A National Lab Is Promoting a “Digital Police Officer” Fantasy for Law Enforcement and Border Control

by Dave Maass, Activist Post:

Researchers at a national laboratory are forecasting a future where police and border agents are assisted by artificial intelligence, not as a software tool but as an autonomous partner capable of taking the steering wheel during pursuits and scouring social media to target people for closer investigation. The “Digital Police Officer” or “D-PO” is presented as a visionary concept, but the proposal reads like a pitch for the most dystopian buddy cop movie ever.

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The research team is based out of Pacific Northwest National Laboratory (PNNL), a facility managed by the corporation Battelle on behalf of the U.S. Department of Energy. They have commissioned concept art and published articles in magazines aimed at law enforcement leaders, EFF has learned through a review of materials, including records obtained through a Freedom of Information Act request.

 

 “To leverage the full power of artificial intelligence, we need to know how people can best interact with it,” they write in a slide deck that starts with a robot hand and a human hand drawing each other in the style of the famous M.C. Escher artwork. “We need to design computing systems that are not simply tools we use, but teammates that we work alongside.”

 

For years, civil liberties groups have warned about the threats emerging from increased reliance by law enforcement on automated technologies, such as face recognition and “predictive policing” systems. In recent years, we’ve also called attention to the problems inherent in autonomous police robots, such as the pickle-shaped Knightscope security patrol robots and the quadrupedal “dog” robots that U.S. Department of Homeland Security wants to deploy along the U.S.-Mexico border

The PNNL team’s vision for “human-machine teaming” goes so much further.

“Al plays an active role in the mission by learning from the human and its environment,” the researchers write in a slide defining the term. “It uses this knowledge to help guide the team without requiring specific direction from the human.”

The Digital Police Officer

In articles published in Police Chief, the official magazine of the International Association of Chiefs of Police, and Domestic Preparedness Journal, the researchers introduce a fictional duo named Officer Miller and her electronic sidekick, D-PO (an apparent play on C-3PO), who’ve been patrolling the streets together for five years.

Here’s what they would look like, according to concept art commissioned by PNNL:

 

(Miller is technically a paramedic in this image, but this was used to illustrate the police officer narrative in both publications.)And here’s another piece of PNNL art from a presentation EFF received in response to a FOIA request:

 

 

 PNNL’s fictional narrative begins with D-PO keeping tabs on the various neighborhoods on their beat and feeding summaries of activities to Officer Miller, as they do everyday. Then they get an alert of a robbery in progress. The PNNL researchers imagine a kitchen sink technological response, tapping drones, face recognition, self-driving vehicle technology, and algorithmic prediction:

 

While Officer Miller drives to the site of the robbery, D-PO monitors camera footage from an autonomous police drone circling the scene of the crime. Next, D-PO uses its deep learning image recognition to detect an individual matching the suspect’s description. D-PO reports to Officer Miller that it has a high-confidence match and requests to take over driving so the officer can study the video footage. The officer accepts the request, and D-PO shares the video footage of the possible suspect on the patrol car’s display. D-PO has highlighted the features on the video and explains the features that led to its high-confidence rating.

“Do you want to attempt to apprehend this person?” D-PO asks.

Obviously Officer Miller does.

As they drive to the scene, the officer talks to D-PO the way she would with a human partner: “What are my best options for apprehending this guy?” Officer Miller asks.

D-PO processes the question along with the context of the situation. It knows that by “this guy” the officer is referring to the possible suspect. D-PO quickly tells Officer Miller about three options for apprehending the suspect including a risk assessment for each one…

D-PO’s brief auditory description is not enough for the officer to make a decision. Despite Officer Miller’s usual preference to drive, she needs her digital partner to take the wheel while she studies the various options.

“Take over,” she tells D-PO.

All this action sequence is missing is Officer Miller telling D-PO to blast Mötley Crüe’s “Kickstart my Heart.”

The authors leave the reader to conclude what happens next. If you buy into the fantasy, you might imagine this narrative ending in a perfect apprehension, where no one is hurt and everyone receives a medal–even the digital teammate. But for those who examine the intersection of policing and technology, there are a wide number of tragic endings, from mistaken identity that gets an innocent person pulled into the criminal justice system to a preventable police shooting–one that ends in zero accountability, because Officer Miller is able to blame an un-punishable algorithm for making a faulty recommendation.

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