Artificial intelligence can be the breakthrough that can allow for limitless possibilities in preventing injuries for athletes. Using AI to help with injury prevention means finding patterns that can allow players and teams a better understanding of why injuries happen and how to prevent them. Researchers from the University of Galati said, “By exploring the application of machine learning (ML) and deep learning (DL) techniques… [this] highlights AI’s ability to analyze complex datasets, detect patterns, and generate predictive insights that enhance injury prevention strategies.” These tools are specifically designed for searching through lots of data to find patterns in what causes these injuries. These patterns are key to being able to predict and prevent further injury which would otherwise be unnoticed by human observers.
By taking a more proactive role it means that there will be less injuries overall and quicker recovery times.
NBA commissioner Adam Silver, is a big proponent of using AI to help prevent injuries as he said, “I’m hopeful that by looking at more data, by looking at patterns, this is one area where AI — people are talking about how that’s going to transform so many areas — the ability with AI to ingest all video of every game a player’s played in to see if you can detect some pattern that we didn’t realize that leads to an Achilles injury.” This comes after Indiana Pacers star Tyrese Haliburton was one of many players to end their season due to a ruptured Achilles.. This was a record breaking season for Achilles injuries because there were seven as opposed to the previous seasons having a record of four.
Similarly, the NFL has also devised a system using AI for proactive injury prevention. This is in the form of the Digital Athlete, described by the NFL as “an injury prediction tool that leverages data and artificial intelligence to help clubs keep players healthy and performing at their best on the field.” With this new system, all 32 teams have access to the Digital Athlete which uses video and data relevant to NFL players’ health to find when they are most vulnerable to injury. Allowing the staff of the teams to determine the best course of action to prevent any injuries proactively. Preventing these injuries in the form of specialized training and recovery plans for the athlete that could take these athletes’ health to a whole new level. The NFL has already begun using the Digital Athlete by introducing new rules such as the Dynamic Kickoff. This kickoff closes the distance between the players which decreases movement and speed on contact, in turn, reducing injuries.
There are many concerns that stem from using AI. Researchers at the University of Galati said, “AI faces challenges related to data quality, model interpretability, and ethical concerns. The accuracy of AI predictions depends on the quality and completeness of the data, and the complexity of AI models can make them difficult for practitioners to interpret.”
Having a small or incomplete sample size can make it difficult for AI to correctly predict and recognize patterns leading to it doing more harm than good.
Another point that critics make is that the rapidly innovating AI scene can make some studies outdated very quickly, ultimately making it not worth the investment. Ethical concerns are also a big issue as these models draw upon a huge number of athletes’ private medical data. There are policies put in place such as the Health Insurance Portability and Accountability Act which ensures the athlete’s privacy by making them anonymous.
With the continued use of AI in major sports, there is a good chance that it could make it down to lower level sports and become much more widespread. As this happens, it could even start to creep into people’s personal nutrition with the analysis of their sleep patterns or nutrition creating limitless opportunities to improve our health.
