{"id":69069,"date":"2026-03-27T14:31:20","date_gmt":"2026-03-27T18:31:20","guid":{"rendered":"https:\/\/alumni.cornell.edu\/cornellians\/?p=69069"},"modified":"2026-03-27T14:31:21","modified_gmt":"2026-03-27T18:31:21","slug":"robot-ump","status":"publish","type":"post","link":"https:\/\/alumni.cornell.edu\/cornellians\/robot-ump\/","title":{"rendered":"Big Red Researchers Study Major League Baseball\u2019s \u2018Robot Ump\u2019"},"content":{"rendered":"\n

After attending spring training games and more, information scientists are weighing in on the new Automated Ball-Strike System<\/p>\n\n\n\n

Editor\u2019s note: This story was adapted from <\/em>a feature<\/em><\/a> in the<\/em> Cornell Chronicle.<\/p>\n\n\n\n

By Louis DiPietro<\/strong><\/p>\n\n\n\n

For 150 years, Major League Baseball players and fans have accepted that an umpire missing a few balls and strikes is just part of the game. But this spring, MLB is rolling out an artificial intelligence-augmented camera system that will provide a second opinion for players to tap if they think an umpire whiffed.<\/p>\n\n\n\n

This historic change inspired a Cornell research team to study how MLB stakeholders are integrating the Automated Ball-Strike System (ABS)\u2014which tracks pitches in real time\u2014into baseball\u2019s sacred gameplay.<\/p>\n\n\n\n

\u201cWe hear so much about AI influencing political views and fueling polarization, and here\u2019s a case of AI being used as a consensus-building platform rather than creating division,\u201d says information science doctoral student Waki Kamino, MS \u201925. \u201cIt\u2019s such a cool thing to see.\u201d<\/p>\n\n\n\n

\n

We hear so much about AI influencing political views and fueling polarization, and here\u2019s a case of AI being used as a consensus-building platform rather than creating division.<\/p>\nDoctoral student Waki Kamino, MS \u201925<\/strong><\/cite><\/blockquote>\n\n\n\n

Kamino, fellow doctoral student Andrea Wen-Yi Wang, MS \u201925, and other colleagues have spent the last year attending spring training games and umpire trainings, and interviewing league executives, umpires, and fans.<\/p>\n\n\n\n

So far, they and a team of human-robot interaction researchers from the Bowers College have published two papers, and submitted a third, exploring the tension that arises when technological precision is applied to the ambiguities of human decision-making.<\/p>\n\n\n\n

Baseball\u2019s ABS consists of 12 AI-powered Hawk-Eye cameras installed in each stadium and all focused on the strike zone\u2014the roughly 17-inch-wide space between the batter\u2019s knees and chest.<\/p>\n\n\n\n

\"A
The researchers’ fieldwork included attending a Cubs vs. Dodgers spring training game in Arizona.<\/figcaption><\/figure>\n\n\n\n

Trained and honed with umpires\u2019 feedback, the ABS will get called up to the big leagues this year after seven seasons in the minor leagues, where it was used and refined in thousands of games.<\/p>\n\n\n\n

In each game, teams can challenge an umpire\u2019s ball or strike call, with only the pitcher, catcher, or batter permitted to initiate those challenges. However, players must be judicious with challenges\u2014if they lose two, the team is out of challenges for the rest of the game.<\/p>\n\n\n\n

Reviews will take about 15 seconds, and the Hawk-Eye pitch visualization will be shown on stadium video boards and to viewers at home.<\/p>\n\n\n\n

Baseball\u2019s strike zone offered a fascinating test case, Kamino says: How can technology determine balls and strikes when MLB\u2019s very definition of the strike zone is about as clear as a Paul Skenes fastball is hittable?<\/p>\n\n\n\n

Baseball\u2019s ABS consists of 12 AI-powered Hawk-Eye cameras installed in each stadium and all focused on the strike zone\u2014the roughly 17-inch-wide space between the batter\u2019s knees and chest.<\/p><\/blockquote><\/figure>\n\n\n\n

\u201cAmbiguity is core to MLB and to the idea of what makes a good game and a good experience,\u201d says Kamino, who\u2019s published research on social robots and the bonds robot owners form with them and each other. \u201cThe strike zone is ambiguous. It\u2019s a social construct. How do you even automate that?\u201d<\/p>\n\n\n\n

That question struck Kamino two years ago after checking in on her favorite player, Shohei Ohtani, the otherworldly pitcher-slugger for the L.A. Dodgers. With the Dodgers game on, she heard the broadcasters discussing the impending rollout of \u201crobot cameras.\u201d<\/p>\n\n\n\n

\u201cWe should study this,\u201d Kamino texted Wang, whose research explores the use of AI systems to automate unclear definitions and concepts.<\/p>\n\n\n\n

<\/p>\n\n\n\n

\"Andrea
Wang (left) and Kamino fly the Bowers flag with Clark the Cub, the Chicago team’s mascot.<\/figcaption><\/figure>
\n

Then they took a big swing. Kamino and Wang cold-emailed MLB Commissioner Rob Manfred \u201980 and made a pitch: they and their co-researchers wanted to study the ABS to find out how a massive organization with so many stakeholders was implementing and making sense of an AI tool.<\/p>\n\n\n\n

The ILR alum responded within 30 minutes and gave the green light. <\/p>\n\n\n\n

That eventually led to on-field research work last summer, when Kamino and Wang attended ABS-enabled spring training games in Arizona, umpire training camps, and a baseball analytics conference.<\/p>\n<\/div><\/div>\n\n\n\n

<\/p>\n\n\n\n

\u201cIntroducing technology into baseball isn\u2019t like bringing a robot into a manufacturing line,\u201d says Malte Jung, an associate professor of information science who\u2019s Kamino\u2019s advisor and research collaborator.<\/p>\n\n\n\n

\u201cYou\u2019re bringing technology into a game that has a culture and a history, with an audience in the millions. As researchers, what was compelling to us was the opportunity to study human-machine interaction in the wild at a scale we never considered.\u201d<\/p>\n\n\n\n

Implementing automated enforcement systems like the ABS into existing organizations requires complex consensus-building and sense-making among stakeholders, researchers found.<\/p>\n\n\n\n

\n

As researchers, what was compelling to us was the opportunity to study human-machine interaction in the wild at a scale we never considered.<\/p>\nProf. Malte Jung<\/strong><\/cite><\/blockquote>\n\n\n\n

After seven years of development and testing, the ABS appears ready for \u201cthe show\u201d\u2014and that\u2019s a credit to MLB\u2019s careful rollout and willingness to adapt the system based on feedback, researchers added.<\/p>\n\n\n\n

\u201cParadoxically, the ABS was brought in to enforce the rules, but it also changed the rules so that it would be accepted by multiple stakeholder groups,\u201d Wang says. \u201cThis bidirectional relationship between enforcement technology and the rules is less talked about and reveals why we need to study technology from a system\u2019s lens.\u201d<\/p>\n\n\n\n

Additionally, the use of ABS confirms what most baseball fans know but choose not to admit, researchers say.<\/p>\n\n\n\n

\u201cUmpires,\u201d Kamino says, \u201care very good at their jobs.\u201d<\/p>\n\n\n\n

(Top: Photo illustration by Laila Milevski \/ Cornell University. All other images provided.)<\/em><\/p>\n\n\n\n

Published March 27, 2026<\/p>\n\n\n\n

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