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How Big Data Will Make The World Unrecognizable, Part 11

In part 110 we take a look at the end game of Big Data, converging all types of sensors and data to predict YOUR future.


So far, what weve described doesnt exist in its entirety in the physical world. A lot of what was described exists in the online world, and some of what was described exists in the real world. So, from this point forward there is a lot of conjecture. But rest assured, this is all coming to the real world around you, and there is nothing much that can be done to stop it. The generic term, the system, Ive been describing is one that describes parts on a myriad of different commercially available systems out there, but the next logical step is to introduce to you, the company. The company does not exist in the form we will describe, it could be an existing company that puts all the pieces together or it could be an entirely new one. Much the same as Googles Adsense controls the world of online advertising or Amazon controls online shopping, there will be an absolute behemoth that controls the physical world.

This company will utilize all of the aforementioned data tools; big data, IoT, AI, the cloud, and fast data, and apply them to the real world. They will combine the data from real world sensors like security cameras, Point of sale data, web browsing, phone records, credit scores and hundreds of other types in the data convergence. Now you might be thinking that most of these types of data are the private property of individual corporate entities, and you are right. But you have to remember one thing; EVERYTHING is for sale at the right price, and the money that will be generated by the company will be far too great to resist. Especially if you get a piece of the action in exchange for your data. Heck, you will see companies grow from nothing to create sensors with types of data we dont even know exists.

A while back I did a little what we like to call foreshadowing. I mentioned a camera in the hardware store on the other side of town and here is why. The middle aged man that bought the Cheep Chicken on Cheep Chicken Monday three weeks ago is walking up to the hardware store to pick up some masking tape. We will call him Todd. Hes known to the companies system, his profile and the data ascribed to him exists, but the system doesnt necessarily know the data belongs to a guy by the name of Todd and you know what, it doesnt matter. We dont really need to know if his name is Todd, bleetilyblopfartsworth, or 34920495Q. Whenever Todd creates data, wherever he is, the system assigns a probability to the possibility that it was Todd that created the data. That data is stored and algorithms scan the data for patterns. AI creates new algorithms specifically tailored to figure more out about Todd to better predict future actions and purchases, remember, its all about the money. Whether Todd likes it or not, a virtual copy of him exists in the cloud.

At 12:15 this afternoon Todd opened his refrigerator and removed a package of ham to make a sandwich. The camera on his internet connected fridge scanned the UPC as he pulled it out. When Todd bought his fridge, he liked the fact that he could check the camera inside to see if he needed to bring home a gallon of milk and after a software update he loved the fact it could tell him he needed to buy milk. Since we are slightly in the future here, Todds fridge can provide him with a detailed list of what is in the refrigerator. He knew that the fridge company collected data on how he used the fridge but he was assured that the data would be anonymous to his identity. Since the fridge company doesn’t associate its data with personal data it has no problem selling this data to the company. The data, however, contains the IP address where it originated. Its OK, the system knows. Long ago it associated Todds cell phone, car, and virtually every device that communicates through Todds home wifi with Todds virtual avatar. In fact, within seconds of Todd booting up his fridge, the system assigned a very high probability it was Todds new fridge. So, at 12:15 it knew that Todd was eating ham. Comparing it to all the past data known about Todd, he had it on wheat bread with a side of the pringles he bought three days prior at the grocery store from our examples. The system determines this to be the case with a 92% probability.

You see, Todd lives in the real world and is simulated in the virtual world, 24 hours a day, 7 days a week, 365 days a year. The AI is a virtual Santa Claus. As Todd pulls into the hardware store parking lot at 6:30PM, the security cameras recognize the make, model, and color of the car. One of the cameras is able to discern 3 of the characters on the license plate. This information alone narrows down the possibilities of who is in the car to just two cars and four people based on known vehicles in that geographical area. When Todd steps out of the car, the camera determines Todds demographics and eliminates two of the four people because they are female. The system pings both of the possibilities cell phones and determines with 99.8% probability it is Todd as the other ping is returned across town.

Remember, the system is weighing various possibilities of what might be on Todds mind, and more importantly, how it can separate Todd from some of his money. It knows Todds habits and even estimates certain biological properties. Can the system convince him to buy clothes? Gas? A new car? Is he out of toilet paper? No, Todd the system predicts he is hungry and information from the cameras confirms this. After Todds visit to the hardware store he is most likely going to purchase food. The system simulations confirm the historical data on how Todd acts when he goes 6 hours without food.

This is where the magic begins, where the data trail turns into money. Todd walks up to the entrance to the store. In the entrance, there is a video monitor. Wait a second, this is the future, the glass on the door can be glass one second, and turned into a monitor the next. The system weighs all of the possibilities of what Todd might do if persuaded to do so. Without intervention, hell probably go to the Taco Bell next door, but there are three other likely possibilities. In the instant before he steps into the store the system notifies server agents at the three possibilities and delivers the probability that Todd will visit them and buy from their store. A bidding process takes place and the highest bidder wins the privilege of interacting with Todd. In the time it took Todd to step in the front door, a reminder appears on the screen that tonight is Cheep Chicken night. Todds mouth waters. Thirty minutes later Todd is in line for Cheep chicken. Since he was there anyways he bought the toilet paper the company knew he needed and at some point in the future knew he would buy with his chicken. All the while, behind the scenes, the bidding system took place, costing the Cheep Chicken grocery store 10 cents to buy the ad, 6 of which went to the hardware store for displaying the ad and 4 of which went to the company, adding to this years top line trillions of dollars in gross sales. This happens billions of times per day across the globe.

All of this happened without really know who Todd is. It happened without any consent from Todd. It happened without any conscious input from Todd. Once the convergence of data is able to predict and manipulate the future in public, and in real time, the world as we know it changes forever. This is just one aspect of how things will change, these changes will affect everything from commerce to advertising, to law enforcement, and to government. In the next part we will investigate the broader scope of how Big Data, AI, IoT, Fast Data, and more will change our lives.


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