Understanding Big Data: Data Calculus in the Digital Era

Abstract

Information processing has been defined as “the change (processing) of information in any manner detect- able by an observer, a process that describes everything that happens in the universe, from the falling of a rock to the printing of a text file from a digital computer system.” Human society has long realized that information processing and sharing are essential to the pursuit of physical, social, and economic well-being. Knowing and sharing information about one’s surroundings is essential to success in the physical world. Knowing and sharing information about one’s “neighbors” is essential to success in the social world. “Knowing-your-customers” (KYC) in order to serve them well is the supreme norm for success in the business world. Sharing that information – the Yellow Pages practice that makes certain personal information, such as name, telephone number, and address public – has become a tradition in modern human relations.

The pervasive use of digitized information has reached a new height that we call the era of "big data." While this has led to unprecedented societal cooperation, it has also intensified three major concerns: How can we properly protect personal privacy in the age of big data? How do we understand and manage the ownership and distribution of benefits and risks arising from the use of data? Will the use of big data lead to "winner-take-all" markets that undermine competition to the detriment of consumers and society? These are the subjects of this report.

We focus on analyzing concrete evidence about "big data" to draw conclusions on its impact. As Nobel Laureate Ronald Coase (1994) suggested, it is important to step away from pure "blackboard economics" that tends to only live in [a theoretician's] mind: "what we need is more empirical work ... An inspired theoretician might do as well without such empirical work, but ... the inspiration is most likely to come through the stimulus provided by the patterns, puzzles, and anomalies revealed by the systematic gathering of data, particularly when the prime need is to break our existing habits of thought."

This viewpoint is particularly relevant because, unlike many production inputs, data has the properties of non-rivalry and non-separability. Unless an evidence-based, integrated and multi-stakeholder approach is adopted, users can be unintentionally hurt in the name of protection. We don’t want to "dismember the goose that laid the golden egg."