From Saving Rhinos To Enriching Cycling: How AI Is Enhancing Sports & Anti-Poaching Efforts

Increasingly, conversations around AI don't seem to be entirely about marketing hype, but something that's steadily increasing behind the scenes in every aspect of our 21st century world.

There is no aspect of our individual or collected lives which isn't shaped by an AI of some sort. Uncontrolled and unsupervised, AI can sound scary -- but harnessed carefully, its benefits outweigh its negatives. At least for now.

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From powering next-generation sporting experiences to leading endangered animal conservation efforts on the frontline, NTT's CEO Jason Goodall gives us the low-down on how AI is increasingly playing an indispensable role in powering our new reality. Excerpts from our interview follow below:

1) What are some of the AI-enriched viewing experiences in popular sport right now?

The world's biggest cycling race, the Tour de France uses an AI-powered machine learning model to combine historical data from past events with live race intelligence, building algorithms that can predict real-time race events.

Similarly, NBA (basketball) and MLB (baseball) use AI to drive fan engagement, such as setting up competitions with supporters to predict where shots are going. These leagues are also using AI analytics to drive broadcast graphics, such as player and team heatmaps during NBA matches, as well as chatbots operating through Facebook Messenger to answer fan queries regarding team stats/rosters and franchise history.

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In golf, the PGA Tour uses AI to digitally transform content to reach supporters across the world. Using AI, broadcasters have instant access to information, which they can use to find patterns and present huge amounts of content in a more structured manner. In motor racing, AI is using deep learning to create self-driving cars and is also helping to enhance safety measures. These are just a few examples to give you an idea about how AI is transforming sport.

2) What are some of the challenges in powering AI-enriched viewing experiences in sport?

There's currently a big challenge around data ownership at sporting events. Typically, the event organisers will claim ownership, but for most league-based sports, the teams have a significant say in how the event organiser operates as, understandably, they don't want performance data potentially benefitting competitors. It means that, so far, no-one is consistently tracking athlete positions, particularly in team sports.

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There also exist hurdles in GPS accuracy, and the inability to work indoors or acquire 100% field coverage in covered seating stadiums. In fact, our research revealed over half (55%) of millennials want more in-stadium experiences, but almost three-quarters (73%) say poor connectivity at a sporting venue reduces their event enjoyment. To address this, there have been numerous pilots on various time-of-flight solutions, but none have become the de-facto standard in any particular sport.

3) In future, what other tech-fueled viewer experiences will be available?

Generally, we see more athlete tracking and AI-driven analytics being used across broadcast to engage supporters, along with more sophisticated AI-powered experiences on social media platforms to push highly-targeted micro-content.

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The Japanese government is developing an AI-based spectator guide system to help spectators navigate venues during next year's 2020 Tokyo Olympic Games. The model will gather crowd flow information and ping spectators notifications every 30 minutes once an event has finished, guiding them down less-crowded exit routes. Exiting a stadium or venue after an event is often one of the most frustrating parts of attending a live event, so it's great to see technology being used to improve the fan experience in this manner.

Smart ticketing has the potential to take connected stadiums to the next level, letting fans change seats from game to game, depending on their preferences. For example, a football supporter could relocate to a more energetic section of the stadium based on AI analysis of crowd noise.

4) Apart from sports, where else is AI helping solve a problem?

Artificial intelligence is being used across many of our world's cities to create connected urban hubs. For example, we are currently working with the City of Las Vegas around intelligent technology solutions -- including advanced sensors, machine learning, and artificial intelligence. This intelligence enables the city to quickly and efficiently manage day-to-day operations, such as providing drivers with recommendations on traffic so they can quickly react and change their route. AI tech allows emergency services to respond to incidents faster, and can also be used to inform architectural plans for better city infrastructures.

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In wildlife conservation, artificial intelligence and machine learning are being used to dramatically reduce the illegal poaching trade. In South Africa, we have partnered with Cisco to almost entirely eliminate rhino poaching in a private wildlife reserve. The Connected Conservation project uses a sophisticated mix of sensors, CCTV, biometrics, and Wi-Fi to detect patterns of irregular behaviour when people enter and exit the park. It has cut rhino poaching by 96% since its inception.

All responses attributed to Jason Goodall, CEO, NTT