In the short 'Big Data and Its Exclusions' Jonas Lerman argues that
Legal debates over the "big data" revolution currently focus on the risks of inclusion: the privacy and civil liberties consequences of being swept up in big data's net. This essay takes a different approach, focusing on the risks of exclusion: the threats big data poses to those whom it overlooks. Millions of people worldwide remain on big data's periphery. Their information is not regularly collected or analyzed, because they do not routinely engage in the sorts of behaviors big data is designed to capture. Consequently, their preferences and needs risk being routinely ignored when governments and private industry use big data and advanced analytics to shape public policy and the marketplace. Because big data poses a unique threat to equality, not just privacy, this essay argues that a new "data antisubordination" doctrine may be needed.Lerman comments that -
Because existing equality law will not adequately curb big data’s potential for social stratification or bias, it may become necessary to develop a new equality doctrine—a principle of data antisubordination. Traditionally, U.S. antisubordination theorists have argued “that guarantees of equal citizenship cannot be realized under conditions of pervasive social stratification,” and “that law should reform institutions and practices that enforce the secondary social status of historically oppressed groups.” This antisubordination approach — what Owen Fiss called the “group disadvantaging principle” — may need to be revised, given big data’s potential to impose new forms of stratification and to reinforce the status of already-disadvantaged groups.
A data antisubordination rule would, at minimum, provide those persons who live outside or on the margins of dataflows some guarantee that their status as persons with light data footprints will not subject them to unequal treatment by the state in the allocation of public goods or services.
To be most effective, however, the principle would need to extend beyond state action. Big data’s largest private players exert an influence on societies, and a power over communications and the flow of information, that in previous generations only governments enjoyed. Thus, a data antisubordination principle would be incomplete unless it extended, in some degree, to the private sector. Once fully developed as theory, a data antisubordination principle could be enshrined in law by statute. Like GINA, it would be a civil rights law designed for potential embedded in powerful new technologies—threats that neither the Framers nor past civil rights activists could have envisioned.
In “The Right to Privacy,” their 1890 Harvard Law Review article, a young Louis Brandeis and co-author Samuel Warren observed that “[r]ecent inventions and business methods call attention to the next step which must be taken for the protection of the person.” The big data revolution, too, demands “next steps,” and not just in information privacy law. Brandeis and Warren’s “right to be let alone” — which Brandeis would later call the “most comprehensive of rights and the right most valued by civilized men” — has become an obsolete and insufficient protector. Even more modern information privacy principles, such as consent and the nascent “right to be forgotten,” may turn out to have only limited utility in an age of big data.
Surely revised privacy rules, norms, and standards will be needed in this new era. But they are insufficient. Ensuring that the big data revolution is a just revolution, a revolution whose benefits are broadly and equitably shared, may also require, paradoxically, a right not to be forgotten or let alone — a right against exclusion.