In the seventeenth century, political philosopher James Harrington noted that the determining element of power in preindustrial England was the ownership of land. James Madison, arguably the father of the U.S. Constitution and an admirer of Harrington, later summed up his views in an aphorism—“power follows property.”
‘Data’ has emerged as the twenty-first century ‘land’, the new form of power. Big data, and in particular, personal big data—the zeros and ones, that, when combined, can reveal unique information about individuals—has already begun to demonstrate its transformative potential. As data begins to reveal more about individuals, its value and impact on those individuals will increase. Conceptions of property must expand from the physical to the virtual to meet twenty-first century realities. Data should be viewed as a form of property.
The Ramifications of Personal Big Data
Global digital data is doubling yearly, and individual consumers create the majority of that data, producing, in essence, digital footprints. These individual consumer digital footprints—downloads, e-mails, ‘likes’, cell-phone location readings, clicks, and purchases—are just the beginning. People are becoming increasingly socialized into sharing more personal information. The Quantified Self movement aims to measure all aspects of our lives with technology, and the new wave of wristbands, like Sony’s SmartBand, are increasingly helping to facilitate that. On their own, personalized bits of data are not particularly useful, and only appear to provide relatively esoteric indicators of a particular individual. Big data, however, by fusing flows of information with insights derived from behavioral science, now allows advertisers, search engines, and social media platforms to try and predict and model human behavior .
While our personalized big data can help facilitate healthier living, smarter cities , and increasing web simplification through personalization, there is also a darker underbelly to the accumulation of this information. In a recently released report by the World Privacy Forum , Pam Dixon and Robert Gellman note that data brokers, analytical firms, and retailers, are using personal data to create hundreds of inaccessible consumer scores, ranking individuals on the basis of their perceived health risk, likelihood they will keep their job, and their supposed propensity to commit fraud. Perhaps more importantly, last week the Obama administration released the findings of their ‘ Big data and Privacy working group ,’ noting that big data analytics can “lead to discriminatory outcomes and circumvent longstanding civil rights protections in housing, employment, credit, and the consumer marketplace.” These secret consumer scores and profiles can cast an indelible stain on individuals, and have the potential to become sources of classification, profiling, and discrimination.
For example, in 2011, Google explained how consumers with ‘high-value profiles’ received higher bids for corporate access to advertise to their profiles. Meanwhile, consumers with ‘low-value profiles,’ often received no bids at all. Jeff Rosen of George Washington Law warns that this will essentially eliminate a free and open marketplace; as consumers will no longer ‘haggle’ with sellers on equal terms, while being unaware of what discounts and prices other preselected individuals are being offered. Even more problematic is the fact that these consumer scores could affect an individual’s eligibility for a new job, a loan, credit, or affordable insurance. In short, one could see the emergence of a class of ‘digitally disenfranchised’ individuals, whose prospects and ambitions are limited or denied due to the existence of ‘digital scarlet letters’.
Perhaps more troubling than the profiling itself, is that these profiles are often wrong. Last month, the Economist ran a blog on the increasing backlash against big data, noting three mainstream criticisms of big data. While big data criticism is not an attack on the data itself, it is a critique on the numerous perceived deficiencies of data analytics. Data analysis can come to erroneous conclusions and correlations. In a recent conversation with an insider from a data aggregation and profiling site, the person revealed that the company’s labeling is correct only 40 percent of time. While an accuracy rate of only 40 percent may not seem like a big deal when Amazon is using individual data to tailor-make book recommendations; a 60 percent error rate looks a whole lot more disturbing when that same data is then used to determine job eligibility and proclivity to commit crime. A false profile may indeed become an ‘invisible brand,’ which cannot be erased. And unlike those tattoos that people immediately come to regret after a revelry-filled evening, in this case, a person may not even know he or she has been branded.
Big Data as Twenty-first Century Property?
Preventing inaccessible data profiling requires enlarging our definition of property from the physical to the virtual.
As Harrington noted in The Commonwealth of Oceana, domestic empire is always founded on dominion, and dominion is property, composed of land, money, and goods. In Oliver Cromwell’s England, and under those who ruled before him, power was a facet of land. ‘Data’ is increasingly becoming the equivalent of ‘land’ in seventeenth century England. For those few corporations and governments that aggregate data, they accrue enormous amounts of power. Data, similarly to land, should be considered a property that individuals have the right to save, sell, or trade.