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HomeArtificial Intelligence and Machine LearningRobot Umpires Invade Baseball; AI That Makes Mistakes on Purpose Could Help 

Robot Umpires Invade Baseball; AI That Makes Mistakes on Purpose Could Help 

By John P. Desmond, AI Trends Editor   

Robot umpires are being employed in minor league baseball as an experiment, while a study of strike zones of major league umpires shows a fairly wide variation. 

The Automated Ball-Strike System, which players like to call “robo-umpire,” is being tested in minor league baseball this season, according to an account in The New Yorker . 

Major League Baseball had designed the system and was testing it in eight of nine ballparks at the Low A Southeast League. While the term ”robo-umpire” might suggest a little R2-D2 positioned behind the plate, the MLB decided to have human umpires announce the calls, which were fed to them through an earpiece. A black sensor that looks like a pizza box with a glowing, green eye is positioned behind and above home plate, according to The New Yorker account. 

The pizza-box device is made by the company TrackMan, founded by two Danish brothers, Klaus and Morten Eldrup-Jørgensen, who created it to train golfers. The MLB strike zone is an imaginary box over home plate, 17 inches wide and extending vertically from the batter’s knees to the middle of the chest, just under the armpits. TrackMan’s website states that AI is incorporated into its golf product. 

The first umpires were volunteers who wore top hats, at whom spectators “hurled curses, bottles and all manner of organic and inorganic debris,” according to a paper by the Society for American Baseball Research quoted in The New Yorker account. 

Fred DeJesus, umpire, minor league baseball, Atlantic League

After the game observed by The New Yorker, the writer spoke to the umpire, Fred DeJesus. “There were six calls that I disagreed with,” DeJesus stated, referring to the words that came through his earpiece from the robot. 

The ABS system last year had a three-dimensional strike zone; this season, the zone was defined in two dimensions.  

MLB Umpires Association Cooperating on Robo-Umpires 

The MLB Umpires Association agreed in their latest labor contract to cooperate with use of the ABS system if Commissioner Rob Manfred elects to use the system in the major leagues, according to a recent account from AP News. 

Chris Marinak, chief operations and strategy officer, Major League Baseball

“It’s hard to handicap if, when or how it might be employed at the major league level, because it is a pretty substantial difference from the way the game is called today,” stated Chris Marinak, MLB’s chief operations and strategy officer.  

While MLB tracks the accuracy of ball-strike calls by its umpires, it does not release the figures. However, umpire Angel Herdandez, in a lawsuit filed against the MLB, stated that his accuracy on ball-strike calls increased from 92.19% in 2012 to 96.88% in 2016.  

Players subject to the ABS will be measured before their first game, Marinak stated, and the top of the strike zone will be 56% of their height and the bottom, 28%. The strike zone will be measured in two dimensions at the front of home plate.  

Right now, MLB is trying to get feedback on the ABS, such as on the shape and design of the strike zone. “We have a lot of work to do to decide what is the zone with this automated system,” Marinak stated. “Is it more of an oval-shaped zone, which is more consistent with what’s called today? Is it a square zone? Is it a three-dimensional zone? How does the zone shift from hitter to hitter? Is it literally the zone drawn every single pitch, as is written in the [rule] book, or is it a fixed zone that’s based on your height as a hitter, no matter how much you sort of squat down or stand up?”  

These are serious questions. If AI is involved in assessing the quality of a pitch, the designers of the system will need to decide the shape of the strike zone definitively—oval or square and the number of dimensions.   

Today’s Strike Zone Varies by Umpire  

The strike zone today is subject to the whim of the individual home plate umpire, according to a recent account in The Washington Post  

A study conducted by The Post based on pitch-tracking data from TruMedia and Baseball Prospectus through the games of Aug. 1 showed umpires appear to be squeezing pitchers in 2021. Specifically, pitches that should have been called strikes this season have instead been called balls at a higher rate than ever before.  

So far this season, umpires are calling fewer strikes than at any point since 2008, the first year sophisticated pitch tracking was available, the Post study showed. Data compiled by TruMedia, which provides data analytics tools, visualizations and video scouting tools to professional sports teams, umpires made 11,644 incorrect calls on balls and strikes, in 2020, equal to about 6.5 poor calls per game.   

Some umpires have different strike zones for each team in a game, the Post study showed. 

Given that this study confirms bad umpiring is part of baseball, an AI system involved in the automation of the strike zone should perhaps take this into account.   

Cornell Researchers Working on Fallible AI  

Fortunately, researchers at Cornell University are studying an AI system that better understands that humans make mistakes, according to a recent account in Wired. But instead of being focused on baseball, the AI program named ‘Maia’ is focused on chess, especially on the prediction of human moves, including the mistakes they tend to make.  

Professor Jon Kleinberg, who led the development of Maia, sees it as a first step toward developing AI that better understands human fallibility. He hopes this results in AI that is better at interacting with humans, by teaching, assisting or negotiating with them. 

He chose to focus on chess because it has a track record of having machine intelligence winning out over humans. “It is this sort of ideal system for trying out algorithms,” Kleinberg stated.   

The Cornell team modified existing open source code to create a program that learned by favoring accurate predictions of human moves. It is unusual in how it focuses on finding the most likely move a human would make.  

If MLB could tap the professor’s brain to build an AI system that could preserve the apparent fallibility of its umpires, perhaps that would continue the traditions of the game in the robo-umpire era.  

Read the source articles and information The New Yorker, from AP News from The Washington Post and from Wired. 

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