Today we bring an article from the guys behind DigIT, which is a student group with roots in ETHOS Lab. The theme is surveillance and privacy, the issue complex, and the point of the article clear..

Read on!

Why make a conference about digital privacy?

Or in other words, why care about this matter?  Why care about digital rights and privacy? Why care about the mass surveillance that is happening? You have nothing to hide, right?

These are the typically questions we get from people who primarily see opportunities when speaking of the level of surveillance we are having in this digital day and age. There are benefits of surveillance such as highly personalized news feeds, customised search results, driving aid and recommendations on which series you should binge-watch next. They see the personal comfort that the extensive personal profiling offers. For it is true in real life as well as in IT; the more knowledge obtained about you, the better service can be provided.

The term surveillance has many definitions, many of them focused around ‚Äúcatching the bad guys‚ÄĚ. Merriam Webster defines it as: ‚Äúthe act of carefully watching someone or something especially in order to prevent or detect a crime‚ÄĚ.¬†¬†But that only covers what the entities controlled by states and governments are supposed to do. It does not cover the activities conducted by the private sector at all.¬†We prefer ¬†the broader definition of surveillance made by David Lyon, as it gives a more clear insight to the embedded problems of surveillance: ‚Äúthe focused, systematic and routine attention to personal details for purposes of influence, management, protection or direction‚ÄĚ David Lyon; Surveillance Studies: An Overview¬†14.¬†With this definition, both personalized big data gathering and surveillance are covered. This reflects the fact that data gathering is not only state driven, but to a great extend also happens in large enterprises.

We have stepped over the verge into a new way of living, where IT is not aiding us only in isolated areas, but is omnipresent. And as with all new inventions and gadgets, we try to apply this magical fairy dust in every thinkable situation, hoping it can solve some of the problems present. But this is  unchartered territory, and no precedence has been made yet. Our fear is that big companies and national agencies are now in a blind gold rush for our data. It is a competition for information in which we are all both the resource and the losers.

The output of this new type of data gathering is profiles that in greater details than ever before generates an image of who you are. It is based on your conversations, movements, friend network, address, sleeping habits, period cycle etc. These profiles are then used to classify you when you are seeking a new job, purchasing insurances, getting your mortgage or how likely you are at doing crime after being released from prison. And you might think that this is a good thing. That you get the real price for your insurance instead of the standard one given to everyone else. That if they just get a picture of you that is detailed enough, you will be treated in a special and more fair way.

The problem here is twofold. First off, you can never get a true 100% accurate picture of a person. All human beings are complex, irrational and diverse, to an extent that it close to impossible to create a totally accurate profile of each individual.

Secondly, the evaluation algorithms that make the final conclusions are often proprietary, closed-source, and act upon averages of statistics.¬†And so, as is the case with the sorting hat from Harry Potter, we all believe in the result, even though it is not transparent how or why the results are achieved. And when you combine less-than-perfect data with algorithms that at best acts ‚Äúcorrectly‚ÄĚ on flawed data, and treat it like it is an undebatable truth, then you have a problem.¬†And you cannot object, as you do not know how the scores are generated.

Let us also be clear: Data in itself is neither bad nor dangerous. When you go to the hospital for example, you want to be monitored from head to toe. But the use of data needs to be regulated and controlled and first and foremost controlled by the people that either actively or passively emits the data. Perhaps you actually want to give your information in return of the service provided. But we need to make that decision based on the full knowledge of how this data harvest can affect us. It is imperative that we get an informed and ethical view on the surveillance and data harvesting through our education.

Our goal is to make sure that people can keep as much of their privacy as possible, in this huge virtual goldmine that is data-collection. This is why we set out to arrange the conference in march, just like the smaller one we did last year. This semester we dig even deeper with 9 after-hours events, 56 high school visits, and 2 larger events. Uber is not a taxi company, Tinder is not a dating app and Facebook is not a social media platform. They are all companies that base their earnings on personal profiling of individuals for retail. And we need to be aware about the implications that the omnipresent surveillance has on our everyday life. How you choose to act is all up to you, but you need to make your decisions based on knowledge of the consequences.

/DigIt