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Big Data from an Institutional Perspective: Opportunities for Researchers

Throughout the last years, the rate of technological progress has accelerated. To a large extent this development was driven by the increasing availability of data, owing to the fact that more and more economic and social transactions take place aided by information and communication technologies (ICT), which easily and inexpensively store the information such transactions produce or transmit. Complementing the increased availability of data, progress has also depended on the increasing ability of firms (and governments) to analyze the novel big data sets (Viktor Mayer-Schönberger and Kenneth Cukier, 2013).

In “The Second Machine Age” (2014:8), MIT-Professors Erik Brynjolfsson and Andrew McAfee motivate their study of the contemporary effects of big data and datafication on our economic, social, legal, political, and cultural spheres as follows:

For years we have studied the impact of digital technologies like computers, software, and communications networks, and we thought we had a decent understanding of their capabilities and limitations. But over the past few years, they started surprising us. Computers started diagnosing diseases, listening and speaking to us, and writing high-quality prose, while robots started scurrying around warehouses and driving cars with minimal or no guidance. Digital technologies had been laughably bad at a lot of things for a long time—then they suddenly got very good. How did this happen? And what were the implications of this progress, which was astonishing and yet came to be considered a matter of course?

This is notably an optimistic account of the latest technological developments. But when Brynjolfsson and McAfee comment on its downsides, they mainly mention “spread,” which they describe as “ever-bigger differences among people in economic success – in wealth, income, mobility, and other important measures” (p.12). In this respect, they join a big group of technologists who understand the opportunities of data-driven technologies well but treat the threats for individuals and society rather superficially.

Then, there is the camp of datafication alerters. Comparing the very asymmetric armament of sellers and individual consumers in data-driven markets, Alessandro Acquisti and Jens Grossklags (2007:369) note that “[c]onsumers will often be overwhelmed with the task of identifying possible outcomes related to privacy threats and means of protection. [. . . ] However, even if individuals had access to complete information, they would often be unable to process and act optimally on large amounts of data.”

Extending the big data technology critique to the political sphere, Evgeny Morozov (2011:xiv) sarcastically writes:

Failing to anticipate how authoritarian governments would respond to the Internet, cyber-utopians did not predict how useful it would prove for propaganda purposes, how masterfully dictators would learn to use it for surveillance, and how sophisticated modern systems of Internet censorship would become. […] Paradoxically, in their refusal to see the downside of the new digital environment, cyber-utopians ended up belittling the role of the Internet, refusing to see that it penetrates and reshapes all walks of political life, not just the ones conducive to democratization.

Summarizing, there seem to be two opposite approaches to the current technological developments related to data science. The first mainly consists of engineers, statisticians, marketers, and technology-savvy entrepreneurs and politicians. This camp underlines the positive effects of technological progress in general, and the increased opportunities for citizens’ participation and consumers’ customization of products that is becoming possible through the embrace of big data technologies in particular. On the other side, political and consumer activists join forces with a few legal scholars in pointing at the negative economic, political, and social effects of the increasing datafication and ubiquitous connectivity of today’s and tomorrow’s world.

What is missing from the picture is a careful analysis of all involved forces grounded in the understanding that issues are complex and subtle because, while unconstrained big data generates both great opportunities and great threats, a misguided policy response can affect market structures, prices as well as incentives to invest and innovate. Such an analysis of the involved trade-offs is the domain of economics—but economics needs to be accompanied not only by knowledge of the involved technological developments but also by awareness of the institutional forces at play: law, political science, sociology, and anthropology all appear to be relevant when we try to understand the opportunities and threats involved in data-driven technologies and offer an advanced examination of how they operate.

This necessary interdisciplinary approach, rooted in economics, is the domain of SIOE-spirited researchers. There is work to do for us. And opportunities abound.

* With thanks to Agnieszka Janczuk-Gorywoda and Pierre Larouche.


Acquisti, Alessandro, and Jens Grossklags. 2007. “What Can Behavioral Economics Teach Us About Privacy?” In Digital Privacy: Theory, Technologies and Practices, edited by Alessandro Acquisti, Stefanos Gritzalis, Costas Lambrinoudakis, and Sabrina De Capitani di Vimercati, 363–77. New York & London: Auerbach Publications.

Brynjolfsson, Erik, and Andrew McAfee. 2014. The Second Machine Age. New York: Norton.

Mayer-Schönberger, Viktor, and Kenneth Cukier. 2013. Big Data: A Revolution That Will Transform How We Live, Work and Think. John Murray.

Morozov, Evgeni. 2011. The Net Delusion. How Not To Liberate The World. London: Allen Lane.