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

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

By John P. Desmond, AI Trends EditorĀ Ā Ā 

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.Ā 

The Automated Ball-Strike System, which players like to call ā€œrobo-umpire,ā€ is being tested in minor league baseball this season, according to an account inĀ The New YorkerĀ .Ā 

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 ā€robo-umpireā€ 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 blackĀ sensor thatĀ looks like a pizza box with a glowing, green eye is positioned behind and above home plate, according toĀ The New YorkerĀ account.Ā 

The pizza-box device is made by the companyĀ TrackMan, founded by two Danish brothers, Klaus and Morten Eldrup-JĆørgensen, 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 batterā€™s knees to the middle of the chest, just under the armpits.Ā TrackManā€™sĀ website states that AI is incorporated into its golf product.Ā 

The first umpires were volunteers who wore top hats, at whom spectators ā€œhurled curses, bottles and all manner of organic and inorganic debris,ā€ according to a paper by the Society for American Baseball Research quoted inĀ The New YorkerĀ account.Ā 

Fred DeJesus, umpire, minor league baseball, Atlantic League

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

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

MLB Umpires Association Cooperating on Robo-UmpiresĀ 

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 fromĀ AP News.Ā 

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

ā€œItā€™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,ā€ stated Chris Marinak, MLBā€™s chief operations and strategy officer.Ā Ā 

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

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

Right now, MLB is trying to get feedback on the ABS, such as on the shape and design of the strike zone. ā€œWe have a lot of work to do to decide what is the zone with this automated system,ā€ Marinak stated. ā€œIs it more of an oval-shaped zone, which is more consistent with whatā€™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 thatā€™s based on your height as a hitter, no matter how much you sort of squat down or stand up?ā€Ā Ā 

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 definitivelyā€”oval or square and the number of dimensions.Ā Ā Ā 

Todayā€™s Strike Zone Varies by UmpireĀ Ā 

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

A study conducted by The Post based on pitch-tracking data fromĀ TruMediaĀ 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.Ā Ā 

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 byĀ 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.Ā Ā Ā 

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

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.Ā Ā Ā 

Cornell Researchers Working on Fallible AIĀ Ā 

Fortunately, researchers at Cornell University are studying an AI system that better understands that humans make mistakes, according to a recent account inĀ Wired.Ā But instead of being focused on baseball, the AI program named ā€˜Maiaā€™ is focused on chess, especially on the prediction of human moves, including the mistakes they tend to make.Ā Ā 

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.Ā 

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

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.Ā Ā 

If MLB could tap the professorā€™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 theĀ robo-umpire era.Ā Ā 

Read the source articles and informationĀ The New Yorker, fromĀ AP News,Ā Ā fromĀ The Washington PostĀ and fromĀ Wired.Ā 

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