Can Artificial Intelligence Change the Ways that Sports are Covered? Niko Jens Schwann Provides His Input
It’s not often that a professional sportscaster is also well-versed in the intricacies of artificial intelligence (AI). However, this is just what Niko Jens Schwann brings to the table. Hailing from Düsseldorf, and boasting a solid background in digital finance, Mr. Schwann is certainly no stranger to how the latest technologies have begun to impact traditional pastimes such as the NBA.
This brings up an important question. How might the growing presence of AI impact sports coverage? Are there any techniques that have already been employed? Could the days of the human sportscaster be numbered? These are some of the issues that we presented to Niko Jens Schwann during a recent round table discussion. Let’s see what he had to say on the matter.
The Role Of Moore’s Law
We will begin by addressing a somewhat technical principle known as Moore’s Law. Without getting into too many details, this law states that the number of transistors found within a microchip tends to double every two years. Therefore, processing power often follows the same curve. We asked Niko if he felt that Moore’s Law can apply to artificial intelligence:
“I do think that it’s definitely a component to be considered,” he observed. “However, this rapid advancement might not directly translate to the evolution of AI. It still takes time to develop programs, to create algorithms, and to fix any bugs.”
Still, the presence of AI within many circles cannot be overstated. Students have begun leveraging these systems to write essays. Graphic artists use AI to create images from a block of text. It only stands to reason that broadcasters (such as those covering an NBA game) will be tempted to follow the same path.
How Might AI Be Applied?
Let’s use professional basketball as an example. Perhaps a sportscaster wants to know the odds associated with an upcoming game between the Chicago Bulls, and the Boston Celtics. As opposed to scouring the Internet for information, he or she might simply enter a prompt into an AI package, such as:
“Tell me the chances that the Chicago Bulls will win against the Boston Celtics in a game scheduled for 14 April.”
Complex machine learning algorithms will collate massive amounts of big data within mere seconds. This information is then presented to the individual; providing a level of insight that would have been nearly impossible to obtain in the not-so-distant past.
What About Generative AI?
This is another question that we posed to Mr. Schwann due to his extensive university background in subjects such as finance, IT. The subsequent answer came as a bit of a surprise:
“Generative AI is perhaps the one area that could forever change sports coverage as we know it. As these systems are designed to learn from their previous mistakes, it could only be a matter of time before they’re able to provide real-time responses to live NBA action.”
Another takeaway point here is that Generative AI is not nearly as “clunky” as past iterations such as predictive artificial intelligence. Conversations are extremely organic, and it is becoming increasingly challenging to differentiate between Generative AI, and natural human speech patterns.
Is AI The “Crystal Ball” That We Have Been Searching For?
Considering the fact that Niko Jens Schwann is a professional sportscaster, we put this next question rather delicately. We asked him if AI would be capable of rendering his job obsolete.
“Not at all,” he begins. “AI is extremely impressive, and its benefits should never be underestimated. Still, the subtleties associated with live broadcasting cannot be replicated with any system based solely on machine learning.”
He went on to explain that subtle nuances within sports such as basketball may not be noticed by AI. If they are spotted, the algorithms themselves could misinterpret their significance. For example, does a sudden glance from a power forward to a fellow offensive teammate automatically suggest that they will commit to a full-court press? In other words, human cues are understood by humans. AI will have to advance in quantum leaps before it is able to execute such observations in real time.
A Delicate Synergy
So, what can we conclude from the information outlined above? It’s wise to take advantage of the research-based background of Niko Jens Schwann to draw any reliable conclusions.
“I believe that, ultimately, AI will represent nothing. But another tool within the arsenal of any experienced sportscaster. This isn’t entirely different from a writer using an automatic plagiarism checker, or a website programmer using an automated coding assistant. Although artificial intelligence may be able to offer technical support, don’t expect the world of the NBA to become overrun by chatbots any time soon”.
However, it is equally important to mention that the proponents of AI claim that these systems will be ubiquitous throughout numerous marketplaces within the next decade. This leaves us wondering when (and if) its presence will emerge throughout the world of professional sports. It’s therefore better to take the “middle of the road”, and to adopt a patient approach.
