IBM Watson At The US Open: Showcasing The Power Of A Mature Enterprise-Class AI

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This week IBM held an analyst session on their Watson AI platform, and it was being used to provide security and other features for the US Open.  It is uniquely capable of identifying and mitigating unique threats. Besides, it was used to assist fans debating the game and create other features that made this year’s US Open without fans present (due to the Pandemic) more interesting. 

But John McEnroe was also on the call, and he answered some fascinating questions regarding AI and Djokovic, the number one contender, being kicked out of the event. He argued that Watson might have come to a very different and fairer conclusion. 

One of the enormous problems with sports judging is that it can seem to be very arbitrary and often capricious because people are doing the judging, and even the same people aren’t consistent. And you get different judges so players, and fans, often think they were mistreated. 

What AI can do is bring a level of consistency to judging where emotions take a back seat, and judgments can at least appear to be fair more unbiased. 

Let’s chat about that this week as we explore how AI could make sports seem more fair.

How AI Could Fix Sports

What happened at the US Open was that Novak Djokovic, upset with how the game was going, hit a ball out of anger, and it bounced off a line judges neck sending her rapidly to the floor. He didn’t intend to hit the line judge, but the Judge was injured enough. She had to leave the game, and this caused the umpire to remove Novak from the tournament.

Many of the fans and Novak seemed to think this was unfair because the act was an accident. And, had the ball not hit the line Judge, it is believed there would have been no severe penalty. This decision had come after Novak had contracted COVID-19 after failing to follow social distancing and mask rules, and what appeared to be a failed attempt to start a rival players union. So he was likely on thin ice. Still, the appearance of unfair treatment took the focus off the game and put it on the judges and umpires. 

What IBM Watson is very good at doing is rapidly aggregating relevant information and then making recommendations based on historical facts for what should be done in a particular instance. It will also provide the details on how it reached the decision showcasing it wasn’t capricious or vindictive.  So both the player and the fans would have received not only the decision, but the validating facts that led up to that decision would show that it was consistent with prior decisions and based on facts, not emotions. In short, it would have appeared fairer. 

Watson, tied to line cameras, likely could also perform consistently concerning whether tennis balls were in or out of the court, allowing line judges to be remote from the field and less likely to be hit by tennis balls or the occasional flying racket. This practice would not only be safer, but it would allow the judges to more rapidly confirm the call that the ball was in or out of the court. 

With any sport, there is always a concern that betting will corrupt the judging, and Watson could not only provide a level of prevention but could also look at trends and determine if a Judge or Umpire was compromised. This capability would potentially reduce the likelihood of scandals, which can have a severe impact on fan loyalty and attendance. 

Finally, Watson could help players when something like this does happen.  For instance, after the ruling, Novak just left for the airport and didn’t talk to reporters or apologize in person who reflected poorly on him.  Watson could have provided options based on past events, like those McEnroe was involved in, to get valid options on what he should do to mitigate the damage to his brand. 

Wrapping Up: Turning The World Into A Fairer Place

IBM’s goal for its AI efforts is to enhance and not replace humans. Sports provide an exciting showcase for how AI across a broad spectrum of activities and in full view of fans who, themselves, might be interested in this kind of enhancement for their responsive executives and firms.  And similar capabilities could be used to enhance and supplement our already overworked and underfunded Judicial system.

In the end, finding a way not only to provide unbiased judgments but proof they were unbiased may be a critical part of finding a way to get through today’s divisive times.  The world has never been a fair place, but maybe, an AI like Watson could make it fairer than it has ever been before.



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