Future makers: "Absolutely positive about big data"
News | April 20, 2017
With examples from our daily lives, Paul Hiemstra brought the abstract subject of 'big data' alive in front of an almost full hall at the Leeuwarder Courant in Leeuwardern. Netflix, fake news, YouTube and Google Adds were all covered. “These techniques all work on the basis of big data.” But big data alone does nothing and, according to Hiemstra, has no value. “Data only becomes interesting if you assign characteristics to it. For example, the movies on Netflix, which have characteristics such as fiction, action, romance. If you link these characteristics to other characteristics that say something about the viewer, for example the time at which the film is seen and which films he/she watches more often, you can make predictions. Netflix serves these predictions to viewers as suggestions for watching the next movie or series.”
In order to make predictions, a computer has to learn all kinds of things. “Just like a child learns,” Hiemstra explains. His 1-year-old nephew learns because his father and mother point out things to him and name what it is. ,,That way he learns everything about cats and eventually recognizes a cat. We also do that with computers. We keep showing the computer pictures of all kinds of cats until it understands the characteristics of a cat. After that, the computer knows flawlessly to say with a picture of a horse: this is most likely not a cat.” Hiemstra explains that 'presenting' is just as important for a child as it is for a computer to learn. The computer stores everything and after a while 'knows' how to distinguish all kinds of animals from each other flawlessly. Hiemstra calls such a computer model an algorithm. As a result, characteristics associated with data suddenly become valuable.
That is the field of work of Anne Gerben Terpstra. He shows how his company can measure the quality of cow's milk using various colors of light and thus make predictions about the cow's health. “By linking all kinds of characteristics to certain colors of light with smart sensors, we can measure the fat content in milk and hundreds of other things. Previously, a chemical analysis took three days and then you received a result on a maximum of 5 measured points. With our method you have a result of hundreds of measuring points within 6 seconds.”
Big data can therefore help us further and make our lives easier. Terpstra: "With our measuring method, the University of Amsterdam has shown that you can predict with 96 percent certainty whether someone has cancer from human blood samples." This kind of information is nice to know for a good and quick treatment, but it also has a downside. Terpstra agrees. "Of course you don't want health insurers to find out this kind of information about you, because that can mean that you are excluded from insurance or that you may have to pay a significantly higher premium." According to him, this method is already being used in car insurance, where sensors are used to record people's driving behaviour. If you drive recklessly, you have to pay a higher premium. “They want to increase road safety in this way.”
According to Hiemstra, the use of big data not only offers a 'dark side', but also great opportunities. “Technology is way ahead of public debate and legislation. That's why I want to share my knowledge and make people aware of what's going on, so that they can form an opinion."
This and the other 4 lectures can be viewed on a special webpage of the Leeuwarder Courant / Future Makers.