Rebalancing Socioeconomic Asymmetry in a Data-Driven Economy

(Image: Defense Advanced Research Projects Agency (DARPA)/CC License)

As the global economy becomes increasingly grounded in the exchange of data, the ways in which those data are collected and analyzed will become even more opaque to individuals, and the value exchange that is taking place even harder to discern. Although an individual may receive something in return for their information, the real values of both the data provided and the service returned (i.e., the underlying exchange of value) is almost impossible to determine—one reason why few individuals seem to put much trust in the data-driven economy.

In a paper published today in the World Economic Forum’s Global Information Technology Report 2014, Strategic Foresight Initiative Nonresident Senior Fellow Peter Haynes and Microsoft Director of Technology Policy M-H. Carolyn Nguyen argue that growing socioeconomic asymmetries must be rebalanced for a data-driven economy to thrive.

Worse, for many people any potential value of their data is already largely irrelevant, because they have given away their digital crown jewels for free. Individuals are passing vast amounts of personal and other data to large corporations (such as Facebook) with little or no thought to its potential monetary value. And those corporations are making significant profits as a result, because their “cost of materials” is essentially zero. Thus the greater the role that data play in the global economy, the less the majority of individuals will be worth and the smaller their role in that new economy.

If a truly sustainable data-driven economy is to be established, the way in which data are traded between individuals and corporations requires a major reset. For such an economy to succeed, individuals would have to receive fair monetary compensation for each specific datum they provide, perhaps with additional payments whenever that datum produced incremental profits for the entity to which it has been passed. Such systems would be complex, but are essential to (re)establish the concept of fair value exchange in a world dominated by data, big or little.

We believe that a key element to enable fair value exchange and individual trust in such a system is an interoperable metadata-based software architecture. In such an architecture, data are logically accompanied by a “metadata tag” that contains references to the permissions and policies associated with the data, along with related provenance information. It can also be used to track and capture the monetary value produced by the data, providing a foundation for both fair value exchange and greater trust. The metadata is logically bound to the data and cannot legally be unbound or modified for the entire data lifecycle by any parties other than the user.

A metadata-based architecture offers value to all stakeholders in a data-driven economy, not only to individuals. For example, data-consuming entities can more easily understand and comply with the permissions and policies defined for specific data. They can also establish a dynamic, economically viable and sustainable “marketplace” in data that would ideally mirror the way in which fair value exchange is established in the physical world. And regulators can take advantage of greatly improved auditability of data, along with a stronger and better-defined connection between the data and those policies that govern its use.

There are numerous challenges here—among them social, technological, and regulatory—and today we have many more questions than answers. But the data-driven economy will be unable to realize its potential unless those answers are found.

Peter Haynes is a nonresident senior fellow with the Strategic Foresight Initiative.