jl999 gaming How the Federal Government Can Rein In A.I. in Law Enforcement

2024-10-10 03:24 Views:114

One of the most hopeful proposals involving police surveillance emerged recently from a surprising quarter — the federal Office of Management and Budget. The office, which oversees the execution of the president’s policies, has recommended sorely needed constraints on the use of artificial intelligence by federal agencies, including law enforcement.

The office’s work is commendable, but shortcomings in its proposed guidance to agencies could still leave people vulnerable to harm. Foremost among them is a provision that would allow senior officials to seek waivers by arguing that the constraints would hinder law enforcement. Those law enforcement agencies should instead be required to provide verifiable evidence that A.I. tools they or their vendors use will not cause harm, worsen discrimination or violate people’s rights.

As scholars of algorithmic tools, policing and constitutional law, we have witnessed the predictable and preventable harms from law enforcement’s use of emerging technologies. These include false arrests and police seizures, including a family held at gunpoint, after people were wrongly accused of crimes because of the irresponsible use of A.I.-driven technologies including facial recognition and automated license plate readers.

Consider the cases of Porcha Woodruff, Michael Oliver and Robert Julian-Borchak Williams. All were arrested between 2019 and 2023 after they were misidentified by facial recognition technology. These arrests had indelible consequences: Ms. Woodruff was eight months pregnant when she was falsely accused of carjacking and robbery; Mr. Williams was arrested in front of his wife and two young daughters as he pulled into his driveway from work. Mr. Oliver lost his job as a result.

All are Black. This should not be a surprise. A 2018 study co-written by one of us (Dr. Buolamwini) found that three commercial facial-analysis programs from major technology companies showed both skin-type and gender biases. The darker the skin, the more often the errors arose. Questions of fairness and bias persist about the use of these sorts of technologies.

Errors happen because law enforcement deploys emerging technologies without transparency or community agreement that they should be used at all, with little or no consideration of the consequences, insufficient training and inadequate guardrails. Often the data sets that drive the technologies are infected with errors and racial bias. Typically, the officers or agencies face no consequences for false arrests, increasing the likelihood they will continue.

We are having trouble retrieving the article content.

Please enable JavaScript in your browser settings.

Thank you for your patience while we verify access. If you are in Reader mode please exit and log into your Times account, or subscribe for all of The Times.