Next Generation Identification

Since early 2011, in an effort to increase resources available to law enforcement (LE), the Federal Bureau of Investigation (FBI) has incrementally rolled out their Next Generation Identification (NGI) system which not only enhances the preexisting Integrated Automated Fingerprint Identification System but expands the biometric data-capture function exponentially. According to the FBI, NGI advancements will “increase the range and quality of its identification and investigative capabilities (Federal Bureau of Investigation, n.d.)” through components such as the Advanced Fingerprint Identification Technology, Repository for Individuals of Special Concern, Latent and Palm Prints, Rap Back, Facial Recognition, and Iris Scan (still currently being beta-tested). NGI additionally enables multi-national collaboration, an especially important feature in today’s war on terror.

FBI Criminal Justice Information Services Assistant Director Thomas E. Bush III purports NGI is not a data collection system but a “database that stores and aggregates information sent to it…from law enforcement agencies. (qtd. Smith, 2008)” yet Privacy advocates suggests otherwise, especially with regards to NGI’s facial recognition capabilities. While the accuracy of fingerprint analysis via NGI has improved from 92% to 99.6 % (Federal Bureau of Investigation, n.d.), the FBI only guarantees that facial recognition software will result in an 85% accuracy rate within a list of 50 candidates generated and only “when the true candidate exists” (qtd. Lynch, 2014). The minimum recommended resolution is .75 megapixels, a shockingly low threshold when compared against the newer iPhones which possess 8-megapixel resolution (Lynch, 2014). (Even Google Glass, which banned the use of facial recognition applications, possess a 5-megapixel camera! (Warman, 2013))

Unfortunately, much of America’s video surveillance infrastructure utilizes technology that does “meet the necessary resolution standards to make accurate facial recognition” (Walker, 2014). Furthermore, a German field study in facial recognition software in 2006 demonstrated only a 60% daytime accuracy rate and a dismal 10% nighttime rate (Smith, 2008). The FBI insists that NGI enables a zero percent false positive feedback because the system does not generate positive identifications but investigative leads. Yet, a database which contains both criminal and non-criminal (i.e. background check for employment) data, capable up processing up to 52 million photo queries a day, has an error rate of almost 8 million people.

Even more unnerving than the lack of accuracy remains a systemic failure to establish working guidelines. Documents released to Electronic Frontier Foundation as a result of a freedom of information lawsuit illuminate that “the FBI and Congress have thus far failed to enact meaningful restrictions on what types of data can be submitted to the system, who can access the data, and how the data can be used” (Lynch, 2014). Many deemed this as unacceptable particularly given that the annual financial obligation necessary to support NGI is suspected of being approximately one billion dollars (Smith, 2008). Nonetheless, the FBI can mitigate concerns over privacy encroachment through transparency in both policy and practice.

The following proposals can alleviate, if not then placate, concerns over privacy intrusions as well as instill the public with a sincere attempt by LE to minimize mistaken identities:

·         instituting a comprehensive policy, based upon significant field testing of enhanced capabilities, that includes standards required to accept data (i.e. higher camera resolution, minimum Galton Points, etc.), the full scope of data complied, methods of data acquisition, accessibility requirements that include limits that cannot be exceeded without a warrant, flow of information, data usage applications, and a recourse for data removal (conditional);

·         the establishment of multiple databases that separate the non-criminal, criminal, and terror suspect information;

·         Non-introduction of criminal data without criminal conviction (except terror investigations);

·         Alignment with both the Privacy Act and Freedom of Information Act;

·         Congressional oversight that involves semi-annual briefings; and

·         System accessibility preclude any attempts for information from any non-verifiable and/or non-active LE entities.

Reference List

Federal Bureau of Investigation. (n.d.). Next Generation Identification (NGI). Retrieved from fbi.gov: https://www.fbi.gov/services/cjis/fingerprints-and-other-biometrics/ngi

Lynch, J. (2014). FBI Plans to Have 52 Million Photos in its NGI Face Recognition Database by Next Year. Retrieved from Electronic Frontier Foundation: https://www.eff.org/deeplinks/2014/04/fbi-plans-have-52-million-photos-its-ngi-face-recognition-database-next-year

Smith, J. L. (2008). The FBI's Next Generation Identification Database. Retrieved from Hendon Publishing.

Walker, L. (2014). FBI Announces Its Facial Recognition System is Ready to Go. Retrieved from Newsweek: http://www.newsweek.com/fbi-announces-its-facial-recognition-system-ready-go-270955

Warman, M. (2013). The Creepiest Google Glass Feature Has Been Banned: No Facial Recognition Apps Allowed. Retrieved from Business Insider: http://www.businessinsider.com/google-glass-facial-rec-apps-banned-2013-6