A polarized discussion


When reading the material concerning big data, most of the time it seems very polarized. It is either a dangerous and dystopian image that is presented (O’Neil, 2016), or, as Ilario wrote in a previous post, almost Evangelical in which big data and algorithms will be our saviour as in Krings Ted Talk.

In such a polarized discussion, I find it hard to actually reach any conclusions in regards to my own opinion of big data. Of course there are clear benefits – just seeing the mapping system and methods Krings present, shows that there are areas in which big data can become a real game changer and as such save many lives. It is thus not hard to see big data and the algorithms used to draw conclusions, as the instrument that sharpens the blunt tool of development work, as I wrote in my previous post. And as such it can create a situation in which the effects of development or humanitarian work are much greater than before, and can reach the people who will benefit from it the most.

But, I also feel sceptical for the same reasons. I agree with the risks presented in regards to our privacy (Spratt & Baker, 2016) and I find it scary –even living in a democracy as Sweden – when I ask myself what kind of information “someone” might have on me. But, I can also see it as the rules of the game. As Ilario said in one of our conversations, it is the payment for the access you get.1But, in regards to development and humanitarian work, I fear that the digital divide and the possible bias (Spratt & Baker, 2016) it might create, may harm the weakest people in the hierarchy even more. A sentence that really has stuck with me comes from Taylor and Schroeder (2015) and it is “to be counted means potentially obtaining access to resources”. The question is who will be left out.

As I wrote in my post “Big data vs Liberalism”, I also see the risk of big data being transformed in to an ideology that will have great impacts on how we view and construct our world, and I fear that it bares to strong of a resemblance to neoliberalism in the sense that “the system is like this and works like this and everyone must adapt to it”, and in so doing, removing any type of human responsibility from the decision-making and the results that follow. In 30 years, will we wake up once again and say “oh, so that didn’t work either – people have not been helped by the system at all, quite the opposite; it has created even more divides”? I fear that we have not learnt our lesson after the demise of neoliberalism, but continue feeding into the same system, only it will not be the market and money that controls the world; it will be data and the algorithms.2As I see it, as long as we follow the conclusions presented by Jerven (2013), and connect all the data gathered to contextual and cultural knowledge, an understanding of the origin of the data and where it might be flawed, use human eyes and annalistic abilities as well as our previous knowledge, we can control the data instead of having it control us, and thus be helped by the possibilities and opportunities the data can create. It all comes down to us.


Krings, G, 9 juni 2016: How telecom data can radically change the way development aid works at TEDxUCLouvain. Retrieved 28/10/2016 from https://www.youtube.com/watch?v=wMWYLgj1ydw

Spratt, S,. Baker, J 2016: Big Data and International Development: Impacts, Scenarios and Policy Options. Brighton: IDS.

Taylor L, Schroeder R. 2015: Is bigger better? The emergence of big data as tool for international development policy. GeoJournal 80: 503-528.

Jerven, M. 2013: Poor Numbers: How We Are Misled By African Development Statistics and What To Do About it. Ithaca, NY: Cornell University Press.

O’Neil, C (10.18.16) Big Data Algorithms Manipulating Us. Wired. Retrieved 28/10/2016 from https://www.wired.com/2016/10/big-data-algorithms-manipulating-us/

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