Global Control: Your Toaster’s Double Life

Germans have a special relationship to privacy. This undoubtedly has to do with experiences gained in the course of German history: Stasi spying in East Germany and observation and surveillance under the Nazi regime. In any case, it was not an accident that in 1983 thousands of people took to the streets to protest the census that the government intended to conduct. Legal actions went as far as the Federal Constitutional Court, bestowing upon the Germans a new basic right: informational self-determination – that is, the right to determine who can store and process what data about me. 

This right served as a guidepost for German data protection legislation, which also had, and still has, international influence. For example, on the new EU Data Protection Regulation, which is due to go into force in 2018. You can argue over how informationally self-determined we can still be in a digitalized world; but ideals can also have an effect.

If political measures against surveillance have proven ineffective, technical ones have been all the more effective. Since Snowden, a regular race for encryption has broken out. Apple’s iMessage, Facebook‘s WhatsApp and many other popular services are now securely encrypted. That this is possible at all is because the “cryptographic wars” were already won in the 1990s. At the time, American politicians sought to prevent the spread of secure encryption. Activists were able to establish the technology to the extent that politics could no longer rein it in. Recently, commercial internet services, which need to encrypt transactions, have been a key factor.

But today politicians are again up in arms and want to force Apple and WhatsApp to set up backdoors for the authorities and so, inevitably, make encryption insecure. Are we standing at the threshold of the next cryptographic war?

So enough with the “internet of people”. This is what the industry seems to think, and has recently been building a computer into every TV and every light switch. But the “internet of things” has also created new problems because, as we all know, computers tend to be insecure. A DDoS (Distributed Denial of Service) attack is when a server is bombarded with so many requests that it collapses. Hackers bring this about by using armies of remote-controlled computers, so-called “bot armies”.

Bot armies have been around for a long time, but they have never been as large as they are today. It turns out that computerized things can all too easily be “recruited” – that is, hacked – because of badly maintained software. With the internet of things, armies of unknown dimensions have arisen, which have recently managed to bring even important infrastructures used by Twitter and Amazon to their knees. Who knows – maybe your toaster was part of it.

You want to buy something. Come to Amazon! Taxi? Take an Uber. Accommodations? Airbnb. You have your friends on Facebook, you read the news on Twitter and chat with your family on WhatsApp about what you watched this evening on Netflix. We have long been living in the world of platforms. Big, monopolistic technology providers have pushed themselves between us and our needs, regulating our lives. And it’s so comfortable! But platforms are not normal businesses.

We have manoeuvred ourselves into a dependency in which nothing works without them. States have long been turning to Facebook to solve their problems. Mark Zuckerberg has mutated into a politician; perhaps the most powerful politician in the world – doesn’t he manage the data of two billion people? How can we limit the power of platforms without hurting ourselves? Because few of us want to live in a world without Amazon and Facebook.

And you? Take our self-testand discover whether you're careless or cautious with your data.

Data are not only stored and collected but above all analysed. Before, people spoke of “data mining”; today, they call it “big data”. Big data means first of all that the amount of data to be analysed is too big to be processed by a single computer. For this reason, methods have been developed to distribute the data sets to several computers, which then analyse them in parallel. Interestingly, the larger the quantity of data, the more conclusions that can be drawn from it. In statistics, this is called the “law of large numbers”. The larger the sample, the more precisely the statistical effects can be measured.

Many people already believe that the behaviour of human beings can be predicted. Such prediction, however, has worked so far only for masses of people, almost never with individuals. For example, data scientists can predict that 26.4 out of a hundred unmarried bus drivers will drink a beer after work – but not which ones will. For purposes of knowing whom to target for after-work beer advertising, however, this suffices.