AI's impact on baseball and beyond changes the world

Baseball heavily revolves around pitchers, particularly starters. The Korean movie “Perfect Game” exemplifies this, showcasing the legendary duel between pitchers Choi Dong-won and Seon Dong-yeol. In their real-life match on May 16, 1987, they threw 209 and 232 pitches, respectively, totaling over 200 each.

Today, it's rare to find a Korean pitcher throwing 100 pitches in a game. As of Thursday, only 19.4% (96 of 494) of the games in Korea's professional baseball league saw starters reach this mark. In MLB, starters threw 100 pitches in just 11.5% (171 of 1,490) of the games during the same period. As recently as 2010, about half (49.7%) of MLB starters threw over 100 pitches before leaving the mound.

Big data is why starting pitchers began throwing fewer pitches. In his 2017 book Everybody Lies, U.S. data scientist Seth Stephens-Davidowitz noted that baseball was the first field to have comprehensive data sets on almost every element, with dedicated smart experts willingly spending their entire lives analyzing them. He added that AI developed by these experts determined that it is inefficient to keep starting pitchers on the mound for too long.

AI has also shifted baseball's focus from throw-hit-run to just throw-hit. Data analysis shows that plays like stolen bases or base running are less effective than commonly believed. Instead, there has been an increase in plays determined between the pitcher and hitter, such as home runs, strikeouts, and walks.

With AI streamlining baseball games, some have lamented a loss of fun, leading to declines in both stadium attendance and TV viewership. To reintroduce excitement, MLB is considering measures like restricting pitching time, enlarging bases, and potentially mandating starting pitchers to throw for at least six innings unless they have exceptional circumstances like injury.

Davidowitz's book highlights baseball as a pioneering force in the changing landscape of various fields. He notes that Sabermetrics, the statistical study of baseball, set a precedent for data analysis across industries. Interestingly, Sam Altman, founder of OpenAI, the organization behind generative AI ChatGPT, has roots as a baseball card collector, with players' records written closely all over the cards, underscoring the potential influence of baseball's data-driven approach.

When introducing ChatGPT-4o, which sees, listens, and speaks like a human being, Mira Murati, OpenAI's Chief Technology Officer, emphasized her focus on improving ChatGPT's functionality more seamlessly for easier user interaction. Similar to baseball, AI aims for smoother and more seamless experiences.