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Embracing Innovation: Is Artificial Intelligence About to Change the Game? 🧠

The rising prominence of AI across new industries has some worried, but the conclusion is the same. Embraced openly and responsibly, these innovations have the ability empower us.

In recent weeks, the rise of artificial intelligence seems to have taken hold of our imagination, quite literally.


From creating an entirely fictional podcast with Joe Rogan and Steve Jobs, generating images from text prompts thanks to the public launch of DALL-E, creating blog content via applications such as Jasper AI (which has recently raised $125m Series Afunding round), to creating ‘digital humans’ of superstar creators like the NBA’s Luka Doncic that can do social media takeovers and develop their own personalities. Nothing appears to be off the table.

The phenomenon, and perhaps the explanation behind why there has been so much fixation upon it, is that it challenges our assumptions of what can be made possible through the advancements of computing. For me, the was best explained by Shaan Puri on his podcast, My First Million.


“The last 10 years have been what I'll call left brain AI. You have your left brain and your right brain - left brain is your analytical brain and that's what artificial intelligence could do.” This, Puri explains, includes concepts such as big data, machine learning - even computers learning to play chess and eventually beating the best players.

“That's where we've been and it's also what we expected. That sounds like the type of thing that super-computer should be able to do,” he explains.

“Then [there] was this game changer where it changed into right brain AI - your creative brain. So, now you’ve got this right brain AI that's doing creative images, creative texts, creative videos, it's writing blog posts, it's making paintings, it's making music, it's making podcasts,” he continues. Ultimately, the ability for it to now do both sides is the big change. “That's the big holy $*!% moment.”

This, as new innovations often do, has stoked a level of fear among a new set of workers about being entirely displaced. However, is this justified?


Perhaps, for some that are unwilling to adapt. However, these technologies are not replacements, they are tools that still need to be wielded by a master craftsmen. The skillset asked of the human may change somewhat, but the best at utilising these tools at their disposal will be able to reach into even higher echelons of possibility. It was no different with the introduction of computers or the internet.

This is already true for many AI tools that have been implemented across industry. And sport is no exception. Here’s a few examples;

  1. Fan Experience Many sports teams are now using AI to improve fan experiences. For example, teams may use systems to track the movements of fans in the stadium. This information is then used to improve the layout and traffic flow. This has not replaced the need for stewards or safety personnel at the stadium, but it has assisted them with information to make better informed decisions.

  2. Coaching & Tactics AI has also allowed tracking devices to do much more than simply measure distance and speed. Within the NBA, AI is able to process data collected from these tracking devices understand when specific plays are underway and can examine which actions worked and which didn’t. This informs coaches and enables them to eliminate bad plays and to get the most out of their top players.

  3. Human Performance With Zone7, I have even been fortunate enough to see first-hand how their platform is able to process performance data and provide actionable insight for sports science staff. Again, the AI acts as a tool to better inform the human decision-making process, rather than making it for them. To explain in layman terms (and also in the only way I know how), the AI is able to process performance data from different devices (GPS, wearables, force plates, etc.), compare it with an enormous data lake of millions of hours of playing and training data, and then flag patterns within that data which suggest a higher risk of injury and recommended courses of action to reduce that risk.

The same is true for many other disciplines, too. As Ed Smith, the former England cricket selector has summed up in the title of his recent book, ‘Making Decisions; putting the human back in the machine’. And, as he wrote in the Financial Times, the computer, or algorithm, or AI, is simply an additional form of intelligence on which to call upon.

“Selection and decision-making are often framed in terms of ‘art versus science’, with the assumption that, in our digital age, ‘science’ is increasingly marginalising the human factor. But making decisions — and this applies in any area, not just sport — demands weighing and reconciling different kinds of information, and drawing on differing types of intelligence.”

“No system, in other words, is so good that it can survive without good judgment. You can’t box off a perfect process. Understanding the data can embolden better risk-taking, but it can’t absolve decision-makers from responsibility.”


Until the destination is no longer our decision, we, the human, will remain in the driving seat (at least metaphorically).

 

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