It is safe to say that not in one hundred years will robots outperform future Ronaldos on the football fields. Not even with all the super-state-of-the-art AI integrated in those future robots. But does that mean AI can’t help next-generation football players increase their genius and perfection even further? FC Barcelona’s ‘Innovation Hub’ is seriously betting on AI. “A Great Sports Laboratory for the Future of Sports”, they brand themselves on their website. There are more top athletes at the Hub than anywhere else – 2500 of them, from different top sports sectors and in ages between 8 and 30. Probably no other place in the world is generating and analyzing more data points on excelling athletes. From sports performance points to each sportsperson’s personalized food intake. From recovering time spans after-action or injuries to sleeping habits. Hamstring injuries are a special case worth mentioning. Many footballers are confronted with them. It can keep them off the fields for frustratingly long. Outside the world of top sports, in the banal world of us normal earthlings, hamstring injuries are never meticulously studied. They are simply not a big deal: we can go and work at the office with such an injury.
For footballers though, they are a serious drawback. Probably there is no place with more in-depth research and knowledge on hamstrings than Barcelona Innovation Hub. They have the ultimate target groups for research, generating more relevant data points than anywhere else. And nowhere is the desire for speedy recoveries ̶ and therefore the urge to obtain knowledge ̶ felt more intensely.
“Probably no other place in the world is generating and analyzing more data points on excelling athletes.”
Of course, it is not exclusively about hamstring data at the Hub. All of the top athletes’ data points are mined and thoroughly analyzed in order to reveal their hidden meanings. AI’s algorithms play the leading role in this and will continue to do so. They are indispensable for analyzing. Of course, data generation and analyzing have always been part of top sport studying. Numbers of passes, shots, goals and tackles are systematically collected and analyzed since the nineteen-nineties. Later also followed by data on field positioning and other team dynamics. In this century, GPRS monitoring and drone use are making this kind of data generation even more expansive and meticulous – and the AI-analysis more sophisticated. In the new century, much more body-physical information is also being added to the ocean of data: speed, acceleration power, collision power, heartbeats and recovery patterns. Both on the playing fields and at the training sessions. With the internet of things on the rise, combined with more sophisticated sensor-wearables, the monitoring of all relevant data will continue to increase. And AI will be in the center of it to analyze patterns.
It will come with frictions circling around a new trade-off. Must footballers allow the data analysts of FC Barcelona Innovation Hub to record everything they eat? In order to assess their optimal food intake? Will they be willing to wear sensor-woven pajamas in the privacy of their bedrooms to monitor their heart rate and sleeping patterns? All for the sake of further sports performance optimization, of course. Or, for those who sleep naked: will an implanted body-chip be an option? Or even and obligation? For sure it infringes on privacy. But the data can also add statistical negotiation power when it comes to transferring a promising athlete to a new club. His or her physical sustainability rates would be settled with much more solid accuracy. Here we meet, not for the first time, the fragile balance of AI as empowerment (better performances) and AI as a creepy invader into the intimacies of our lives.
What starts with top sportspersons, will trickle down to everybody else, recycled to fit the lives of the masses. When AI algorithms increasingly encircle our lives, we will all encounter the same frictional balance as the BCN athletes are now confronted with: better performances and services versus deeper intrusions in the privacies of our lives.
With AI nestling itself at and above (through GPRS drones) the sporting fields… With AI nestling itself in each training session, and in the food intake, sleep patterns and heartbeats of each top athlete, it is obvious that FC Barcelona is not only in sports business anymore but also in the data business. Yes, the sportsmen and women will continue to steal the show on the champion fields and amaze us with their actions, incomes and transfer prices. But underneath it, all their data, superiorly analyzed by AI, will be sold as well. To other sports clubs worldwide at first, and then to individual sportspersons who want to use the super-smart performance monitoring methods of Barcelona Innovation Hub. Producers of performance-enhancing products will also be eager to collaborate with the Hub. If a company can market a product as ‘tested by FC Barcelona’, it will immediately be more credible and appealing –and more expensive. Barcelona Innovation Hub will charge royalties. “And if the product is in sleep or nutrition areas, where elite athletes and ordinary mortals have similar needs, revenues could be large.” In the meanwhile and as a ‘futile’ sideline, Barcelona Innovation Hub will also become the ultimate knowledge and consultancy center for hamstring injuries. Hamstrings will always be a sideline, but the example gives you an idea of the lucrative expansion capacities when an amazing football club enters the data broker industry.
FC Barcelona will continue to stay an excellent sports center. At the same time it might evolve into an equally impressive data broker: collecting data, analyzing data, selling and renting the data, and building consulting services around the data. Many athletes will become even better. Many normal earthlings will have the chance to get healthier in more customized manners. Data broking empowers. An elite football-focused organization becomes a player for the masses.
The Serious Data Brokers
Once Google was mainly into page searching. It did an excellent job empowering us to navigate the internet and explore the exploding amount of websites. Google’s aim was to unlock all the knowledge of the world for us.
In return, we gratefully started loving the brand. But there was one downside for lovable Google: the company lacked a fertile business model behind all those free searches. Google could have let us pay for each search, but this opposed Google’s idealistic ambition to open the world’s knowledge to everyone. And thus Google became a company in search of a business plan. They found it in tracking us. Like no other company, Google knows our intentions, as we are typing them in for them with every search assignment. This way we provide Google with superior intelligence about our intentions and interests, which the company sells to all companies that want to sell to us. Google became the biggest and most lucrative marketing communication agency ever: Google’s AdWords. “A user looking to buy a hammer will begin with a search on Google, getting a set of results along with three AdWords ads from vendors selling hammers. The search takes milliseconds. The user buys a hammer, the advertiser sells one, and Google gets paid for the ad. Everyone gets what they want.” (Quote from ‘Zucked, Waking up to the Facebook Catastrophe’. Author: Roger McNamee, Publisher: HarperCollinsPublishers. Pg. 67). Google still is a search machine, but it has become a data broker even more, tracking our search behavior and selling the derived intelligence to advertisers.
Google might know and understand our intentions. But Facebook has a deeper understanding of our social connections, what we like, how our friends appreciate what we like and how we appreciate what our friends like. Just like Google, Facebook started as a company with a lofty ideal: connecting you with your friends and the world, contributing to more sharing humanity. And just like Google, after some years Facebook went for the really big money and turned itself into a data tracking machine, selling the derived knowledge on who we know and what we like – that we reveal so generously to them – with utter refinement to their advertisers. “The metadata that Facebook (…) collects enables them to find unexpected patterns, such as ‘four men who collect baseball cards, like novels by Charles Dickens, and check Facebook after midnight and bought a certain model of Toyota’, creating an opportunity to package male night owls who collect baseball cards and like Dickens for car ads” (Quote from ‘Zucked, Waking up to the Facebook Catastrophe’. Author Roger McNamee. Publisher: HarperCollinsPublishers. Pg 69).
Just as Google and Facebook became unimaginably rich and powerful by transforming themselves into serious data brokers, so did Amazon. Google might know most about our intentions. Facebook about who our friends are and what we like. But Amazon can claim to know best what we actually buy, and almost buy, and how long we hesitate to click which buttons and which people like what we buy – (so Amazon can offer it to them too.)
New inroads for the super data brokers
Today, Google, Facebook and Amazon are predominantly in the business of tracking us, analyzing the virtual breadcrumbs we so richly leave on ‘their’ Internet. (Maybe we should not talk about bread crumbs. Tiny gold nuggets is the better expression: they are worth money.) All three have their own competitive edge, through knowledge of our intentions, our appreciations, or our sales. Yet the cards have not been shuffled for good. Tracking us gets more and more dimensions. With an Android-empowered mobile phone, Google now knows where you are walking around. Google Maps is perfecting this knowledge at any time. Google can now help its advertising clients to approach you on the go with laser-sharp effectiveness: right time, right place, right desire and intention. Remember Pokemon GO (or Ingress/Harry Potter: Wizards Unit for that matter)? The game was born out of Google Maps. On a surface level, Pokemon GO appears like a fun game that enthralls youngsters worldwide. On a data brokers level, Pokemon GO earns huge amounts of money by selling the locations where the Pokemon GO players must go to, such as the McDonalds and its likes in the near neighborhood.
Another inroad for the super brokers to reach us is a mobile payment. Suppose you use Apple Pay to buy a bouquet from a florist. Apple Pay can collect all the flower sales data in the neighborhood and analyze what kind of flowers are most popular at that exact moment. Then Apple Pay can sell this relevant information to the highest-bidding florist close by, enabling him to raise prices for the currently most popular flowers. When you pay with Apple Pay, the company can gather your financial transaction data, repackage it and sell it to the highest bidder. As a consequence, Apple is also morphing from a mobile phone company into a bank, but basically into a data broker.
And more inroads into our lives are coming! Take face recognition. When we watch a YouTube film or an online advertisement we go through a series of emotions. Some emotions only take us for a fraction of a second – too short to consciously recognize. Webcams though can register these micro-expressions. They, for instance… “can capture the nanosecond of disgust that precedes a rapid-fire sequence of anger, comprehension, and finally joy on the face of a young woman watching a few frames of a film, when all she can think to say is ’I like it’. (Quote from ‘The Age of Surveillance Capitalism’. Author Shoshana Zuboff. Publisher: Profile Book. Pg. 283) The webcam on your computer, so helpful for a pleasant Skype with a long-distance friend, is at the same time a magnificent tool for the super data brokers to mine more data about us in order to predict our future (buying) behavior with ever more detail and certainty.
Next to face recognition, we also are on the thresholds of a voice recognition revolution. Smart televisions have it already ingrained, silently eavesdropping on words you express in the intimacy of your room. The virtual assistants that the super data brokers invite us to welcome into our lives – Alexa by Amazon, Siri by Apple, Cortona by Microsoft; these are the three leading ones in the Western hemisphere – are perfecting this new inroad for the super brokers to understand ever better what we want – and to predict our behavior. “Already, forward-looking Amazon patents include the development of a ‘voice sniffer algorithm’ integrated in any device and able to respond to hot words such as ‘bought’, ‘dislike’ or ‘love’ with product and service offers.” (Quote from ‘The Age of Surveillance Capitalism’. Author, Shoshana Zuboff. Publisher: Profile Book. Pg. 269)
And then there are the specialized data brokers
Next to the super data brokers, actually often in alignment to them, are the more specialized data brokers. They gather our data points less extensively than the super ones do, but they do it with more depth. Here are three different examples:
- You know the handy Roomba vacuum cleaners who can do the boring chores for you? Their latest iRobot Home versions not only allow remote control by Amazon’s Alexa but also comes with extra sensors that map the interiors of each house plus its square-meter layout. CEO Colin Angle is eager to reach data sales deals with partners like Google. Google is already measuring the streets outside our house. Knowing what each house looks like inside, is the knowledge that adds value and can be sold – to IKEA maybe. Of course, there is the privacy issue. The company is clear about it: you can always opt-out by disconnecting your iRobot Roomba from Wi-Fi or Bluetooth, unfortunately disabling the capacities of the vacuum cleaner significantly as upgrades are cut off as well. And if you don’t opt out? Well, then it is your smart vacuum cleaners’ right to share the info it collects. According to Josh Hafner and Edward C. Baig in USA today, 25th of July 2017: “Your Roomba Already Maps Your Home. Now the CEO is planning to sell the map”.
- Jeremy Jauncey, not long ago an aspiring rugby player from Scotland, has found his real ambition as a world traveler, becoming a successful entrepreneur in the meanwhile. Still a Millennial, Jauncey understands not only that a picture can tell more than a thousand words, but also how to earn money from it; thousands and thousands of euros actually. Jauncey started social-first, creative agency BeautifulDestination.com. Growth since 2014: 30.000%. BeautifulDestinations fully understands the power of Instagram. Especially when you enrich it with AI-analysis. What pictures of hotels and travel destinations attract the most attention? What pictures have stopping power? To answer these questions, BeautifulDestinations’ (BD) data team has constructed its own engagement algorithm: collecting thousands of pictures across social media and analyzing them for correlations across millions of parameters. Now you can find a plethora of these super-engaging pics on the BD website. The BD team’s software ranks images by predictive engagement. Then it presents these ranking to clients like Marriot hotels and Mastercard with an enticing ’come and visit this place’ invitation to potential customers. Beautiful Destinations now has over 13,5 million Instagram followers from 180 countries and is still pending. Many pics on the sites receive far over 100.000 likes within 24 hours after publication. BeautifulDestinations is still a travel site but has essentially turned into a specialized data broker. A data broker that has found its business plan, finding it in travel while embracing social media like no one else. (Based on an article on Jeremy Jauncey in Entrepreneur magazine, issue April 201 by Kate Rockwood.)
- Alexandra van Houtte started as a fashion stylist, trawling through many catwalks images to serve her clients – filmmakers, (fashion) advertisers, celebrities – with the most appealing looks. Following 537 designers with four shows, a year adds up to 35.000 looks per year. Screenshotting, tagging, and combining all these looks is incredibly time-consuming. So Alexandra built her own unique database of all the pics and looks she collected from the catwalks. Then she brought everything to her online platform tag-walk.com. It has become the most sophisticated tool for fashion forecasting, research and inspiration. 72% of users are Millennials. 91% is B2B. The business brands subscribing to platforms are asking questions as: ‘What are the most used search terms?’, ‘What is on the rise, what is decreasing?’ ‘What are the most popular offerings of my brand?’, ‘What are journalists watching compared to regular consumers?’ Tag-walk.com algorithms can answer them. Tagwalk seems to be part of the fashion industry, but even more, it is a (fashion) data broker. Businesses that subscribe to the platform can expect to receive answers to their hot questions like above, as tag-walk’s algorithms crunch all the data for them. Plain visitors can enter the platform for free. The more the better. After all, their clicks and searches are the digital breadcrumbs (or gold nuggets) that the platform manages to transform in real business money. Tag-walk is thus a data broker in the first place.
Next to the super data brokers and specialized data brokers, there is a third category of data brokers. These are neither as big as the super ones nor as specialized as ‘niche’ ones like Tag-walk, Beautiful Destinations or Roomba. These are the data brokers who did not transform themselves ‘accidentally’ into data brokers but actually started as such from day one. They collect data points from all kinds of different sources, including offline data (because the super data brokers often concentrate on online data), while their algorithms crunch all the data according to the needs of their clients. Amoobe.com is one: “Drive better results with better data. Recognize consumers using a person-level identity framework and orchestrate their brand experience across all screens, with definitive online to offline campaign measurement.” Experian is one: “We gather, analyze and process data in ways others can’t.” Acxiom is one: “Our diverse portfolio of offerings empower thousands of brands, platforms and partners to better understand and engage audiences everywhere.” Oracle and Palantir are other big ones.