It’s mid-spring, which means that the Triple Crown is already on the way. The Kentucky Derby has already concluded, with Sovereignty taking the win.
Now, we shift to the second leg of the three races: the Preakness Stakes. If you are searching on how to bet on Preakness Stakes click here.
Racing can be great fun, but there is a core problem with the pursuit that often goes undiscussed: Championship horses get injured all the time.
They perform like professional athletes but without the ability to communicate pain or discomfort. Often, they meet race day under the influence of painkillers that allow them to perform in subpar health.
AI has the power to change this by detecting injuries and optimizing training with animal health as a priority. Advanced monitoring systems using machine learning algorithms can now track subtle gait changes, thermal patterns, and stress indicators that might escape even experienced trainers.
These technological innovations offer hope for a future where the excitement of racing can continue while prioritizing equine welfare.
AI Tech Overview
While AI is far from perfect, it excels consistently at data analysis and interpretation. It’s to this extent that it can be used to help trainers ensure the health of their horses. This powerful combination of sensors and algorithms creates unprecedented visibility into equine well-being.
While there are a variety of ways this technology can be introduced to care routines, it generally hinges on pairing physical devices with software. Horses will be harnessed with wearable data-taking technology. A commonly used tool is the Equestic SaddleClip.
It takes a ton of data on how the horse is moving, including stride length, symmetry, and impact forces that would be impossible to quantify through observation alone.
This information can be used to improve efficiency and help trainers refine their routines. The SaddleClip can also observe early indications of injury. Even a slight change in the horse’s gait often indicates that something is wrong, allowing for intervention before minor issues become career-threatening problems.
AI in Veterinary Medicine
AI healthcare integrations are still in their relatively early stages. However, artificial intelligence’s ability to interpret data points like X-rays has already proven very promising. But why, when humans can do the same thing? AI interpretation of medical information tends to be significantly quicker than what people are capable of—without sacrificing accuracy.
Human participation in the diagnosis and treatment process is still completely mandatory. However, AI assistance can accelerate the diagnosis and treatment process. In healthcare—be it for horses or for humans—timing is incredibly important.
Improved Breeding
AI systems analyze genetic markers across thousands of horses. They identify optimal pairings for specific traits. These systems evaluate bone density factors. They assess muscle fiber composition. They compare genetic predispositions to specific injuries. Breeders receive detailed compatibility reports.
The technology examines generations of performance data. It identifies patterns in successful bloodlines. AI prediction models calculate racing potential. They also estimate injury risks. This contributes to stronger bloodlines.
It helps reduce hereditary weaknesses. Horses bred using AI-assisted selection often develop more durable leg structures. Their cardiovascular systems show greater efficiency. Recovery times between races decrease.
The data helps breeders make more informed decisions. AI assists in creating horses that maintain peak performance. These animals often experience fewer racing-related injuries. The technology continues to improve each year.
Understanding Animals Better
AI and other digital technologies also have the ability to help us better understand animals. That’s important because it’s often misinterpretations that lead to some of the most significant animal rights violations. The way horses are housed is a common example.
Horses have a higher level of intelligence than many people have previously assumed. Dr. Kraig Kulikowski, an equine veterinarian, reflected on this fact while testifying before the New York State Senate: “A 2-year-old horse is equivalent to a 6-year-old human; a 3-year-old horse is equivalent to a 9-year-old human.”
It’s almost funny that we need digital technology to see something that should be self-apparent. Horses are herd animals. In the wild, they might travel up to 20 miles a day. Spending more than 90% of their life in a 144-square-foot room goes against their nature.
And yet despite these ethical failings, the world of horse racing is primarily filled with people who love not just the game but the animals that make it great. AI and other digital tools can help ensure that horse racing continues as a safer, more ethical practice for decades to come.
The Future is Uncharted
Of course, with all of that said, it’s difficult to say exactly where AI will take us in the years to come. Certainly, artificial intelligence has already been integrated into our daily lives to a great extent—whether we like it or not. But the results are often mixed.
AI can be a helpful tool in improving the lives of horses. However, it’s not enough. True change will come through human intervention and public sentiment. Remember that facilitating better conditions for horses takes more than knowing what needs to be done. It also takes time, money, and effort—things that are rarely spent without reason.
Horse racing fans can play their part by advocating for better animal treatment.
