We have heard it time and time again: Facebook knows us better than some of our closest friends and Google is aware of secrets, we did not tell anyone else. To most of us, the fact that companies collect huge amounts of our personal data is nothing groundbreaking. We all have either read articles, seen critical documentaries or bingewatched the British TV-series Black Mirror, which portrays humankind in a world of mass surveillance, painting a grim yet possibly realistic future.

Since Edward Snowden’s NSA-papers surfaced in 2013, data privacy has become a huge topic of discussion. At the same time, it seems like the vast majority of people are not concerned about their data being gathered and possibly misused. Have we all accepted the fate of digital transparency and above all:

Do we even have to worry about Big Data in the first place?

The Terminology

You might already have a rough idea but what does Big Data really mean? The most mainstream definition was established by Doug Laney in 2001, when he explained Big Data with the help of three Vs: Volume, Velocity and Variety. Heavily simplified, Big Data is characterized as a big amount of information that is being processed in short amounts of time while containing various types of media like text, E-Mail, audio or video. But what to do with all these zeros and ones?

To companies like Google, unstructured data is pointless until a process of structuring and interpreting gives it real-world meaning. With the help of sophisticated algorithms and machine learning – also known as A.I. – decisions can then be based on otherwise useless information.

The Good

Despite extensive criticism, it goes without saying that there are positive sides to Big Data. In fact, its analysis can be extremely useful in many cases. It can provide you with more accurately tailored advertisements or show only articles that are relevant to your preferences. Corporations like Netflix use their users’ data to predict what kind of content the viewers would be inclined to watch. The incredibly successful TV-series House of Cards might be the most prominent example. Since films of Director David Fincher and films starring Kevin Spacey were doing well on the platform, an algorithm predicted that combining both would be profitable. 46 Primetime Emmy and 8 Golden Globes Nominations have proven this to be more than true and give an idea, how Big Data Analysis can also be used creatively.

In a similar way, these immense amounts of data can help analysts to predict future events. The American LAPD is using citizens’ data to potentially prevent crimes before they even happen. Also the healthcare sector has increasingly found interest in Big Data. Thanks to Electronic Health Records, doctors can diagnose patients’ predispositions more effectively and are able to warn them about diseases they might get in the future and therefore save lives. Assisted by fitness trackers, constantly recording the body’s vital information, scientists and doctors are granted increasing amounts of data. The subject of body trackers brings up another burning question:

In what ways could this data be abused?

The Danger

At the very same time, these advantages could also be considered great dangers. Individualized content that companies provide us with, depending on the data they gathered, is one of many examples. What happens when Netflix only shows films that match your preferences, Spotify plays music you are likely to enjoy and Facebook recommends articles whose opinion you will  presumably agree with. Experts call this phenomenon filter bubble. When your impulses are only limited to what you have already been exposed to before, you are deprived of making new experiences. In actuality, it is the articles that cover a different opinion or films you usually would not have watched that make you grow as a person – instead of becoming more extreme in your world view.

2018’s Cambridge Analytica-scandal exposed how Facebook had been selling their users’ private information to a third party. The data of several millions of Americans was used to make predictions about their personality and has been implemented in the 2016 US elections. Many even argue that this data helped Donald Trump defeat Hillary Clinton. However, it is not only about what Big Data is used for, but also how their algorithms are functioning. With the help of machine-learning, algorithms are the key to unlock the potential of unstructured data. Since they are carrying out the actual interpreting, they are given immense power. Who gets to decide how these algorithms behave – especially when people’s lives are affected by their decisions – for example when it comes to job applications?

“Information is the oil of the 21st century, and analytics is the combustion engine.”
Peter Sondergaard

Researchers have found that Google is more likely to show you advertisements for high-paying and prestigious jobs if you are male. After all, Big Data is only as good as its algorithm. In case the algorithm is biased, it can end up discriminating against certain groups and be sexist or racist in its decision-making.

In that sense, Big Data shares many parallels with nuclear fission, since it both can be very helpful to humans but in the wrong hands can also lead to disastrous consequences. By giving our data away so carelessly, we put all our trust in these companies to use it morally and only to our best interest. For this reason it is important to remember what the main focus of a company really is: Profit.

Should we care

These examples might already be enough to consider paying more attention to how much information we share and to be more curious where it ends up being used. So what is the reason that the broad majority of people still doesn’t care? It simply does not affect our lives in a way that would make a change of behaviour necessary. While many of us benefit from the perks of Big Data, the dangers are hard to grasp. Threats of data-monopolies or biased algorithms can seem very abstract.

At least in Western culture the effects of Big Data are still relatively subtle. In countries like China, we can see first-hand what a society looks like when the government itself uses analytical tools to interpret the data, recorded by surveillance technology. Targeting critics who speak out against the system – for instance online on social media – can be one of the violations of Big Data and demonstrates how dangerous it is to give our data in the hands of others.

Does that mean we should be worried about Big Data and care more about data privacy?

Yes, we should definitely care more. However not because of today’s situation, but because of what Big Data might be used for tomorrow.