The AI Injury Conundrum

**Brian** (0:00)
How's everybody doing? This is Brian, welcome to another Saturday Conundrum. Appreciate y'all being here. And this week, I was inspired to work on this conundrum. As usual, usually there's something that sort of triggers me to like want to go in one direction or another. This week, it was sports. More specifically, it was, I happened to see an injury update about Lindsey Vonn. Now, quickly for anybody who doesn't know, Lindsey Vonn is highly decorated Olympic downhill skier.
Who famously in this last Olympics, she was 40 at the time I think of the Olympics, tore her ACL, had mere days to rehab, came back to the Olympics, actually did OK in the qualifiers, but only 13 seconds into her first official run. She had a devastating crash where she broke multiple bones in her leg. And at least as of the report I said, she's still on crutches, and has had five surgeries so far. So why am I bringing up Lindsey Vonn? Well, this is about injury, specifically sports injury, and how AI is going to continue, it already does, but continue to play a huge role in this area. So much so that we can imagine a future where AI is able to accurately predict because of mountains of data about tiny tears or tiny adjustments in someone's gait. As an athlete that would predict with accuracy, we can assume in time, I mean, not right now, but in time, predict with accuracy what's going to happen. It's going to be like the ultimate preventative maintenance for an athlete. But this is where it gets really tricky, because we can imagine a time, I think it's okay to imagine a time where AI can do this. We already know that sports data is such a huge industry in itself.
AI is only going to amplify that.
But the question becomes, at what point is it the job of the sports team, the institution, the league, whatever you want to call it, to protect an investment? Because let's be honest, if you're on a major sports team, you're an investment versus allowing an athlete to take their own risks and be in charge of their own body. Because as many stories as we know of The Bloody Sock, we know of amazing failures only to be followed by amazing successes.
We see both sides of it. We see the stories. And what makes a better story than a comeback story, right? From something like this. By the way, in the update I saw, Lindsey Vonn thinks she might try to race again and may even try for the Olympics, which would make her 44
That's a different story, but that just shows you the mindset of your top elite athletes and not just top athletes in general, usually. Okay, so what does this mean? Well, I want to read the intro to this conundrum because I think it will lay it out better than I probably did. But I'm just letting you know where my brain was and how I came to this particular conundrum. But I really, really like this one. I say that a lot. I know that they're all kind of like my own little kids, these conundrums because I work hard on them. But I really like this one because it's easy to envision the day where all of this is true, where AI can predict with accuracy, like extreme accuracy that somebody's adjustment in their gait is going to lead to, let's say, an ACL tear or whatever it might be in their sport. Then what do you do with that data? Who ultimately gets to make the decision about somebody else's body, their ability to compete, and let's be honest, at the upper, upper levels, their likelihood, because it could be the difference between somebody sitting out or someone playing a full season, getting, let's say, scholarships. Scholarships turn into an NFL contract, which turns into millions of dollars for them, that person and their family. There's a lot here. I'll stop so I could read the intro, and then of course, we'll turn it over to our two AI co-hosts who will take us the rest of the way.
All right.
This one's called the AI injury manager. Sports have always asked athletes to live near the edge of risk. A sprinter races on a tight hamstring, quarterback returns after a hard hit. A pitcher says his arm feels fine because the season, the scholarship or the contract depends on him being available. Today, AI is already changing the timing of that decision. But the future impact of AI on sports industries will be much greater. Instead of reacting after pain appears, teams and leagues can begin seeing injury risk before the athlete feels it. Model might notice a tiny change in gait, fatigue, sleep, joint stress, reaction time, or recovery patterns, and predict that a player is entering the danger window. That sounds like protection. It also changes what it means to compete. If a system can see the risk before the athlete can, then the athlete's own confidence may no longer be enough. The most important moment in a career could be decided before anything has actually gone wrong.