Big Red Researchers Study Major League Baseball’s ‘Robot Ump’

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Editor’s note: This story was adapted from a feature in the Cornell Chronicle.

By Louis DiPietro

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.

This historic change inspired a Cornell research team to study how MLB stakeholders are integrating the Automated Ball-Strike System (ABS)—which tracks pitches in real time—into baseball’s sacred gameplay.

“We hear so much about AI influencing political views and fueling polarization, and here’s a case of AI being used as a consensus-building platform rather than creating division,” says information science doctoral student Waki Kamino, MS ’25. “It’s such a cool thing to see.”

We hear so much about AI influencing political views and fueling polarization, and here’s a case of AI being used as a consensus-building platform rather than creating division.

Doctoral student Waki Kamino, MS ’25

Kamino, fellow doctoral student Andrea Wen-Yi Wang, MS ’25, and other colleagues have spent the last year attending spring training games and umpire trainings, and interviewing league executives, umpires, and fans.

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.

Baseball’s ABS consists of 12 AI-powered Hawk-Eye cameras installed in each stadium and all focused on the strike zone—the roughly 17-inch-wide space between the batter’s knees and chest.

Trained and honed with umpires’ 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.

In each game, teams can challenge an umpire’s ball or strike call, with only the pitcher, catcher, or batter permitted to initiate those challenges. However, players must be judicious with challenges—if they lose two, the team is out of challenges for the rest of the game.

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

Baseball’s strike zone offered a fascinating test case, Kamino says: How can technology determine balls and strikes when MLB’s very definition of the strike zone is about as clear as a Paul Skenes fastball is hittable?

Baseball’s ABS consists of 12 AI-powered Hawk-Eye cameras installed in each stadium and all focused on the strike zone—the roughly 17-inch-wide space between the batter’s knees and chest.

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“Ambiguity is core to MLB and to the idea of what makes a good game and a good experience,” says Kamino, who’s published research on social robots and the bonds robot owners form with them and each other. “The strike zone is ambiguous. It’s a social construct. How do you even automate that?”

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 “robot cameras.”

“We should study this,” Kamino texted Wang, whose research explores the use of AI systems to automate unclear definitions and concepts.

“Introducing technology into baseball isn’t like bringing a robot into a manufacturing line,” says Malte Jung, an associate professor of information science who’s Kamino’s advisor and research collaborator.

“You’re 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.”

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

As researchers, what was compelling to us was the opportunity to study human-machine interaction in the wild at a scale we never considered.

Prof. Malte Jung

After seven years of development and testing, the ABS appears ready for “the show”—and that’s a credit to MLB’s careful rollout and willingness to adapt the system based on feedback, researchers added.

“Paradoxically, 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,” Wang says. “This bidirectional relationship between enforcement technology and the rules is less talked about and reveals why we need to study technology from a system’s lens.”

Additionally, the use of ABS confirms what most baseball fans know but choose not to admit, researchers say.

“Umpires,” Kamino says, “are very good at their jobs.”

(Top: Photo illustration by Laila Milevski / Cornell University. All other images provided.)

Published March 27, 2026

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