The increased use of data and AI in sports has led to controversy of VAR in football, and has been the subject of much debate in recent times, however many athletes across all sports – and officials, have used artificial intelligence (AI) to improve their performance, in a number of different ways.

The National Hockey League (NHL) has announced a partnership with Amazon Web Services (AWS) that will see the latter become the official cloud infrastructure partner of the league. The NHL will turn to AWS specifically in the areas of artificial intelligence and machine learning.
 

Sports Data Labs, Inc. (SD Labs), an award-winning leader in collection, analysis and distribution of real-time Human Data from on-body sensors and sensing systems in professional sports and digital health, announced today the publication of a pioneering study in the biomedical journal Digital Biomarkers. It provides the first published evidence for real-time capture, digital processing, and heart rate display from medical-grade sensors in live professional sports competition.

It is not hard to understand why people are receptive to a vision of the future in which AI’s primary impact is to augment human activity. At an elemental level, this vision leaves us humans in control, unchallenged at the top of the cognitive food chain. AI is, according to this line of thinking, just one more tool we have cleverly created to make our lives easier, like the wheel or the internal combustion engine. But AI is not just one more tool, and uncomfortable reconceptualizations are on the horizon for us.
 

Microsoft has developed an artificial intelligence for its Teams videoconferencing software that aims to put people presenting a remote talk more at ease by highlighting the most positive audience reactions.

It took about 50 years for computers to eviscerate humans in the venerable game of chess. But one artificial intelligence program is taking a few steps backward, to appreciate how average humans play—blunders and all. A chess program that learns from human error might be better at working with people or negotiating with them.

With the proliferation of data in sports, bookmakers have begun taking full advantage of its value by providing unique in-game betting opportunities, offering bet simulation tools that increase the frequency of bets, and creating attractive odds that increase betting volume.

MIT researchers have developed a type of neural network that learns on the job, not just during its training phase. These flexible algorithms, dubbed “liquid” networks, change their underlying equations to continuously adapt to new data inputs.

Dialogue is hampered by an information gap between creators of AI technology and policymakers trying to regulate it. Knowledge building is critical to set a framework of ethics and norms in which AI can innovate safely.

At the heart of the development of AI appears to be a search for perfection. And it could be just as dangerous to humanity as the one that came from philosophical and pseudoscientific ideas of the 19th and early 20th centuries and led to the horrors of colonialism, world war and the Holocaust. Instead of a human ruling “master race”, we could end up with a machine one.