Q. What did it take to write Big Data?
A. Kenn has written about technology and business from Europe, Asia, and the US for The Economist, and is well-connected to the data community. Viktor had researched the information economy as a professor at Harvard and now at Oxford, and his book Delete had been well received. So we thought we had a good basis to make a contribution in the area. As we wrote the book, we had to dig deep to find unheard stories about big data pioneers and interview them. We wanted Big Data to be about a big idea, but also to be full of examples and success stories -- and be engrossing to read.
Q. Are you big data’s cheerleaders?
A. Absolutely not. We are the messengers of big data, not its evangelists. The big data age is happening, and in the book we take a look at the drivers, and big data’s likely trajectory: how it will change how we work and live. We emphasize that the fundamental shift is not in the machines that calculate data, but in the data itself and how we use it.
Q. In discovering big data applications, what was your biggest surprise?
A. It is tempting to say that it was predicting exploding manholes, tracking inflation in real time, or how big data saves the lives of premature babies. But the biggest surprise for us perhaps was the very diversity of the uses of big data, and how it already is changing people’s everyday world. Many people see big data through the lens of the Internet economy, since Google and Facebook have so much data. But that misses the point: big data is everywhere.
Q. Is Big Data then primarily a story about economic efficiency?
A. Big data improves economic efficiency, but that’s only a very small part of the story. We realized when talking to dozens and dozens of big data pioneers that it improves health care, advances better education, and helps predict societal change—from urban sprawl to the spread of the flu. Big data is roaring through all sectors of the economy and all areas of life.
Q. So big data offers only “upside”?
A. Not at all. We are very concerned about what we call in our book “the dark side of big data.” However the real challenge is that the problem is not necessarily where we initially tend to think it is, such as surveillance and privacy. After looking into the potential misuses of big data, we became much more troubled by “propensity” -- that is, big data predictions being used to police and punish. And by the “fetishization” of data that may occur, whereby organizations may blindly defer to what the data says without understanding its limitations.
Q. What can we do about this “dark side”?
A. Knowing about it is the first step. We thought hard to suggest concrete steps that can be taken to minimize and mitigate big data’s risk, and came up with a few ways to ensure transparency, guarantee human free will, and strike a better balance on privacy and the use of personal information. These are deeply serious issues. If we do not take action soon, it might be too late.