VOLUME 163, ISSUE 2 JANUARY 2015

The Fourth Amendment requires “reasonable suspicion” to stop a suspect. As a general matter, police officers develop this suspicion based on information they know or activities they observe. Suspicion is individualized to a particular person at a particular place. Most reasonable suspicion cases involve police confront-ing unknown suspects engaged in observable suspicious activities. Essentially, the reasonable suspicion doctrine is based on “small data”—discrete facts, limited information, and little knowledge about the suspect.

But what happens if this small data suspicion is replaced by “big data” suspicion? What if police can “know” personal information about the suspect by searching vast networked information sources? The rise of big data technologies offers a challenge to the traditional paradigm of Fourth Amendment law. With little effort, officers can now identify most unknown suspects, not through their observations, but by accessing a web of information containing extensive personal data about suspects. New data sources, including law enforcement databases, third-party records, and predictive analytics, combined with biometric or facial recognition software, allow officers access to information with just a few search queries. At some point, inferences from this personal data (independent of the observation) may become sufficiently individualized and predictive to justify the seizure of a suspect. The question this Article poses is whether a Fourth Amendment stop can be predicated on the aggregation of specific and individualized, but otherwise noncriminal, factors.

For example, suppose police are investigating a series of robberies in a particular neighborhood. Arrest photos from a computerized database are uploaded in patrol cars. Facial recognition software scans people on the street. Suddenly there is a match—police recognize a known robber in the targeted neighborhood. The suspect’s personal information scrolls across the patrol car’s computer screen—prior robbery arrests, prior robbery convictions, and a list of criminal associates also involved in robberies. The officer then searches additional sources of third-party data, including the suspect’s GPS location information for the last six hours or license plate records which tie the suspect to pawn shop trades close in time to prior robberies. The police now have particularized, individualized suspicion about a man who is not doing anything overtly criminal. Or perhaps predictive software has already identified the man as a potential reoffender for this particular type of crime. Or perhaps software has flagged the suspect’s social media comments or other Internet postings that suggest planned criminal or gang activity. Can this aggregation of individualized information be sufficient to justify interfering with a person’s constitutional liberty?

This Article traces the consequences of a shift from “small data” reasonable suspicion, focused on specific, observable actions of unknown suspects, to a “big data” reality of an interconnected, information rich world of known suspects. With more specific information, police officers on the streets may have a stronger predictive sense about the likelihood that they are observing criminal activity. This evolution, however, only hints at the promise of big data policing. The next phase will use existing predictive analytics to target suspects without any firsthand observation of criminal activity, relying instead on the accumulation of various data points. Unknown suspects will become known to police because of the data left behind. Software will use pattern-matching techniques to identify individuals by sorting through information about millions of people contained in networked data-bases. This new reality simultaneously undermines the protection that reasonable suspicion provides against police stops and potentially transforms reasonable suspicion into a means of justifying those same stops.

This Article seeks to offer three contributions to the development of Fourth Amendment theory. First, it demonstrates that reasonable suspicion—as a small data doctrine—may become practically irrelevant in an era of big data policing. Second, it examines the distortions of big data on police observation, investigation, and prediction, concluding that big data information will impact all major aspects of traditional policing. Third, it seeks to offer a solution to potential problems using the insights and value of big data itself to strengthen the existing reasonable suspicion standard.

Policymakers and legal scholars routinely make “comparative institutional competence” claims—claims that one branch of government is better at performing a specified function than another, and that the more competent branch should be in charge of that function. Such claims pervade American law and policy, but they are rarely evaluated with rigor.

We take advantage of an unusual legislative experiment to conduct what we believe to be the first systematic empirical analysis of the comparative institutional competence of the executive and judicial branches in a critical field of American law and policy: U.S. foreign relations. From 1952 to 1976, the U.S. State Department decided whether foreign nations would receive sovereign immunity from suits in U.S. courts. Based on the perception that the State Department’s sovereign immunity decisions were overly influenced by political considerations, Congress passed the Foreign Sovereign Immunities Act of 1976 (FSIA), which transferred immunity decisionmaking authority to the judiciary. This transfer was based on an explicit comparative institutional competence claim: that courts are better equipped than the State Department to make immunity decisions based on law rather than politics.

To rigorously evaluate this fundamental claim, we created and analyzed an extensive dataset of foreign sovereign immunity decisions made by the State Department and the U.S. district courts over the last fifty years. Our principal findings are threefold. First, we find little evidence that political factors systematically influenced the State Department’s immunity decisions. Second, there is strong evidence that political factors have systematically influenced the courts’ decisions. Third, the transfer of immunity decisionmaking authority to the courts did not significantly affect the likelihood of immunity.

All three findings challenge both the underlying comparative institutional competence claims that supported the FSIA’s pas-sage and more general conventional understandings about the proper allocation of authority between the executive and judicial branches. To be sure, there may be valid reasons for the judiciary to play a leading role in immunity decisionmaking, and possibly other areas of U.S. foreign relations as well. But our analysis casts doubt on the widely made comparative institutional competence claim that the judicial branch is necessarily better equipped than the executive branch to make foreign relations law decisions free from systematic political influence.

A new and startling development has recently occurred in the law of delegation: Congress has for the first time expressly delegated to an administrative agency the power to write rules of privilege. Privileges abound in federal law, but until now, they have been defined either by statute or judicial opinion. The type of law that Congress has now authorized agencies to create—the regulatory evidentiary privilege—is a true novelty in our legal system.

This Article is the first to grapple with the implications of migrating the power to write rules of privilege from Congress and the courts, on the one hand, to the executive branch, on the other. It begins by describing an underappreciated aspect of the administrative state: the law of privilege is becoming increasingly important to the functioning of administrative agencies. As a result, administrative agencies are actively pursuing control over the law of evidentiary privilege to further their substantive mandates.

Granting agencies that sought-after control through a privilege delegation will imperil key federal and state regulatory and governance interests. First, privilege delegations will reduce agency accountability. A delegated authority to write privileges that enables an agency to shield its own communications from disclosure will allow the agency to insulate itself from external review and oversight. Second, privilege delegations will erode state interests in allowing litigants and the public broad access to information. Agencies promulgating regulatory evidentiary privileges are likely to displace state laws that would permit disclosure to a greater extent than would be the case if Congress and the courts retained the privilege pen. Third, privilege delegations threaten to undercut state sovereignty. When Congress authorizes federal agencies to privilege the communications of state officials, it obstructs the capacity of the states to monitor state agents and thereby produces a type of harm akin to prohibited congressional commandeering of state governance.

After establishing the risks attendant to privilege delegations, this Article offers some design principles that should govern the institution chosen to draft any new set of privileges that may be invoked by executive branch agencies and explains that the existing judicial rulemaking system fits well with these principles. Finally, this Article explains why this innovation in delegation provides a unique opportunity to test prevailing scholarly models of why and to whom Congress chooses to delegate. When it delegates the power to privilege to an agency, Congress is substituting a new delegate—a politically accountable executive agency—for an old delegate—the politically unaccountable federal courts. Accounts of delegation grounded in party competition have greater explanatory power for this swapping of delegates than alternative accounts.