Thank you for reading!

This blog exercise has been a part of our path to a Master’s degree in Communication for Development. It has been a fruitful journey. The blog exercise is now completed and we thank you for reading! We also hope this blog will give inspiration to other ComDev students.

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Blind spots: how a lack of reliable data undermines development

(c)Markel Rodondo, Conakry, Guinea

Despite its critics, vaccines are the most cost-effective and efficient forms of preventing disease. Yet millions of kids die from vaccine-preventable diseases – like pneumonia and measles – every year.

Despite routine vaccination and vaccination campaigns, many developing countries have repeated outbreaks of disease.  In 2013, Médecins Sans Frontières vaccinated 2.5 million people in response to measles outbreaks; half of those were in the Democratic Republic of Congo. (MSF, 2014)

So where do governments and aid agencies go wrong in not getting the vaccines kids need?

A lack of data – in many forms – is crucial. And this is where governments, in a particular, have a responsibility to improve data collection. Many country governments have blind spots when it comes to how many of their nation’s children are properly vaccinated, or even where their people live.

As Kazungu and Adetifa observe:

Good quality vaccination data is required to understand inequities in access to vaccines. Most vaccination coverage estimates in LMICs are from administrative reports that tend to overestimate coverage, due to errors in the number of vaccine doses administered and/or invalid assumptions about the size of the target population of children. (Jacob Kazungu, 2017)

Much of this lies at the foot of governments. Morten Jerven argues – with good reason – that the interest, or more often the lack thereof, in gathering data on their populations’ health, wealth and wisdom is often down to whether its in the best interests of the politicians. As he states:

Data collection is often done in accordance with a governance imperative: statistics are collected and compiled in order to facilitate particular policy agendas. Conversely, a lack of data may signal and facilitate inaction. (Jerven, 2013)

Overestimation of vaccination coverage is unfortunately a common theme throughout many states in Africa. In 2009, Burkina Faso experienced a measles outbreak with over 50,000 cases – to the surprise of many, it turns out. “[the country’s] vaccine coverage estimates preceding this outbreak suggested the country was near elimination, not at risk for a large outbreak.” (Nita Bharti, 2016)

It’s not only a lack of data on vaccination coverage rates that have an impact on disease outbreaks. The ability of a country to be able to provide vaccines for their country’s children in the first place has an impact. The price a country pays for a vaccine is a large part of this. Pharmaceutical companies are notoriously opaque about pricing – and the pneumonia vaccine is a great example of this.

What each country pays for this vaccine is largely a secret. Countries of like-sized economic status – take the BRICS, for example – don’t know what each other is paying for the pneumonia vaccine.  This lack of data “impacts… international or national policy evaluation, and these evaluations in turn have direct implications for issues of governance.” (Jerven, 2013) In this case, whether or not a government can afford to buy a life-saving vaccine that could protect kids against a disease that kills a million children each year.

Médecins Sans Frontières launched a campaign – called A Fair Shot – in part to highlight this lack of data around the price of the pneumonia vaccine. Here’s a short, funny video that explains the part of the campaign where prices are hidden:

The campaign was designed to ask two pharmaceutical companies – Pfizer and GlaxoSmithKline – to reduce the price of the pneumonia vaccine to $5 per child in developing countries. In the early part of the campaign, it highlighted that countries don’t know what other countries are paying for the vaccine, therefore they had to negotiate a price with the companies ‘blind’.

To highlight the issue, and solve the problem, MSF, working with the Guardian newspaper, decided to crowdsource the prices of the pneumonia vaccine in different countries. They asked readers and supporters to visit their local pharmacy or hospital and ask for the price of the vaccine, and then report it to the Guardian or to MSF.

MSF and the Guardian used social media posts to boost this ask:

The request to ask the public to send data on vaccine prices worked. MSF and the Guardian were able to source prices for the pneumonia vaccine from countries and sources that had hitherto been unknown or unavailable.

While these blind spots – or lack of data – in vaccination exist, there are way around them. Governments can do more, “but data availability is a good indicator of political commitment.” (Jerven, 2013) Governments will source the data they require, and respond to the needs accordingly – but only if the political will to do so is there.

 

Works Cited

Jacob Kazungu, I. A. (2017, February 15). Crude childhood vaccination coverage in West Africa: Trends and predictors of completeness. Wellcome Open Research.

Jerven, M. (2013). Poor numbers: how we are misled by African development statistics and what to do about it. Ithaca: Cornell University Press.

MSF. (2014). International Activity Report 2013. Médecins Sans Frontières .

Nita Bharti, A. D. (2016, October). Measuring populations to improve vaccination coverage . Scientific Reports.

 

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(Big) Data’s Entry Into Our Lives: Should We Worry?

In my previous post I talked about why it is important to be counted (link). With the story in the beginning, the post also touched upon the skepticism towards being counted. In this blog, we have discussed some of the negative sides of big data in development and what impact data and social media can have in democratic processes, in terms of data justice. Here, I will reflect on the inevitability of data in our everyday lives. Does it only have good sides? Can we trust that information about ourselves will not get misused? Are we being surveilled and should we be skeptical?

As we have pointed out in our previous post on this blog, it becomes more and more difficult to resist the effects that technology has on our lives, in terms of for example the marketing on social media such as Facebook that bases on data produced from our use of internet. As users of various apps on our phones, «we» (at least the younger users of these apps) have almost stopped worrying about the information that the apps ask us to give in order to fullfill their function properly: information about our current location, our phone number, our photos on Facebook or on our phone, etc. Correct me if I’m wrong, but the user of the app will often provide this information to make the app work as well as possible.

Another example before we go on: I recently read an acticle in the Norwegian newspaper Aftenposten about how Estonia has digitalised 99 % of its public services, based on a digital infrastructure called X-road. Estonia has introduced services such as e-Voting, e-Health (digitalised medical journals), e-Tax, e-School and e-Residency, to name a few. Estonia has become a leading country in digital innovation, and according to the e-Estonia website, Estonian digital solutions have been exported to 35 countries. Estonia now holds the presidency of the Council of the European Union, and has pronounced that its «first priority will be to put free flow of data across borders on the agenda» (Braathen, 2017, p. 26).

An Estonian e-Residency card. Photo: Masayuki Kawagishi

These are examples of the fact that data-producing technologies are an inevitable part of life in the 21st century, and trying to resist it might be seen as going back in time in terms of technological development. What is the point, then, to dwell upon the potential negative effects of them?

My first immediate answer will be: because they are an inevitable part of our lives, and because data, and big data, could bring along reasons to be skeptical. Estonia’s e-Residency service has been criticised for potentially attracting criminals who might misuse the system to avoid punishment by operating via Estonia (ibid). Also according to the article in Aftenposten, Estonia’s different public agencies’ websites as well as the president’s website were hacked in 2007. However, according to the article, there has been no cases of misuse of e-Residency so far, and the cyber attack was successfully stopped and followed by the establishment of the NATO Cooperative Cyber Defence Centre of Excellence in Tallinn.

In his book «Digital Humanitarians», Meier addresses the problem of false data in social media and its effect on humanitarian work. Using examples from aid work after the earthquakes in Haiti and Chile in 2010, Meier shows how «as a result of false information, urgent humanitarian aid could be allocated to the wrong area, for example, which could result in wasted time and resources; at worst, it could cost lives» (Meier, 2015, p. 33). Other examples are fake photographs of the hurricane Sandy in 2012 and false information on Twitter about the White House being attacked in 2013. (Meier, 2015, p. 34). But, as Meier shows, information from social media can be verified using tools such as for example crowd computing and artificial intelligence. This does not solve all the problems, but the examples show that advanced tools for facing these challenges have been developed.

Should we be worried, then? In terms of our own privacy, we should at least be conscious of how we use technology and social media and what information we provide about ourselves. Technological infrastructures such as the Estonian one has proven to be safe, although some «threats» against it have occured.

As Spratt and Baker conclude, big data will continue to have a large impact, and it will vary from country to country how they make use of the data. Big data definitely implies risks, but they will be more «acute» in some countries than in others (Spratt and Baker, 2016, p. 33). To secure that the benefits of big data will apply in both developing and developed countries, a framework «that protects people’s rights but also gives them the confidence to share the data that are needed for these benefits to be realised» is needed. Giving individuals, communities and societies access to and control over their own data is at the heart of this» (ibid). Hopefully, an aknowledgement of this need from research on big data should give us even less reason to worry.

References:

Braathen, F. (2017): Heldigitale Estland vil snu opp-ned på Europa: Hvordan klarte den lille eks-sovjetrepublikken å bli et av verdens mest digitaliserte samfunn? Article in Aftenposten A-Magasinet no. 41, 13th October 2017.

Meier, P. (2015): Digital Humanitarians: How BIG DATA Is Changing the Face of Humanitarian Response. Boca Raton, FL: CRC Press.

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

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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.

References

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: http://time.com/83200/privacy-internet-big-data-opt-out/

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Missing maps – using data to aid development from your armchair

Imagine being an ambulance driver and you get a call to assist someone who’s had a heart attack. You get the address, but it’s not one you know. What do you do? Try to find it by typing the address into Google maps, for example. But Google maps is telling you it doesn’t exist. You get this as the result:

But you know it exists. What’s an ambulance driver to do?

Same situation, but you’re an aid worker and there’s a big disease outbreak. You and your colleagues need to go door-to-door advising people of how to take precautions to prevent disease and watch for disease symptoms to seek treatment. In rural South Sudan, for example, Google Street View hasn’t quite made it down there. And Google maps is unreliable. It’s not showing houses, or roads, or even entire towns on the map. But they exist.

This was a problem a number of NGOs were discovering in their aid work, and it was proving a hindrance. Lives were in danger, or even being lost, as aid workers didn’t know where their house or their town was exactly located when they responded to outbreaks of disease or natural disasters.

Enter the Missing Maps project.

Missing Maps was established by a number of NGOs, including the British and American Red Cross, and Médecins Sans Frontières, to properly map areas using satellite data. Here’s a short vid explaining the project:

As Read, et al assert,

Essential to new mapping techniques are imaging technologies, in particular satellite data, the increasing use of which ‘is radically reshaping the ways different groups comprehend space and place.” (Roisin Read, 2015)

It’s because of Google maps, and the thousands of satellites floating around in space, that we have the essential data available to map these places.

It’s vital work, enabled by not only satellites orbiting above the earth, but also development in digital communications, and social media. Yet some scholars may doubt this, as digital humanitarianism is seen by some “to be driven by what is possible rather than what is needed, to the extent that, as Trevor Barnes noted with regard to the data revolution in geography: ‘computational techniques and the avalanche of numbers become ends in themselves, disconnected from what is important’.” (Roisin Read, 2015) I disagree with this assertion. Data is knowledge, and data knowledge in aid work enables a lot of the work and development being done today.

The social media aspect behind Missing Maps is interesting and bears some thought. First, groups of people come together in ‘mapathons’, to use data to map areas together. Often mapathons are promoted in advance on social media, or in fact during it:

Is it possible to classify young people engaging in Missing Maps as ‘Slacktivism’? Some had noted that Slacktivism is used to describe “

Some journalists have adopted the label ‘Slacktivism’ or ‘Clicktivism’ to describe “contemporary forms of youth engagement arguing that online social action satisfies youths’ moral and psychological needs for engagement, thereby excusing them from participating in traditional offline forms of engagement”. (Daniel Lane, 2017)

Missing Maps, it could be argued, meets the description of online youth and social action satisfies moral and psychological needs for engagement. However, I’m not convinced that it is actually a case of letting youth off the hook in terms of offline forms of engagement, because Mapping in itself is not “‘easy’ and tokenistic, but in fact entail[s] a great deal of social investment” (Daniel Lane, 2017), and thereby doesn’t ‘inhibit’ meaningful social action and engagement, as it is such in itself.

Data, digital development, social media, and loosely framed Slacktivism have enabled the creation of Missing Maps, born out of a necessity for humanitarian aid workers to find where exactly they’re going. It might be digital development from the comfort of an armchair, but the data used still serves essential humanitarian development purposes.

 

 

Works Cited

Daniel Lane, S. D. (2017, May 15). Sharing beyong Slacktivisim: the effect of socially observable prosocial media sharing on subsequent offline helping behaviour. Information, Communication and Society.

Roisin Read, e. a. (2015, December 22). Data hubris? Humanitarian information systems and the mirage of technology. Third World Quarterly.

 

 

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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.

 

Bibliography
Médecins Sans Frontières. (2017, September 21). Mexico: MSF assists people following Mexico City earthquake. Retrieved from Médecins Sans Frontières: http://www.msf.org/en/article/mexico-msf-assists-people-following-mexico-city-earthquake
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: https://en.wikipedia.org/wiki/2017_Atlantic_hurricane_season

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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.

References:

About Aardaar, from the UIDAI website, retreived from https://uidai.gov.in/your-aadhaar/about-aadhaar.html 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 https://tv.nrk.no/program/msue11004013/geitekillingen-som-kunne-telle-til-ti 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.

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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”.

References

European Women’s Lobby, 2017, Last Checked: 8/10/2017, Retrieved From: http://www.womenlobby.org/HerNetHerRights

Nicole Shephard, 2016, Big data and sexual surveillance, Last Checked: 8/10/2017, Retrieved From: https://www.apc.org/sites/default/files/BigDataSexualSurveillance_0_0.pdf

Nicole Shephard, 2017, 5 reasons why surveillance is a feminist issue, Last Checked: 8/10/2017, Retrieved From: http://eprints.lse.ac.uk/78521/1/Engenderings%20%E2%80%93%205%20reasons%20why%20surveillance%20is%20a%20feminist%20issue.pdf

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

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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.

Denmark
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
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

Sweden
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.

Finland
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: http://dx.doi.org/10.1787/dcr-2017-en

References:

OECD (2017) Development Co-operation Report 2017: Data for Development, OECD Publishing, Paris. Retrieved 2nd October 2017 from http://dx.doi.org/10.1787/dcr-2017-en

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
https://www.ssb.no/omssb/samarbeid/internasjonalt-utviklingssamarbeid/_attachment/316124?_ts=15d36b4d518

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

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Humanitarian Data in a Development Context

Humanitarian Data in a Development Context
Image Source: Google

Big data is an opportunity for the entire global community to better understand what is happening around us in real time, all over the world. If in 2017 there are more than 7 billion mobile phones in the world, around 6 billion of them are used by people from developing countries. This leads to the production of large amounts of data as these people go about their daily lives.

Using Big Data Safely and Responsibly as a Public Good

Some of the UN Global Pulse initiatives that rely on user generated data online include the following example projects. These demonstrate how big data and mapping techniques are important for both humanitarian action and development:

  • Estimating Socioeconomic Indicators From Mobile Phone Data in Vanuatu. This ongoing project takes into consideration results from recent studies that show that data from mobile phones (Call Details Records and airtime credit purchases) can help in the process of understanding socioeconomic factors where official statistics are absent. The research project uses data from a local telecom operator in Vantau in order to compare if the officially provided statistical data in terms of education and household issues is accurate enough.
  • Exploring the Potential of Mobile Money Transactions to Inform Policy. The project analyses data provided by one of Uganda’s mobile operators to understand if the usage of mobile banking services depends on social networks, time and location. The result of this still ongoing project would help local authorities better understand the decision making process behind these services.
  • Informing governance with social media mining. This project analyzes the first live TV Presidential debates in Uganda in 2016, and it’s direct impact public opinions expressed on Facebook and social media in general. The analysis included 50,000 Facebook posts published publicly during the first two presidential debates on TV. The results of the project confirmed the positive impact of TV debates on democracy in Uganda.

Using Big Data for Mapping Our Future

Haiti in 2010 is considered as the initial moment in digital humanitarianism. And the most used platform for the biggest part of the digital response was Ushahidi. It was created in Kenya to help with tracking the violence after the elections. People used Ushahidi earlier in 2008 so that anyone could send in reports of violence via a web-form or SMS. Then they added the results to a Google map of Kenya (Read, Taithe, Mac Ginty, 2016, p. 9).

By learning from the past and by finding ways to protect the privacy of online users, organizations such as UN Global Pulse already have projects that use the electronically generated data from subscribers around the world. Of course, this data is useful for various purposes. But in most of the cases the gathered data is for creating maps. For example, all over the UN system there are maps. Maps of human rights violations, maps of poverty, maps of crop yields, etc.

In most of the cases, these maps are somehow static and don’t provide 100% reliable data in real time. As Patrick Meier argues, “the radical shift from static, “dead” maps to live, dynamic maps, requires that we reconceptualize the way we think about maps and use them”(Meier 2012, p. 89).

Dodge and Perkins (2009) suggest that “essential to new mapping techniques are imaging technologies, in particular satellite data”. And this results in “radically reshaping the ways different groups comprehend space and place” (Dodge and Perkins 2009, p.497). But they both remind us that “although access to much of this imagery is free, this disguises the powerful interests of corporations such as Google and Microsoft, who produce and own the images and control what we see and thus how we see the world through them” (Dodge and Perkins 2009, p.497).

The Duality of Big Data

In fact, a telecom company is able to track where its users move in real time. And by using this data, it’s possible to create maps of the movements of the population for example. This data can contain information about people going after a disaster, or people going to schools, clinics, etc. Current technology provides methods to create precise maps of people’s behavior in certain situations.

In other words it all depends on how we use and interpret big data. Big data seems to rely on human interpretation. Crawford et al (2013) note that we need to “more broadly consider the human impact – both short and long term – of how data is being gathered and used” (Crawford et al 2013, p. 4.). And “the technologies required to interrogate big data may mean that its use is restricted to a privileged few” (Read, Taithe, Mac Ginty, 2016, p. 11.). Boyd and Crawford argue that big data is ‘a cultural, technological and scholarly phenomenon’ combining technology (advanced computation power and algorithmic accuracy), analysis (identifying patterns to make claims) but also mythology; the belief that it offers new and higher knowledge ‘with the aura of truth, objectivity, and accuracy’ (Read, Taithe, Mac Ginty, 2016, p. 10.)

References

Boyd and Crawford, “Critical Questions,” 663., Last Checked: 1/10/2017, Retrieved from: https://people.cs.kuleuven.be/~bettina.berendt/teaching/ViennaDH15/boyd_crawford_2012.pdf

Crawford, K., Faleiros, G., Luers, A., Meier, P., Perlich, C., and Thorp, J. (2013) Big Data, Communities and Ethical Resilience: A Framework for Action. White Paper for PopTech and RockfellerFoundation. Last Checked 01/10/2017, Retrieved from: https://www.rockefellerfoundation.org/report/big-data-communities-and-ethical-resilience-a-framework-for-action/

Dodge M, Perkins C., The ‘view from nowhere’? Spatial politics and cultural significance of high-resolution satellite imagery. Geoforum. 2009 Jul;40(4):497-501.

Meier, P. 2012: Crisis Mapping in Action: How Open Source Software and Global Volunteer Networks Are Changing the World, One Map at a Time, Journal of Map & Geography Libraries

Read, R., Taithe, B., Mac Ginty, R. 2016: Data hubris? Humanitarian information systems and the mirage of technology, Third World Quarterly, forthcoming. Last Checked: 1/10/2017, Retrieved from: http://dx.doi.org/10.1080/01436597.2015.1136208

 

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