Last month, the White House Office of Management and Budget (OMB) issued a landmark policy putting in place long-overdue requirements on how federal agencies can – and cannot – use artificial intelligence.
Here are our main takeaways on what it means for law enforcement.
The Policing Project at NYU School of Law, the global law firm Jones Day, the law firm Lawrence & Bundy, and Canfield Law LLC have filed an appeal to the Eleventh Circuit Court of Appeals challenging the dismissal of a civil rights lawsuit against Clayton County police. A range of groups and individuals, including law enforcement officials; Tyler Perry, Jamie Foxx, and other prominent Black actors; empirical scholars; Cato Institute; NAACP Legal Defense Fund; Institute for Justice; ACLU of Georgia, have filed amicus briefs in support of the appeal.
This week, we’re highlighting testimony we provided to the New York City Council on how the NYPD has skirted democratic accountability in deploying intrusive policing technologies.
During this year’s legislative session, we provided input and drafting support on 36 pieces of legislation or regulations across 12 states. Notably, 22 of these engagements came at the express invitation of state or local partners, including both advocates and lawmakers. The most popular topics were use of force, officer decertification, and data collection and transparency, but legislators also sought to address a wide range of others, from warrant reform to police use of robots, and more.
Last year saw a renewed focus on policing reform and the widespread deployment of new technologies, such as aerial surveillance and facial recognition. Amidst these changes, the work of the Axon AI Ethics Board was as vital as ever. Today, the Board releases its end of year report detailing its work over calendar year 2020.
In a report produced with the Policing Project, Axon’s AI and Policing Technology Ethics Board concluded that face recognition technology is not yet reliable enough to justify its use on body-worn cameras, and expressed particular concern regarding evidence of unequal and unreliable performance across races, ethnicities, genders and other identity groups.
