The Social Solutionism of Big Data

The Social Solutionism of Big Data
Image Source: Google

I recently came across an article about an experiment where the author tries to opt out of big data. Technological solutionism and big data can be an important factor in one’s every day activities. In fact, big data is already an integral part of our lives. Our always connected devices generate data every second logging our activity and unique personal preferences that we make online.

Furthermore, our online actions as consumers produce data which in its turn can be used in the process of predicting tendencies in human behavior. In the age of data and analytics, everything we do generates data. Always on technological devices, living creatures, everything can be explained through the means of data. And it looks like all of them can store and produce data as well . Perhaps one day we will be able to create, store and consume data by ourselves and for ourselves. It seems like data is one of the top words that will characterize our century. Or at least a good part of it.

The Inevitable Solutionism

In his “To Save Everything, Click Here”, Evgeny Morozov argues that the folly of the technological solutionism leads to a world where the power of algorithms eradicates imperfection. And where the rules imposed by the Silicon Valley shape our future (Morozov, 2013).

The author provides some examples for such a technological solutionism inspired by “Zuckerberg’s tyranny of the social”. There we find evidence that “activities get better when performed socially” (Morozov, 2013). The BinCam project which makes our bins “smarter” (by taking photos of what you just have thrown away), “more social” (by uploading these photos to your Facebook account) is one of these examples that promise to save our planet.

Another interesting example that Morozov gives is the prototype teapot. It  “either glow[s] green (making tea is okay) or red (perhaps you should wait)” (Morozov, 2013) the hardware of which “queries Britain’s national grid for aggregate power-usage statistics” (Morozov, 2013).

Algorithmization of Ethics?

But as Morozov suggests, nowhere in the “academic paper that accompanies the BinCam presentation do the researchers raise any doubts about the ethics of their undoubtedly well-meaning project” (Morozov, 2013). The situation is similar to the case of the teapot prototype where “social engineers have never had so many options at their disposal” (Morozov, 2013). He further argues that resolving complex social problems with the help of the right algorithm is more likely to cause unforeseen effects and repercussions that can generate “more damage than the problems they seek to address” (Morozov, 2013).

The more big data and analytics become integral part of our lives, the more difficult it is to refuse to let technology control simple daily activities. And doing your everyday tasks the old-fashioned way seems more complex and more impossible. Even a simple attempt to opt out from marketing detection (like using Tor for browsing Facebook or Twitter) can make your online activity look suspicious and illicit (Vertesi, 2014).

But as Morozov suggests, big data without any connections to social networks can do quite positive things too. He mentions the BigBelly Solar and its positive impact on cutting “garbage-collecting sorties from 17 to 2.5 times a week” in the city of Philadelphia and the Street Bump project where, thanks to motion detectors in smartphones, an app helps with reporting potholes on the streets of the city of Boston. In other words, people use data for good or bad purposes. And the path we choose depends on our shared vision of the future of our society.


Morozov, E. 2013: To Save Everything, Click Here: The Folly of Technological Solutionism, New York, NY: Public Affairs.

Vertesi, J. 2014, My Experiment Opting Out of Big Data Made Me Look Like a Criminal, Last Checked: 17/10/2017, Retrieved from:

Relying on social media for data in disaster response

Working for Médecins Sans Frontières (MSF), I’m required on the occasional weekend to check MSF’s Twitter account for questions and activity to respond to. The account is currently followed by 100,000 followers.

On a recent weekend, I came across a tweet at @MSF which got me thinking:

My response was as follows:

In the last few weeks, the world has been hit by two Category five hurricanes through the Caribbean and the United States (Wikipedia, 2017)– Hurricanes Irma and Maria – and two powerful earthquakes in Mexico. (Médecins Sans Frontières, 2017) My thought was, how much information do we get in disaster response such as the events in the Caribbean and in Mexico based on tweets such as these? How often do we see people pointing responders – using social media – in the direction of people who need help? People flagging what the scale of disaster is? And then when the response does come, how much is social media a tool for where can people go to help, or even criticise the repose?

In Hurricane Irma, first the scene was set:

Roisin Read and her colleagues outlined in a paper on humanitarian response information systems that the hurricane that struck Haiti in 2010 first outlined the potential of social media in humanitarian response:

At first the goal was simply to map the unfolding crisis and identify where people had moved, and it was not connected to any official humanitarian response efforts. However, as the digital map grew, emergency responders began to see how it might assist them. The processes of the digital humanitarians began to change to take a more active (though geographically remote) role in the response… the Haitian crisis highlighted the fact that real time data could now feature in humanitarian responses. (Roisin Read, 2015)

Social media – in this case Twitter, using data on phones, perhaps one of the few ways to get information out in the aftermath of a disaster like this – allowed Barbuda to tell the world just how bad things were:

The situation throughout much of the Caribbean after Irma was desperate; but social media tools allowed responders to consider what to do next – “good contextual knowledge is essential in designing humanitarian responses.” (Roisin Read, 2015)

Next, comes the help – targeted to those areas that need it most:

Büscher et al note that crowd-sourced information in the hands of digital volunteer networks ‘can support faster and more detailed awareness of the needs of affected communities and the nature and extent of damage. (Roisin Read, 2015)

…or the fundraising campaigns…

And few disasters pass by without some criticism being levelled at one or more responding institutions. In this case, the British government received stinging rebukes on their slow response, in contrast to the French government – and in contrast to one of the main points of using social media tools in disaster response “is that data can be gathered and conveyed at greater speed, with an impact on the timeliness of humanitarian responses.” (Roisin Read, 2015)

So is social media tools like Twitter used in response to disasters? Yes. Are they useful for responders? Yes, absolutely. As Read and her colleagues conclude, “The promise of greater accuracy and speed of information gathering, together with the novelty aspect that technology can bring, may constitute material power and demand-resource reallocation within international organisations and INGOs.” (Roisin Read, 2015)

The power of social media behind disasters is that they can tell the whole story. From initial disaster – often even capturing the disaster itself – to the consequences, to the response, to the response assessment.


Médecins Sans Frontières. (2017, September 21). Mexico: MSF assists people following Mexico City earthquake. Retrieved from Médecins Sans Frontières:
Roisin Read, B. T. (2015, December 22). Data hubris? Humanitarian information systems and the mirage of technology. Third World Quarterly.
Wikipedia. (2017, September). 2017 Atlantic Hurricane Season. Retrieved from Wikipedia:

The Importance of Being Counted

The title reminds me of the Norwegian children’s story by Alf Prøysen about the little goat who counted to ten. In the story, the goat begins to count himself, and when he meets his friends he asks if he can count them too. «I don’t think I have the courage, I’m not even sure my mother would let me», says his friend the calf and tries to get away, but the goat counts him anyway: «I am one, you are two.»

The calf starts to cry and calls for his mother, and when the mother cow arrives, the goat counts her, too. «Now he counted you too!» says the calf, and the mother cow becomes furious. The calf counts more and more animals as he is chased around, and in the end they arrive to a river and the goat jumps on to a boat with all the animals after him.

The skipper on the boat panics and cries out: «Does anyone here know how to count? This boat can only take ten animals!» The goat counts all the animals: they are ten, so they are safe. The story ends as all the animals applaude the goat and he becomes the skipper’s helper on the boat.

You might say that this example is a bit silly and childish, but on the other hand it certainly does illustrate both the skepticism towards and the importance of being counted.

Taylor and Schroeder (2014) talk about the importance of being counted (Taylor and Schroeder, 2014, p. 506) when referring to Morten Jerven’s highly interesting book «Poor Numbers» about the lack of accurate data on Africa and in African development work. According to Jerven’s experience and findings, the statistics on African economy are inaccurate, arbitrary and misleading. Consequently, of course, important decisions are being made by actors in African development on the basis of poor numbers.

This illustrates one central example of the relevance of data for development and, more precisely, the importance of gathering accurate (and enough) data to be used in development policy. It illustrates one of the major problems when it comes to data gathering in developing, low- and middle-income countries is that data gathering is poor, or even absent (Taylor and Schroeder, 2014, p. 504).

And why is it important to be counted? We have already answered that question: simply said, because decisions are made and measures are implemented on the basis of the data. For example, counting the population in a country is «vital for the measurement and practise of development» (Jerven, 2013, p. 56). Therefore, being counted also means getting access to resources. (Taylor and Schroeder, 2014, p. 504).

Another example of the importance of being counted is Aadhaar, a biometric ID system database in India. The Aadhaar number is a 12-digit number that Indian citizens receive on the basis of both demographic (name, age, etc.) and biometric (fingerprints, iris scan) information.

Aadhar can be used, citing from the Unique Identification Authority of India’s website: “a basis/primary identifier to roll out several Government welfare schemes and programmes for effective service delivery…” and “is a strategic policy tool for social and financial inclusion, public sector delivery reforms” and so on.

The problem is that not everyone can be identified by their fingerprints or by an iris scan. As pointed out by Taylor (2017), people who do heavy manual work may not have fingerprints and people who are malnourished may not have good enough iris scans (Taylor, 2017, p. 5). Therefore, the Aadhaar system excludes the poorest part of the population.

That being said, according to Taylor, it seems like Aadhaar recognizes the challenges of the system and is working on how to reach more of India’s citizens (ibid).

For Morten Jerven, a solution for poor numbers in African economy is more knowledge and research emphasizing the relevance and quality of data in (African) development. A first step towards better data is certainly made by recognizing the problem. It now remains for researchers in development to pick up the thread.


About Aardaar, from the UIDAI website, retreived from on October 11th, 2017.

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

Sandnes (2014), Geitekillingen som kunne telle til ti, Sandnes media, retreived from on October 10th, 2017.

Taylor, L. 2017: What is data justice? The case for connecting digital rights and freedoms on the global level, draft paper.

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

Big Data from a Feminist Perspective: #HerNetHerRights

Big Data from a Feminist Perspective #HerNetHerRights
Image Source: Google

One of the main topics on our blog is big data and its importance in international development and human development. In my previous posts I had the opportunity to cover the impact of big data on development and the challenges of using big data for humanitarian purposes. And I talked about how big data and new online technologies pose some risks related to privacy and ethics. In other words, how problems from our everyday ‘analogue’ life become real issues in the virtual reality online.

Online violence, especially violence against women and girls, is one of the many serious issues that arise as a consequence of our always-connected world.

There are initiatives and projects that fight against these kind of inequalities that tend to form online. And to analyze the tendencies of online violence against women in Europe, the European Women’s Lobby (EWL) began to lead a project called HerNetHerRights.

What We Need to Know About the #HerNetHerRights Project?

  • Its main purpose is to fight against online violence where women and girls are the victims of male violence.
  • There will be an online conference on October 13th 2017 where activists, researchers and survivors will come together to discuss the current trends and new challenges related to the problem of online violence against women and girls.
  • The sponsor of the #HerNetHerRights project is Google.
Image Source: Twitter - #HerNetHerRights
Image Source: Twitter

The event is part of the annual week-long event called “European Week of Action for Girls 2017”. There will be a discussion on Twitter after the conference. And participants can further comment on the issues reported during the conference.

HerNetHerRights’ conference agenda includes discussions around different forms of online violence, such as:

  • Feminist implications of big data and privacy
  • Analysis of reports on cyber violence against women
  • Sharing experiences from first hand

Big Data and Privacy from a Feminist Perspective

The topic that I’m personally interested in is the one that will be covered by Nicole Shephard. During this event, she will be sharing her experiences with the ‘feminist implications of big data and privacy’ (European Women’s Lobby, 2017) and I personally expect her to also refer to her work called “Big data and sexual surveillance” where Shephard shows the challenges and opportunities that women (and not only) encounter when data, surveillance, gender and sexuality meet together.

In her “5 reasons why surveillance is a feminist issue” Shephard refers to De Lillo (1985) arguing that the “fictional speculation that “you are the sum total of your data” has proven quite visionary” (Shephard, 2017).

In conclusion, big data and the use of technologies for analyzing it don’t seem to be neutral. And they have their own biases. For example, Shephard argues that “racist algorithms” such as Google’s “unprofessional hair” results can be found everywhere in our daily life (Shephard, 2017). And, unfortunately, the end results are not neutral at all. But we should also consider the fact that errors happen and “unprofessional hair” can be as unintentional as “what is the national anthem of Bulgaria”.


European Women’s Lobby, 2017, Last Checked: 8/10/2017, Retrieved From:

Nicole Shephard, 2016, Big data and sexual surveillance, Last Checked: 8/10/2017, Retrieved From:

Nicole Shephard, 2017, 5 reasons why surveillance is a feminist issue, Last Checked: 8/10/2017, Retrieved From:

Taylor, L. 2017: What is data justice? The case for connecting digital rights and freedoms on the global level, draft paper.

Data for Development – contributions from the Nordic countries

OECD is one of the international institutions that makes use of data produced by our use of technology, such as mobile phones and internet, in their research and policymaking (Taylor and Schroeder, 2014, p. 505).

At the end of this month, on October 30th, OECD will release its Development Co-operation Report for 2017, Data for Development. In the introduction of the report, OECD stresses the importance of big data and the data revolution for development in a broad sense: “more and better data can help boost inclusive growth, fight inequalities and combat climate change. These data are also essential to measure and monitor progress against the Sustainable Development Goals.”

Furthermore, the report stresses the fact that the lack of good data is still evident in most developing countries, and asks central questions: Why are over half of deaths and one-third of births worldwide unaccounted for? Why is investment in statistical capacity (…) not a priority for most providers of development assistance?

The report calls for a strengthening of national statistical systems and will present measures to “make data work for development”.

The profiles of different countries’ contributions to data for development is already published. This post briefly looks at the contributions from the Nordic countries in the report: Denmark, Norway, Sweden and Finland.

According to the report, more and better data is getting more important than earlier for Denmark when it comes to reporting on the Sustainable Development Goals (SDGs). Until now, it has not been a high priority. Denmark aims to “improve statistical production and promote the use of data by policy makers, civil society and citizens”.

During 2013-2015, Denmark committed on average 12,7 million USD per year to finance statistical capacities and systems in developing countries.

Norway contributes to strenghtening data for development through its national statistical institute, Statistics Norway. Among other things, Statistics Norway collaborates with the UN’s High Commissioner for Refugees “to establish international guidelines for collecting and producing statistics on refugees and internally displaced people.”

Norway aims to “improve statistical production and data literacy and to strengthen co-ordination among development partners” and it contributes in helping developing countries “to build up civil registration and vital statistics”.

This year, Statistics Norway participated in an expert panel meeting where it provided input to the Development Co-operation report, stressing the importance of building holistic and sustainable national statistical systems (p. 10 in Statistic Norway’s newsletter “International Development Cooperation at Statistics Norway”, June 2017).

Norway launched a white paper this year in where it stresses the importance of good data and statistics in development cooperation.

Norway committed on average 15,0 million USD per year in 2013-15 to finance statistical capacity building.

Countries where Statistics Norway has Institutional Cooperation:

Source: Statistic Norway’s newsletter, June 2017

Data for development or building up statistical capacities is an important part of Sweden’s development work. It is included in Sweden’s Budget Bill and the new policy framework for Sweden’s development co-operation. Sweden contributes in improving statistical production and literacy in development countries and offers technical assistance and financial aid. Among other things, it gives financial support to the UN Global Pulse, “which harnesses big data for development and humanitarian action”.

Interestingly, Statistics Sweden has collaborated with Burkina Faso and Mali on establishing “continuous household surveys” to help building up statistical capacity.

Sweden committed on average 20,89 million USD per year to finance statistical capacity in 2013-15.

The OECD report does not contain any information on Finland’s contribution to data for development. Finland’s contribution this field therefore remains unanswered.

However, Finland contributed a much smaller amount of money than its Nordic neighbours (1,51 million USD per year in 2013-15) to statistical capacity building, which indicates that it is not a priority.

The full country profiles are available here:


OECD (2017) Development Co-operation Report 2017: Data for Development, OECD Publishing, Paris. Retrieved 2nd October 2017 from

Statistisk sentralbyrå (2017): International Development Cooperation at Statistics Norway: A newsletter from Statistics Norway’s Division for Development Cooperation, June 2017. Retrieved 2nd October 2017 from

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