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/

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