More Surveillance Won’t Solve Right-Wing Extremism


The storming of the Capitol has prompted security experts to offer some predictable advice: Double down on surveillance, by sharing more information among federal and local law enforcement agencies about potentially dangerous people. I’d be all for this if I thought it had much chance of making inroads against right-wing extremists. As things stand, it’s more likely to compound the suffering already inflicted upon immigrants and minorities.

I’ll admit that my grasp of how law enforcement collects and shares data is far from comprehensive. That said, based on what I’ve seen in my work as an expert on big data and algorithms, I can say that they certainly haven’t been focused on the strange concoction of conspiracy theorists, White supremacists and gun enthusiasts who descended upon the U.S. seat of government. Their sights have been trained on foreigners and poor people of color, who as a result will invariably feature in whatever information they have.

Consider the Department of Homeland Security’s information-sharing with state departments of motor vehicles. It’s been consciously constructed with an eye towards pursuing undocumented immigrants — a function of the nation’s decades-long fantasy that terrorism must be imported, not home-grown. The 2005 Real ID Act, for example, has helped DHS pick out people who lack the social security number required to obtain a new, enhanced-security “Real ID” driver’s license. As a result, in states that allow the undocumented to be licensed, a regular license effectively acts as a marker, exposing immigrant families to added scrutiny and threat of deportation.

Or consider who’s likely to be in the database of the New York City Police Department. According to the New York Civil Liberties Union, the racial bias of Stop & Frisk policing meant that in at least one year (2011), the number of young Black men stopped exceeded the city’s entire population of young Black men. Anyone processed by the NYPD gets their picture and information recorded, so its database will be skewed toward identifying Black people — an artifact of a deeply racist history. New York, of course, is not alone in its approach to policing, so efforts to make data universally accessible among police departments will serve to perpetuate the problem.

I saw the issue first hand back in 2015, when I worked on a data task force at the police department of Camden County in New Jersey. A startup called Mark43 was trying to connect various siloed data sets so police officers could obtain, and share with other departments, all the relevant information on a given address — such as the identities, mental health statuses and possibly the phone records of anyone who had lived or been arrested there.

While I recognized the attraction, I also worried that the system could be headed for a hugely disparate impact. I’m all for nabbing bad guys, but it’s not justice if you’re nabbing them only in the poor, minority part of town. And it’s far too easy to imagine old or bad data leading to unnecessarily violent arrests. It doesn’t make sense for just anyone to have complete access to those data. It should be granted only under narrow and carefully considered conditions.

I agree that the potential for domestic terrorism is a major problem, and I wish the answer were as simple as better data sharing. But it’s not. Anyone who paid attention to Parler could have known that something bad was coming to Washington D.C. If authorities had taken the extremist chatter seriously, they would have been better prepared. I’d argue this was more of a failure to act on an obvious threat than a lack of information. The data were right there in President Donald Trump’s Twitter feed.

If the intelligence community wants to counter the danger of White rage and grievance turning violent, it will require a different approach, with more realistic assumptions about what troubles the nation.

This column does not necessarily reflect the opinion of the editorial board or Bloomberg LP and its owners.

Cathy O’Neil is a Bloomberg Opinion columnist. She is a mathematician who has worked as a professor, hedge-fund analyst and data scientist. She founded ORCAA, an algorithmic auditing company, and is the author of “Weapons of Math Destruction.”

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