Cops Running DNA-Manufactured Faces Through Face Recognition Is a Tornado of Bad Ideas
In 2020, a detective from the East Bay Regional Park District Police Department in California asked to have a rendered image from Parabon NanoLabs run through face recognition software. This 3D rendering, called a Snapshot Phenotype Report, predicted that—among other attributes—the suspect was male, had brown eyes, and fair skin. Found in police records published by Distributed Denial of Secrets, this appears to be the first reporting of a detective running an algorithmically-generated rendering based on crime-scene DNA through face recognition software. This puts a second layer of speculation between the actual face of the suspect and the product the police are using to guide investigations and make arrests. Not only is the artificial face a guess, now face recognition (a technology known to misidentify people) will create a “most likely match” for that face.
These technologies, and their reckless use by police forces, are an inherent threat to our individual privacy, free expression, information security, and social justice. Face recognition tech alone has an egregious history of misidentifying people of color, especially Black women, as well as failing to correctly identify trans and nonbinary people. The algorithms are not always reliable, and even if the technology somehow had 100% accuracy, it would still be an unacceptable tool of invasive surveillance capable of identifying and tracking people on a massive scale. Combining this with fabricated 3D renderings from crime-scene DNA exponentially increases the likelihood of false arrests, and exacerbates existing harms on communities that are already disproportionately over-surveilled by face recognition technology and discriminatory policing.
There are no federal rules that prohibit police forces from undertaking these actions. And despite the detective’s request violating Parabon NanoLabs’ terms of service, there is seemingly no way to ensure compliance. Pulling together criteria like skin tone, hair color, and gender does not give an accurate face of a suspect, and deploying these untested algorithms without any oversight places people at risk of being a suspect for a crime they didn’t commit. In one case from Canada, Edmonton Police Service issued an apology over its failure to balance the harms to the Black community with the potential investigative value after using Parabon’s DNA phenotyping services to identify a suspect.
EFF continues to call for a complete ban on government use of face recognition—because otherwise these are the results. How much more evidence do law markers need that police cannot be trusted with this dangerous technology? How many more people need to be falsely arrested and how many more reckless schemes like this one need to be perpetrated before legislators realize this is not a sustainable method of law enforcement? Cities across the United States have already taken the step to ban government use of this technology, and Montana has specifically recognized a privacy interest in phenotype data. Other cities and states need to catch up or Congress needs to act before more people are hurt and our rights are trampled.
Paige Collings is the Senior Speech and Privacy Activist at EFF. Matthew Guariglia is a policy analyst working on issues of surveillance and policing at the local, state, and federal level. This article is published courtesy of the Electronic Frontier Foundation (EFF).
