The sports world has been dealing with the human error of referees and umpires for decades—it’s pretty much tradition at this point. But with technology that can assess the game more accurately, some athletes are ready to push the people calling balls and strikes off the field in favor of technology.
The news: On Tuesday, Chicago Cubs second baseman Ben Zobrist, one of the most vocal supporters of turning over baseball rulings to software, used an argument with the umpire as a chance to advocate for a change in the league.
“That’s why we want an electronic strike zone.”
—Zobrist, shortly before getting his first career ejection
The comment reinvigorated a long-standing debate over automation in sports.
You’re out! As you watch baseball on television, a graphic is often overlaid on the action that shows in real time whether a pitch is a ball or a strike. But human umps are still making the calls on the field based on nothing but their own eyes. Increasingly, viewers and players would rather have the technology take over.
The opponents: As Jason Gay wrote in the Wall Street Journal, “Humanity—and all the imperfections that go with it—is an integral part of sports, even when it means officials making costly mistakes. Instant replay has its upsides, but has also turned into a soul-crushing time suck.”
A collaborative solution: Professional tennis could be an example for baseball to follow. Rather than firing all the umpires, it has decided to embrace human-software collaboration, giving the final word to the “Hawk-Eye” program on disputed in-or-out rulings. The program is quick and accurate, and it even evokes an immediate response from the crowd. If baseball can find a system like this, it may be able to find a way for the traditionalists and tech fanatics to live in harmony on the diamond.
This story first appeared in our future of work newsletter, Clocking In. Sign up here.
This artist is dominating AI-generated art. And he’s not happy about it.
Greg Rutkowski is a more popular prompt than Picasso.
What does GPT-3 “know” about me?
Large language models are trained on troves of personal data hoovered from the internet. So I wanted to know: What does it have on me?
An AI that can design new proteins could help unlock new cures and materials
The machine-learning tool could help researchers discover entirely new proteins not yet known to science.
DeepMind’s new chatbot uses Google searches plus humans to give better answers
The lab trained a chatbot to learn from human feedback and search the internet for information to support its claims.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.