Is college basketball becoming just another content farm? The final score – Harvard 73, Cornell 54 – tells you what happened in Ithaca, New York on Saturday. But the fact that this game report was generated by an AI, using technology from Data Skrive and data from Sportradar, tells you something far more unsettling about the future of sports journalism, and frankly, all news. The real story here isn't Tey Barbour’s 30 points, it’s the creeping automation of storytelling, and what that means for the human element we expect – and deserve – from coverage of events we care about.
Crimson Dominate, But the Real Game is Changing
Harvard’s victory over Cornell was, by all accounts, a solid performance. Barbour led the Crimson (15-10, 8-3 Ivy League) with a dominant showing, supported by Robert Hinton’s 16 points and six rebounds, and a contribution of 10 points from Thomas Batties II. For Cornell, Anthony Nimani provided a spark off the bench with 18 points, while Jake Fiegen and Cooper Noard each added 11. These stats, meticulously tracked by Sportradar, are the raw material for this AI-generated report. But reducing a game to these figures, even with a few sentences strung together by Data Skrive’s algorithms, feels…hollow. It’s the difference between knowing that something happened and understanding why it mattered.
Source material: CBS Sports.
The Rise of Algorithmic Reporting
This isn’t some distant, futuristic threat. The Associated Press has been experimenting with automated journalism for years, initially focusing on earnings reports and minor league baseball. The logic is simple: these are high-volume, low-margin stories where human reporters are expensive and AI can deliver speed and efficiency. But the scope is expanding. Now, even Ivy League basketball is fair game. STATS LLC also holds copyright on the content, further illustrating the commercial forces at play. The AP claims this frees up human journalists to focus on “more complex” stories. But what defines “complex”? And who decides which stories are worthy of human attention? The danger isn’t just that we lose jobs; it’s that we lose nuance, context, and the unique perspectives that only a human observer can provide.
Beyond the Box Score: What Gets Lost in Translation
Consider the details missing from this AI-generated account. Was there a crucial momentum shift fueled by a particularly energetic defensive play? Did a key player overcome personal adversity to deliver a standout performance? Was the atmosphere in the arena electric, or subdued? These are the elements that transform a game from a collection of statistics into a compelling narrative. An algorithm can tell you Hinton shot 2-for-5 from beyond the arc; it can’t tell you how those shots felt, or the impact they had on the flow of the game. It can’t capture the exhaustion on the players’ faces, the frustration of a missed call, or the joy of a hard-fought victory. These are the things that connect us to the game, and to each other.
The Future of Sports Coverage – and Beyond
The AP’s use of AI isn’t about replacing journalists entirely, at least not yet. It’s about maximizing efficiency and minimizing costs. But this trend has implications far beyond sports. As AI-powered writing tools become more sophisticated, we can expect to see them deployed across a wider range of news categories, from local politics to financial reporting. The question isn’t if this will happen, but when and to what extent. My prediction? By the end of 2027, you’ll be routinely reading AI-generated summaries of local government meetings, school board decisions, and even preliminary crime reports. The challenge won’t be distinguishing between human-written and AI-written content – it will be finding reliable sources of any content that hasn’t been optimized for clicks and ad revenue, and stripped of its soul. Are we prepared to live in a world where the news is simply a product, churned out by algorithms with no stake in the truth?
