begun to embrace the implementation of AI, transforming the career trajectory of referees. One of the undeniable challenges for a referee is making both fair and accurate calls. Due to human error, the referee is often the center of both players’ and viewers' anger, but AI could change that. The use of AI referees in sports has rapidly gained popularity, as the possibility of a “bad call” drastically decreases compared to its human counterparts.
Despite the fact that advancements in AI have skyrocketed in the past few years, AI was first introduced into sports around 15 years ago with tennis’ “Hawk-Eye” system. Before Hawk-Eye was introduced, linesmen lacked precision with their calls, as the human eye isn’t advanced enough to be able to truly see whether the tennis ball is in or out. Therefore, the possibility of a “bad call” was an inescapable reality referees would face. An example of the inaccuracy of refs can be demonstrated in the 2004 tennis match between Serena Williams and Jennifer Capriati. In this match, the referee incorrectly called Williams’ ball out of bounds on a crucial point which aided Capriati's victory. Serena even argued that “every time I hit a ball, they would call it out. No matter how close it was or how far it was.” Not only did Serena experience inaccurate calls from the umpire, she also experienced biases that prevented her from achieving her maximum potential in the game. According to CNBC, Hawk-Eye can track a tennis ball at 340 frames per second and has an accuracy within a millimeter. Because of Hawk-Eye’s precision, situations like Williams’ have been prevented, leading to a more fair and more accurate game.
AI’s revolutionary implementation in tennis has raised the question for other sports: can technology improve fairness and neutrality? Inspired by Hawk-Eye’s use in tennis, baseball aimed to make their referee calls more accurate with the MLB’s automated ball-strike system. This system uses motion capture and AI algorithms to determine whether a pitch falls inside a strike zone. Similarly to tennis, baseball has seen an extreme increase in precision and validity in referee calls. Yet, the topic of AI referees cannot be discussed without acknowledging the backlash these technologies have received by sports fans. Specifically, the MBL has encountered a problem where their AI technologies take too long to make an accurate decision—taking away from the fast-paced nature of baseball and making the game feel increasingly fragmented.
AI has undeniably increased the accuracy of sports calls, yet it will be interesting to see if the implementation of AI in sports is exploited or used ethically in the future. Nevertheless, AI has the ability to transform the nature of sports and improve the industry for both players and viewers.
