People of color and immigrants will shoulder much more of the burden of these misidentifications. For example, people of color are disproportionately represented in criminal and immigration databases, due to the unfair legacy of discrimination in our criminal justice and immigration systems.452 The fallibility of biometric identification. According to the National Academy of Sciences, no peer-reviewed study has ever been conducted to prove the basic assumption that each person’s fingerprints are unique.453 The largest biometric database in the world is the Aadhaar project in India, a foundational population register in which approximately 1.2 billion people have enrolled as of 2019.454 A 2012 study found that out of 1.2 billion enrollments in the system, the automated process that identifies duplicate fingerprints would register approximately 10 million false positives, resulting in exclusion from the system.455 Although computer algorithms—developed and sold to governments by private technology companies—are used worldwide to identify potential fingerprint matches from a database like IDENT, ultimately human examiners compare a list of potential matches generated by the automated search.456 This is significant because studies have also demonstrated that fingerprint examiners are influenced by contextual bias when comparing fingerprints.457 One study “found that fingerprint examiners can be improperly influenced by the use of automated fingerprint identification systems, which provide ordered lists of the most likely matches. The study found that examiners are more likely to wrongly identify one of the prints near the top of the list as a match, and to fail to make correct identifications if the print is down low on the list.”458 According to one analysis: When examining this issue again in 2016, the President’s Council of Advisors on Science and Technology (PCAST) in the US found that only two properly designed studies of latent fingerprint analysis had been conducted. These both found the rate of false matches (known as “false positives”) to be very high: 1 in 18 and 1 in 30. One of the main reasons for these high error rates is that fingerprint analysis involves human judgement, and relies on a methodology (known as “ACE-V”) that is not sufficient to ensure the accuracy and reliability of an examiner’s conclusions. This means there is no guarantee that two different examiners who follow its steps will reach the same result.459 Questions regarding the reliability of databases and fingerprints are based on concerns about the use of old, outdated, and possibly inaccurate technologies. But a wave of new technologies examined below, including DNA capture, raises even greater concern about misapplication and permanent surveillance. II. Denaturalization: A Radical Measure in the Hands of Zealots 103