Update (engl.) - Michael Steinbrecher - E-Book

Update (engl.) E-Book

Michael Steinbrecher

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Beschreibung

Big Data is changing all aspects of our lives. In tune with the current debate, the authors develop positive and negative scenarios reflecting individual facets of life. The advantages and disadvantages of our world of data are illustrated in numerous case studies. In extensive interviews, actors from the worlds of politics, science, journalism and business have their say.

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Michael Steinbrecher, Rolf Schumann

Update

Why the data revolution affects us all

About the book

Big Data is changing all aspects of our lives. In tune with the current debate, the authors develop positive and negative scenarios reflecting individual facets of life. The advantages and disadvantages of our world of data are illustrated in numerous case studies. In extensive interviews, actors from the worlds of politics, science, journalism and business have their say.

Vita

Prof. Dr. Michael Steinbrecher is a multi-award-winning television journalist (incl. the Grimme Award). Since 2009 he has been working as a professor for television and cross-media journalism at the Institute for Journalism at the Technical University of Dortmund. His main areas of research include big data.

Rolf Schumann embodies technology with entrepreneurship and is a renowned expert in innovation topics. He played a key role in establishing and expanding the cleantech startup Better Place and is now responsible for the Office of the CTO at the software company SAP in his capacity as Chief Technology Officer (CTO) and Head of Innovation for the EMEA, Central and Eastern Europe region.

Table of contents

Acknowledgments

Chapter 1The data revolution; or, How do we want to live?

Is big data a danger?

What this book can achieve

Chapter 2What is big data?

From information growth to big data

The data cocktail

The end of theory?

Forecasts

We, the data donors

The technical and economic view of big data

Probabilities become more important than the search for reasons

Frankfurt to San Francisco in 20 seconds

Interview with Prof. Dr. Viktor Mayer-Schönberger — “If big data were a human being, it would surely be a fascinating person, with all their bright and dark sides.”

Chapter 3Data trails in our everyday lives

Interview with Sabine Leutheusser-Schnarrenberger — “Yes, you have a lot to hide.”

Chapter 4Opportunities and risks of the data revolution

4.1: Digitalization and the quantified self for a longer life?

The opportunity: A longer, healthier life

The risk: Selection and data dictatorship – big data is unhealthy

Interview with Peter Schaar — “Technology must not be an independent variable.”

4.2: The mobility of the future

The opportunity: The car as an oasis of well-being in a world without traffic and road casualties

The risk: The car as a surveillance center of a remote-controlled life

4.3: Smart homes and smart cities – how will we live in the future?

The opportunity: Smart homes and smart cities – intelligent, safe, convenient and environmentally friendly

The risk: The smart home; or, The story of the Trojan horse

Interview with Jason Wolf — “The most powerful sensors out there are the people themselves.”

4.4: Consumerism: the new, personalized world of data trading

The opportunity: Personalized consumption – a tailor-made customer service

The risk: The transparent human – a puppet of industry

Interview with Shannon Poulin — “Above all, we believe that everyone should have the option to make up their own mind in these situations.”

4.5: The future of education – I know that I don’t know

The opportunity: Supporting individual talent

The risk: Learning segregation

4.6: Will big data make us more or less safe?

The opportunity: A safe life – thanks to big data

The risk: The deceptive promise of security – an attack on freedom!

Interview with Elmar Theveßen — “Puppets on strings.”

4.7: How will the data revolution change journalism?

The opportunity: A new golden age thanks to data-driven journalism, transparency and dialog

The risk: Big data; or, Will the last journalist please turn out the lights?

Interview with Shel Israel — “Journalists should use data to build credibility.”

4.8: On the road to the fourth industrial revolution

The opportunity: Machines as partners – with the human being at the center!

The risk: Role reversal – the takeover of our lives by machines

Interview with Prof. Dr.-Ing. Siegfried Russwurm — “Basic administrative duties will disappear, and the future belongs to creativity.”

4.9: Sports – between technology and emotion

The opportunity: The fascination of sports remains – but data makes all the difference!

The risk: Transparent sportspeople in a predictable world

Interview with Dr. Stephan Nopp — “This game will never be predictable.”

Chapter 5How do we want to live and what can we do?

The machine as a life companion

We, the self-surveillants?

Do you want to be led?

What can you do personally?

The dominance of machine-driven efficiency?

Return to a predetermined life?

The predetermined life

The dictatorship of speed

Danger of mass unemployment

Future of lateral thinkers

The great data collectors

What do we expect of corporations?

What do we expect of politicians?

Interview with Prof. Dr. Dr. Dirk Helbing — “Digital enlightenment or self-inflicted dependency – these are our alternatives.”

Chapter 6Looking ahead

The opportunities of the data revolution

The risks of the data revolution

Acknowledgments

Michael Steinbrecher:

A personal thank you for their cooperation and support goes to: Matthis Dierkes, David Friedrich, Nicolas Jungkind, Fabian Karl, Julia Lönnendonker, Judith Pulg, Günther Rager, Marie Luise Rager, Kathrin Reinl, Christoph Schickhardt, Dennis Westenberger, Anna Carina Zappe and Hanna Zimmermann.

Rolf Schumann:

Many thanks for their support and cooperation go to: Katja Mehl, Anja Schneider, Susanna Bauer and Michael Pacevicius. Very special thanks to Johannes Tulusan for his ongoing support and supervision of this project.

Chapter 1The data revolution; or, How do we want to live?

“The data revolution? Big data? What does it have to do with me? Let them collect all my data – after all, I have nothing to hide! And who cares about what I think and do anyway?”

Does this sound familiar? Yes, the data revolution really does affect you. Personally. It affects all of us. Big data is not just about Edward Snowden, the NSA and possible travel bans to the United States. Neither is it about whether the secret service knocks on your door tomorrow. It’s about how you see the world, your own life and how you wish to shape it in the future.

Big data can save lives and ensure that we all live to be much, much older. Moreover, it can help protect our environment and finally curb our depletion of the planet’s resources, while at the same time making our lives simpler and more comfortable. Just imagine: No more sitting in traffic, no more wondering whether the stove was left on. It also opens up completely new horizons in business and science. Many experts are euphoric and fascinated by big data. For companies, data is the oil of the 21st century – and we are already in a race to tap into new data sources and bring this new oil to the surface.

However, if it falls into the wrong hands, big data could lead to disaster, creating a surveillance state with instruments the likes of which the world has never experienced before. Even in democratic societies, big data can create complete profiles of us all, classifying and sorting us and thereby determining our future. Big data can create a future in which our past never lets us go. After all, your profile forgets nothing: everything will remain saved. Big data can bring about increased automation and make people superfluous across broad swaths of the labor market. At the same time, it can also take away our freedom and lead to a state of affairs in which in 50 years only the very old can still imagine what it is truly like to have a private sphere. Are we prepared for this situation?

But on the other hand, is the human right to privacy still equally important to all generations? Is privacy even dispensable if our lives become safer and more convenient without it? Where does privacy end and human dignity begin? Big data raises a number of important questions. If we wish to avoid unpleasant surprises, we shouldn’t delegate these questions to someone else. It is an existential matter.

Big data isn’t a vision of the future; it is already with us today and is irreversible, changing our world more and more. We will never be able to turn back the clock. Moreover, big data is more than just a technological development. It is more significant than the invention of the lightbulb or of television. It creates a new type of thinking and acting or, as interpreted by Prof. Dr. Viktor Mayer-Schönberger, “a new approach to reality.”1 We are experiencing changing times, which even Mayer-Schönberger, who is fully aware of the gravity of the terminology he uses, calls a “revolution.” In his interview with us, he makes it clear that, for him, big data represents an epochal event comparable to the Enlightenment: “It is an event to be measured over the course of centuries.”2 Big data will change how we think, act and live – and how our society will develop.

Far-reaching changes are looming, but they are gaining a foothold virtually without a sound. Even today, the outlines of this future are clearly recognizable in many areas, resulting in sweeping consequences for our lives. Can you imagine that several billion objects are already equipped with sensors and connected to the internet? Yes, you read that correctly: not people, but objects. How does it sound to you when we assert that a window “talks” to a radiator? Or the street to the car tire? Exactly this has already been happening for a long time. And this Internet of Things will continue to expand. Leading analysts and industrial corporations estimate that, in 2020, 50 billion objects will be equipped with sensors and will communicate with one another.3Just look around yourself now while you are reading these lines. Where are you right now? In an apartment or a house? Everything that you see will belong to the Internet of Things. The floor, the doorknob, the window, the lamp – absolutely everything. If you are currently in a pedestrian area, you can see streetlights, benches, shops and store windows around you. And they will talk to one another too. Are you in the woods? Even here, sensors will in the future be fixed to the trees. Vines are already delivering information for winegrowers,and trees will do the same for foresters in the future. But why are all these things communicating? They are synchronizing themselves with one another, exchanging information and thus optimizing their “behavior.” This allows your apartment to start your own personal feel-good program, greeting you with the right music and serving you food as soon as you feel hungry. Not magic, but a real possibility thanks to big data. The flip side of this is that nothing in your apartment will go unobserved. Who should be allowed to know and use your data? And who already has that right?

Is big data a danger?

We are still in the pioneering phase in which it is possible to shape change. And this is fortunate, as the dark side of big data casts a long and threatening shadow. But one thing should be made clear at the outset: We are not saying that big data is bad, nor that it is brilliant. We believe it can be both. It is important that you know the good, promising side, but also that you are equally aware of the dark side of big data before making a conscious decision on how you wish to deal with this epochal change. You should develop a feel for what can affect you as a person and which developments are taking place to what extent. We want you to be consciously aware of big data in its entirety.

Big data has usually been discussed in the public arena in connection with Edward Snowden. In his first interview, with the Guardian in June 2013, Snowden said: “I do not want to live in a world where everything I do and say is recorded.”4

The discussions triggered by his revelations were an eye-opener for many of us. The scale of what the NSA already practices surprised the public and even some experts. Many editorials were written on the subject, and there were countless television reports. Lots of questions, and outrage, followed.

However, this focus on the topic of datasecurity and the secret services has obscured the fact that big data has already long since conquered all areas of our lives. A dynamic has developed in the slipstream of this discussion that the general public has not yet become aware of. This book aims to contribute to changing this.

What this book can achieve

We aim to allow you to visualize the change that is taking place around us in a practical and impartial way. We want to convey the promises as well as the dark side, with regard to all areas of life that affect you day in, day out. What does big data mean for your health? What is the evidence that big data will cure you or allow you to live longer? And what price might you have to pay? How do you want to travel, live, shop and work in the future? How does big data change our ideals and the way we think and act?

In his interview with us, Prof. Dr. Dr. Dirk Helbing makes it clear what is at stake: “There could easily be a disaster on the road to the digital age if we do not learn how to handle this magic wand quickly.”5

Each one of you should be able to make a conscious decision as to what position you take. Where do you stand? Are the possibilities offered by big data more important than what big data would cost you? We need to approach this topic in a way that is free from any ideology. We will therefore introduce and convey the opportunities and risks presented by big data separately. The comparison in Chapter 4, which is the core of this book, is aimed toward helping you decide for yourself what kind of future you want. But, because we also want to present the future scenarios within a context, we will describe what big data is. And we guarantee that everyone, even those without any prior technological knowledge, will understand what big data is. In order to provide you with a diverse perspective on big data, we have conducted dozens of interviews with physicians, journalists, executives of large corporations, data protection experts, mobility researchers, politicians and visionaries, covering a broad spectrum of fields and opinions. With selected interviews presented in this book we aim to give you uncensored insights into various areas of life. It is your choice whether you start by reading the interviews or read the book from cover to cover. It is simply important that you immerse yourself in the subject, as it deserves considerably greater exposure. An epochal event of this momentousness should be shaped by us.

Because, once again: Big data is not good or bad. It can be both. Big data is what we make of it.

Chapter 2What is big data?

Why are we talking about a data revolution? What is actually meant by the notion of “big data”?

In the so-called internet age, everything we do in our day-to-day lives creates data and leaves digital trails. Some 3.3 billion people have access to the internet (with 2.5 people joining them every second), Google processes 3.5 billion search queries every day6, 500 million Tweets are posted on Twitter daily7, 1 billion YouTube users load 300 hours of video material onto the platform every minute8 and 15 million photos are posted on Facebook every hour.9 Do these numbers make you feel dizzy? They are the key to comprehending the scale of the change.

In the last 20 years, the amount of data in existence has risen 100-fold. However, this data surge is not unique in history – one similarly rapid increase has occurred before, between the years 1450 and 1500. The volume of data in the world doubled during this period thanks to the advent of Gutenberg’s printing press, which meant a revolution in society at the time. Today, the worldwide data volume is doubling every 18 months. However, what is often not considered in this context is this: while in the year 2000 almost three-quarters of all data were still in analog form, for example on paper, less than 15 years later this figure is less than 1 percent. A previously analog world has gone digital, which changes everything.

Are we currently in the middle of a revolution that is changing how we live, think and work, as claimed by Viktor Mayer-Schönberger and Kenneth Cukier in their book Big Data? Is the data revolution the greatest threat to our freedom and democracy, or is it the road to more transparency, greater freedom and a longer life?

Although data is becoming ever more important in our lives, it has not yet been possible to establish a widespread understanding of the change our society is undergoing. If you cannot yet imagine the actual meaning behind terms such as “big data” or the “Internet of Things,” you are not alone.

Three scenarios can help you get a better understanding of what big data is.

Let us first think about panning for gold. You are at the edge of a riverbed and are trying to use a pan to extract valuable metals. The enormous quantity of sand grains represents the ever-increasing amount of data available to us. For many people, big data triggers something comparable to a gold rush. After all, who wants to miss the opportunity to be a major player when the claims are handed out? This image represents the promise held by big data. Something new, something valuable is coming about that can enrich our lives.

The second image is a panopticon, a round, multistory building designed for factories and above all for prisons. The architectural principle behind the panopticon was devised by the British philosopher Jeremy Bentham at the end of the 18th century.10 In the middle of a panopticon there is a watchtower granting a panoramic view into all areas of the building. Imagine that you are in one of the small cells that could be observed from the watchtower. One guard is enough to give you and hundreds of fellow prisoners the feeling that you are being watched. After all, the guard could be observing you at this very moment.

Applied to big data, this could mean that not one person, but an organization, be it Google, the NSA or even a state, is constantly looking over our shoulder. We know that we are under permanent observation and that there is a possibility of attracting unpleasant attention and being sanctioned, so we adapt our behavior accordingly. Are we all in a panopticon in the age of big data? This is certainly a gloomy vision for many of you. Will we spend our lives constantly monitoring our own behavior and keeping an eye on our data trails in order to paint the most positive picture of ourselves, while at the same time being fully conscious of being watched around the clock? This is a vision that will accompany us throughout the book.

The third image is a childhood memory for many of us. Did you ever have a kaleidoscope? It resembles a small telescope. If you turn it and look into it, you discover fascinating, colorful patterns. But what does this have to do with big data? Inside the kaleidoscope there is a seemingly random collection of colored stones. If you turn the kaleidoscope, a small movement changes their structure. In doing so, you establish different links and recognize a variety of new patterns created by the combinations of these colored stones. Big data is not just the sheer quantity of data, but also the possibility to search for ever more new links and recognizable patterns.

These three images convey different perspectives on big data. Panning for gold tells us that something valuable is coming about. Something that will enable us to grant many wishes and that can make our lives more pleasant and comfortable. And something of great value for companies tapping these resources. Like a kaleidoscope, big data is special in that it enables us to recognize more and more new patterns. But we pay a price for this: the feeling of being observed, like in a panopticon. Or will we get used to the guard watching over us? Maybe at some point we will no longer even notice them?

Let us return to the effects of big data. How can it be that suddenly everything is supposed to change? Why is it suddenly conceivable that driverless cars navigate their own way through cities? Why do physicians harbor great hopes in the field of medicine, so that even a breakthrough in the battle against cancer seems possible? On the other hand, critics see dangers in a previously barely measurable dimension. They fear the loss of our freedom and self-determination. Hasn’t there always been data? What is really new about big data?

First we need to find out how data is created. And why there is suddenly so much of it. If you are only interested in the consequences of big data and do not wish to read about its origins, you can skip this chapter. But if you are new to the field, you will be missing the chance to gain a first impression of the technical causes of this rapid development.

From information growth to big data

Have you ever asked yourself what data you produce every day and how it is measured? Lots of data about us exists even before we are born, for example from an ultrasound scan – data that is saved and processed. As an adult you might use a credit card for payment, own a smartphone, measure your pulse while you are out running and hold customer loyalty cards. Every day, 2.5 exabytes of new data are being created worldwide. But how can we picture this unit of measurement?

Figure 1: Names and numbers for the designation of data quantities

A volume of 2.5 exabytes corresponds to 12.5 times the amount of data in all printed books.11 Imagine a library or a large bookstore in your city. Think of the hundreds of books on dozens of shelves that you will never have the time to read in your entire life. And now, in your imagination, stack up all the books in the world, on all continents. Every single day we produce a multiple of the data volume that would correspond to all the books in the world. Isn’t that incredible? The data capacity of your smartphone roughly corresponds to the data volume that was necessary to fly to the Moon for the first time in the 1960s. As you can see, there has been an extreme development here.

To return to the unit of measurement: What do terms like exabyte and terabyte actually mean, and what are bytes? Let us take a look at the basic principles of computers. You don’t have to memorize the next two paragraphs in order to understand big data, but in the medium to long term you should overcome your inhibitions with regard to these figures, as they determine part of our future.

A computer is a digital machine that can only differentiate between two states: 0 or 1, current flows or current does not flow. This element is the smallest of all data units and is called a bit. A byte corresponds to 8 bits and is therefore the next unit. Memory capacity specifications are made in bytes. As such, a photo of your family may comprise 2.5 megabytes, i.e., 2.5 million bytes. If you look at your computer at home or at work, you will see that the specifications are given in bits and in bytes. Your files or memory are measured in bytes (kilobytes, megabytes or gigabytes). A modern smartphone has a main storage unit with 64 gigabytes, for saving photos, music and other data.

The processor capacity, on the other hand, is measured in bits. An 8-bit processor is able to perform computing operations with a maximum of 8 bits. Today, your computer is probably a 64-bit model.

Many readers may think that this is trivial. But just as many may be grappling with the familiar feeling of being overwhelmed. Bit, byte, processor? What was a processor again? Just a minute, I’ll have a look in Wikipedia. What does it say?

“A central processing unit (CPU) is the electronic circuitry within a computer that carries out the instructions of a computer program by performing the basic arithmetic, logical, control and input/output (I/O) operations specified by the instructions.”12.

OK. So what is electronic circuitry, what is an algorithm? And how is data processed? A split is emerging in our society: For one part, these terms and units of measurement feel as natural as the alphabet. For others it is and will remain a completely foreign language. How will we react to this in the future? Does the goal have to be to communicate a basic principle of “data logic” to everyone? One topic in the next few years will be what happens to those who wish to escape the glut of data. Will they lose touch? Or will technology at some point become so intuitive to operate that only a few people will have to occupy themselves with the technical details?

This book is not a basic course on data. The only objective can be to illustrate the sheer scale of big data even to those who don’t feel comfortable with technical matters. That is why the proportions are depicted on the following pages. This will help you get a feeling for the data expansion.

Let us embark on a small journey through time, so that we can understand how the data we are talking about actually came into being. First, we will go back to the 1970s. At this time, mainframe computers were fed with so-called punched cards. These punched cards had punched holes. The states 0 and 1 were represented by a hole being punched – or not – in the corresponding place on the card. In this way, programs could be saved with these cards. Who can still remember punched cards today? In 1976, the floppy disk was invented. It took another ten years until up to 650 megabytes could be saved on its technological successor, the CD-ROM.

Even this development shows that the phenomenon of rapidly growing data quantities has been with us since the very first days of digital information technology. However, these quantities were initially only saved on local data carriers that had to be adapted accordingly. It was the emergence of the internet in 1983 that marked the start of a true global data network and triggered rapid growth in data volumes. In 1986, only three years later, the worldwide data capacity was already three exabytes. And that, we remember, is 15 times the data contained in all printed books existing in the world. The internet grew quickly and steadily, and in 1993 it already contained 16 exabytes of data. This capacity could hold enough music files to play non-stop for 19.8 million years. As you can see, even in the 1990s data quantities began to climb into the realm of the unimaginable. And here’s another image that illustrates the scale of this development: experts from the University of California, Berkeley estimate that all the words ever spoken by human beings could be saved in five exabytes.13

In 1996 the successor of the CD-ROM, the DVD, appeared, which could hold up to 8.5 gigabytes. And although only 2 percent of the global population had access to the internet in 1997, the flood of data grew continuously, reaching 55 exabytes in 2000. To gain an impression of such a quantity, imagine a film spanning 55 exabytes. It would take 1.1 million years to watch it.

The proportion of the world population with internet access also grew steadily. Whereas this stood at 2 percent in 1997 (120,758,310 people), in 2012 this figure was already 36 percent (2,511,615,523). In 2001 Apple released its iPod, which could hold up to 1,000 songs on its five gigabytes of storage. At that time, 4 percent of internet users were registered on Facebook. The total amount of saved data was by then 295 exabytes. To save this data on DVD, one would have to write enough DVDs to completely fill the Chrysler Building in New York. To further illustrate the scale of this, note that the architectural masterpiece has 77 floors and stands 1,046 feet high.14

By 2010, 6 percent of all internet users were registered on the Twitter messaging service. The proportion of internet users registered on Facebook had risen to 24 percent, while the total number of people with internet access had climbed to around 2 billion, corresponding to 30 percent of the world population. In 2015, the global network contained 1,352 exabytes of data. If saved on DVD, this would produce a pile stretching from the Earth to the Moon. The internet is used by 45 percent of the world population, or 3.3 billion people. And by the time you read this, these numbers will probably have grown by a long way again.

Figure 2: IT developments from 1972 to 1984

Figure 3: IT developments from 1986 to 2000

Figure 4: IT developments from 2001 to 2007

Figure 5: IT developments from 2009 to 2015

The most interesting thing about this development is the rapid increase in data since 2011. Over 90 percent of all digitally recorded data originates from this period. A number of factors have contributed to this, including the intensive use and spread of social media such as Twitter, Facebook, Google+ and Instagram. Another reason why these channels are so heavily frequented is because mobile terminals, smartphones and tablets make it possible. Among the mobile terminals – of which there are today 7 billion – 1.445 billion smartphones are expected to be sold in 2015. This puts them clearly in the lead. During the same period, just under 0.545 billion PCs and tablets are set to be sold.15

Have you used your smartphone today? Then think about everything you have done with it today alone. Have you taken a photo and sent it to your work colleague? Read your e-mails? Downloaded and installed a new app? Saved music? Maybe you had a look at Facebook while you were on the subway? Or did you use your smartphone as a sports computer to see the difference in altitude you covered during your morning run?

You might have already made a significant contribution to the data flood today – just with that small device in your pocket! And you are not the only one. In the next three years, the industry expects the number of mobile terminals to increase to almost 10 billion, 5.5 billion of which will be smartphones. Today, the data quantities transmitted using smartphones amount to almost three exabytes per month and will break through the ten exabyte barrier in the next three years. The Asian market is the world leader here with almost half of all data traffic. All over the world, 300 hours of video material are uploaded to YouTube, 4,112,500 Google search queries are made, 3,300,000 Facebook entries shared, 347,222 Tweets sent on Twitter16, 48,000 apps downloaded from Apple’s App Store and 38,200 photos posted on Instagram – every single minute.17

These are all entirely new dimensions. It has by now become clear that the data flood is quickly becoming ever larger and has seen strong growth in the last few years. But this alone does not make big data such a decisive event. It all gets a lot more futuristic. Even the things around us are networking themselves. Ever more devices contain sensors that record and transmit data. This has brought about an Internet of Things made up of so-called smart devices. It all begins, as described above, with the smartphone, but also follows you into your own home, among other things encompassing the washing machine, the household management system and even the humble toothbrush. Sensors are also fitted in cars and enable the user to fully network and maintain the vehicle. In “smarter” cities, sensors control the entire infrastructure of the city. We will find out more about and discuss these developments in Chapter 4. Smart devices have entered virtually every facet of our lives. Experts forecast that there will be over 50 billion networked devices worldwide by 2030.

The data cocktail

What accounts for the new quality of big data? There is no single, universally accepted definition of big data. But there is an approach cited most often in journalism and science when we talk about the topic, and which will certainly help you get to grips with it.

This approach is based on the four Vs: volume, velocity, variety and veracity. We’ve already established that big data is large – after all, the name does hint at it. However, big data is also fast, varied and can sometimes even contain vague data. And this is supposed to trigger a revolution that turns our lives on their head? Exactly.

The velocity in particular has engendered a real spirit of optimism in business. Companies can monitor which traffic light could soon malfunction, which parcel is currently where, and which pipe needs to be replaced in real time – and react immediately. But it doesn’t just present opportunities for businesses – it will change your day-to-day life too. In a networked home, you can observe while on vacation how high the room temperature is or in which room a conversation is currently taking place. Many things become possible. The question you will ask yourself again and again is: How do I want to live?

Figure 6: The four Vs of big data

What is special about the third V, variety? We used to gather data for ONE specific purpose. Once we had used the data to find out what we wanted, we perhaps saved it somewhere, but it was then generally useless. However, in the world of big data it remains valuable. Because it is precisely this linking of seemingly non-related data that makes big data so exciting.

The fourth V is for veracity. Even inaccurate, vague data can be useful in the age of the data revolution. Although it sounds unspectacular, in combination with the other three Vs it has far-reaching consequences.

Many constituent parts of big data already existed as individual elements. There has always been data, and computers have also long been with us. However, it is not, as one may assume from the term BIG data, the data VOLUME alone that is changing the world. It is all four elements together, with all of their interactions: volume, velocity, variety and veracity. It is a cocktail consisting of these four elements that is intoxicating so many. A cocktail that releases energy and imagination.

Four Vs are simply not enough for some, so further Vs are sometimes added, for example the value of the data. But as we do not wish to further complicate the definition, we will stay with the original four Vs.18

What does this all mean in concrete terms? What does this new data cocktail change? Some believe it changes everything.

The end of theory?

Let us begin with science. The precision of processes used has been a key focus of social sciences for decades. Accordingly, a random sample must be as representative as possible in order to allow the researcher to draw conclusions for the study as a whole. Here is one concrete example used by Viktor Mayer-Schönberger and Kenneth Cukier to illustrate the changes in science. Assume you want to measure how the temperature in a particular vineyard changes throughout the months. How do scientists go about this right now? They develop a small quantity of precise measuring instruments and place them in various positions in the vineyard. The results they gather using this method then allow them to draw conclusions as to how temperatures have developed. Big data, however, means that we have a sensor on every vine, indeed on every grape. And this in turn means that n equals all. We have thousands of measuring stations, and we assume that most of them work correctly. In the age of big data, a representative sample is less and less significant. Furthermore, it is suddenly unimportant if 20 measuring instruments fail, or if some are not set up precisely. The result will still be more precise than what I had before. And I can call up the information immediately, in real time. That means that even “messy data” can be valuable in the age of big data. We haven’t even discussed the third V, the variety of data, in this example.

Chris Anderson put all this on the agenda for the first time. He declared the “end of theory” in a short essay in 2008.19 In simplified terms, he asked the questions: Why still work with hypotheses that we then painstakingly check? Why still work with random samples? Big data makes random samples redundant in many cases and tells us what we need to know in real time.

Even though there are of course resolute critics of this stance in science, in the future we will have to ask ourselves whether the old instruments are still the right ones.

Forecasts

Why are corporations, states and secret services interested in collecting so much data? Every seemingly inconsequential piece of information can be valuable in the future when combined with other data. This explains why data collectors have such an interest in saving as much data as possible from diverse fields. It is the variety of the data, the seemingly unconnected individual information that can later, in a new context, sharpen the profile of a person or enable statements to be made on completely different topics.

We have now arrived at the core of big data. Lots of very different data is combined in real time by means of an algorithm, or to put it in simplified terms, by a special program. If a digital bookstore knows which books you have bought in the past, which topics you are interested in and where and how you live, it can suggest books for you to read next.

Google wants to do even more. Eric Schmidt, the CEO of Google, put it in clear terms in an interview with American journalist James Bennet: “We know where you are. We know where you’ve been. We can more or less know what you’re thinking about.”20 What do you think of this idea? That a corporation already knows what you want to read, eat or do next, before you know yourself? The question of how we deal with the forecasts made possible by big data is a key topic of this book. If the precision of forecasts continues to improve and even people’s behavior can be predicted, why can’t we forecast where a crime is about to take place? And why not detain those who are highly likely to commit such a crime before it actually happens? This is currently the subject of intensive discussion, with all its opportunities and dark sides. We will dedicate ourselves to the topic of predictive policing in Chapter 4.6.

We, the data donors

Is your picture of big data slowly becoming more complete? In the age of big data, unimaginably large amounts of data are available to us. Data about each one of you, but also about the things of this world. We establish links and use them to make forecasts. All data is valuable. All data can be important.

The secret services have always seen it this way. However, in the past they had to go to great effort to compile information about you. They had to track you, place bugging devices in apartments and bring together a network of informants. They pressured your friends into revealing private information about you. They watched you and followed your car in order to find out where you were.

Today, the East German Stasi, for instance, would not have to do as much work. After all, we have all willingly become data donors. In Facebook we gladly reveal all the information that secret services once had to work so hard to collect. We talk about which topics we are interested in and who our friends are. We even provide pictures of them, which can be saved directly in the databases of the secret services. Our smartphones document where we go. It is no longer necessary to follow us in a car to find out where we are. On the other hand, the social networks create a fantastic communication platform for us, complete with all the features we appreciate so much. In this book we will repeatedly weigh the risks against the opportunities. The only important point here is that something decisive has changed.

Big data is often associated with prophecies of doom, such as those in George Orwell’s novel 1984. The phrase “Big Brother is watching you” has become a synonym for state surveillance. However, when writing his masterpiece in the late 1940s, Orwell still assumed that the state would organize its constant monitoring of citizens, who are divided into classes, by maintaining a ubiquitous and overbearing presence in their lives, and by creating common enemies and controlling public opinion.

Today, no threats are fabricated in order to monitor you. You deliver the majority of the information yourself, maybe without even realizing it. You are not aware of any consequences, indeed, your life seems to carry on as it did before. Yet something is changing. If you envision the individual areas of life in Chapter 4, you can consider how valuable the promises held by big data are to you. Some of you already feel the presence of data in your lives and ask yourselves whether we can prevent third parties from accessing our data at all if we wish to participate in modern life. This is an interesting question. Let us first draw a clear picture of what has changed from the point of view of companies.

The technical and economic view of big data

The data cocktail has created a new situation in a structural sense, too. We all know that the array of possibilities for transferring data have accelerated our lives. The days of the stagecoach that would carry our handwritten letters will not come back. We no longer have to wait days for an answer. With the advent of e-mail, an exchange is possible in seconds – a far-reaching change that has long since become part of day-to-day life in our society.

From the perspective of companies, however, being able to process large projects and complex data quickly was until recently anything but normal. The latest technological developments enable data to be processed at up to 3,000 times the speed at a comparable cost. How does this technological leap affect us? In order to deepen our understanding of this, we will perform a little thought experiment. Imagine a flight from San Francisco to Frankfurt. Today, such a flight usually takes between nine and eleven hours. However, if one applied the latest advance in information technology to the aviation industry, this flight could take only 20 seconds.

You read it right – 20 seconds! This is reminiscent of the vision of “beaming” that has for decades appeared utopian and fascinating in equal measure, and not just to Star Trek fans. Would you still see this as a “proper” flight? Surely it would no longer be the same. Exactly this is the point. The idea of something being technically impossible and therefore not worth pursuing further has become obsolete on many levels.

In connection with our topic, this means that progress will significantly change the way in which we handle and live with data and information. After all, the latest technologies allow these enormous quantities of data, originating from completely different information, to be processed efficiently and in full.

These changes open up previously undreamed-of possibilities. Interactions at different interfaces are changing – on the one hand between people, but also between people and objects, i.e., devices and machines. You still frequently see yourself as being in control. You have to read operating manuals and know how to make the device do what you expect it to. However, an entirely new user experience is emerging.

Where today we reach for our smartphones, tomorrow we will hold or wear devices fitted with sensors that not only collect data, but also control themselves in many ways. We can already see this form of digitalization in many everyday objects, from cars to our own homes. This user- and device-oriented form of interaction will result in massive changes to our behavior. Manual entries will be fully automated and will be faster and offer far more precision. As a result, data will no longer be created solely by a user; instead, the sensor itself will become a protagonist, enabling processes to be automated which today still require a decision to be made or necessitate the direct intervention of the user. Sensors and machines are thus no longer mere receptacles for commands, but are rather increasingly developing a life of their own. Things are therefore communicating with one another and making decisions for us. Because they know almost everything about us, we assume that they are deciding in our best interests. A number of questions arise here. Are we being manipulated without knowing it? Will we forget how to go through life in a self-determined way?

But let us stay with the potential. Alongside these changed conditions when using devices, it is above all the efficiency that becomes ever more important as data quantities increase. What does efficiency mean? From a technological point of view, efficiency can mean processing in close to real time. An overview of everything is gained, even of the most complicated coordination processes, and processes are set in motion. As a result there are virtually no more technical limits when it comes to saving and processing data. Capacities and processing possibilities in real time are seemingly limitless – a situation that changes the behavior of the system and thereby also how we handle information technology.

Thanks to the new type of user experience and interaction as well as the advent of real-time data processing, the boundaries of the possible are no longer limited by technology, but rather more or less by our own imaginations. We are being given a degree of flexibility in our actions that was previously unknown in this form. In order to release potential, however, it is necessary to change behavior that has been optimized – due to technical limits – over the course of decades and adapted to the respective requirements.

Probabilities become more important than the search for reasons

So what are the consequences when big data and the new technical possibilities become regular features? How will we change or have to change our behavior, and what new options will we be presented with?