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Artificial Intelligence is an upcoming technology that is currently being implemented in many industries. Also in the sport industry, AI is being implemented in many more places than before. To get a good insight in where AI would be interesting to implement, we need to analyse the entire sporting industry first. The sport industry can be divided into two sections: media & fan experience and management & operations.

The media & fan experience include things such as news & content, eSports and sport betting. You can divide this section even further into post-game analysis and talent ID & selection

Post-game analysis retrieves its data from wearables and game equipment and AI would be interesting to implement in analysis & feedback, recovery and injury management.
In the talent ID & selection section, sensory data is used from peripheral devices and AI could be used in talent identification & selection.

Sponsoring, merchandise, venues, events & ticketing are all parts of the management & operations section of the sports industry. This section can also be divided further into in-game activity and pre-game preparation.

In-game activity gets its data from other systems and when implementing AI in this region, you have to think about umpiring and specialist coaching.
Machine & deep-learning is used to retrieve data for the pre-game preparation section. AI can be implemented in things such as training & coaching, nutrition, injury management, strategic and tactical game planning and team selection.

As described above, the sporting industry is a very interesting industry with several different aspects to consider. There are many different stakeholders in the industry and all off them could potentially benefit from more use of AI. There are still a lot of things that need to be explored further but the use of AI in sports is very promising.

References

Rizzoli, A. (2022, October 3). 7 Game-Changing AI Applications in the Sports Industry. V7. Retrieved October 11, 2022, from https://www.v7labs.com/blog/ai-in-sports

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The world as we know it fifty years ago is not the world we live in today. The digital world is changing rapidly, and the use of Artificial Intelligence (AI) is becoming more dominant every day. Artificial Intelligence allows machines to model and improve the capabilities of humans. Think about self-driving cars or smart assistants like Siri or Alexa but platforms like Spotify and Netflix also use AI to predict what music or film recommendations you would enjoy as well. The use of AI and the possibilities the technology has are very promising but there are also some important downsides that need to be thought trough before implementing AI everywhere.

The first problem with AI is that when you replace human jobs with AI models, you delete the human aspect of the job. For example, AI is capable of doing the same things a judge does when convicting someone of a crime. AI can weigh various factors and determine whether or not a person is guilty, just like a judge would do. However, who determines if the decisions made by the model are ethical and just? A second problem that occurs when you would implement AI in more places is who would be responsible for the mistakes that the machine makes? AI is a self-learning algorithm and sometimes even the programmer itself does not understand the decisions the technology makes. Would it then be fair that the programmer is still responsible for all actions made by the model when they do not understand the actions themselves? These are only two downsides of the use of AI but there are many more that need to be thought through before just simply implementing AI in every place that it might be useful in.

Ethics and AI

References:

Harris, D., Glover, E., & Sawtell-Rickson, J. (2022, September 19). What Is Artificial Intelligence (AI)? How Does AI Work? Built In. Retrieved October 11, 2022, from https://builtin.com/artificial-intelligence

Who Am AI to Judge? (2019, January 23). EGF. Retrieved October 11, 2022, from https://egfound.org/2019/01/who-am-ai-to-judge/

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