Three Laws Blog: Law and Artificial Intelligence

Lecorps and Tissandier on PAVED With Good Intentions? An Evaluation of a French Police Predictive Policing System @YLcrps @GaspardTissand1

Yann Lecorps, LeMans University, and Gaspard Tissandier, Université Paris 1 Panthéon-Sorbonne, have published PAVED With Good Intentions? An Evaluation of a French Police Predictive Policing System. Here is the abstract.

From late 2017 to early 2019, one of the two french law enforcement agencies, the Gendarmerie, tested in 11 out of 101 departments its own predictive policing system named PAVED. In order to better allocate the patrolling units, the system predicts burglaries and vehicle thefts that we observe from 2015 with monthly data in each French department. We use this quasi-experimental design to evaluate whether the system produces the expected reduction in these thefts and whether this effect is due to a deterrent effect or a displacement effect. Both the standard Two Way Fixed Effect and Synthetic Difference-in-Difference estimations consistently indicate a significant reduction of vehicle thefts in the treated Gendarmerie areas but no detectable effect on burglaries. Our results indicate that vehicle theft has not increased in areas near the treated areas, suggesting that the reduction in vehicle theft is due to a deterrent effect rather than a displacement effect.

Download the article from SSRN at the link.

Joh on Reckless Automation in Policing @elizabeth_joh @UCDavisLaw @BerkeleyTechLJ

Elizabeth E. Joh, University of California, Davis, School of Law, is publishing Reckless Automation in Policing at Berkeley Technology Law Journal Online (2022). Here is the abstract.

Automated decision-making plays an increasingly larger role in policing. Traditional methods of police investigation have been augmented by tools like facial recognition, predictive analytics, license plate readers, and robotics. How should we evaluate the growth of automation in policing? There is no shortage of answers, but this essay starts with a simple observation: by focusing on automation’s harms to persons first. American policing is rife with reckless automation. If we accept the premise of reckless automation, the conversation about accountability, artificial intelligence, and policing might benefit from a seemingly unrelated policy framework: that of experimentation on human subjects. Borrowing from that framework does not imply that reckless automation in policing is the literal equivalent of medical or psychological experiments on human subjects. Nor does such a comparison imply that the technical aspects of institutional review boards should apply directly to new policing strategies. But turning to a bioethical framework has value because it draws attention to the subjects - the communities affected - of policing. To the extent that the ethical considerations applied in human subjects research provide useful insights to apply to the many changes in policing, they open a new conversation. What if we think of new forms of automated decision-making in policing as experiments on communities that might impose harms with life-altering decisions?

Download the article from SSRN at the link.

Ferguson on Facial Recognition and the Fourth Amendment @ProfFerguson

Andrew Guthrie Ferguson, University of the District of Columbia School of Law, has published Facial Recognition and the Fourth Amendment. Here is the abstract.

Facial recognition offers a totalizing new surveillance power. Police now have the capability to monitor, track, and identify faces through networked surveillance cameras and datasets of billions of images. Whether identifying a particular suspect from a still photo, or identifying every person who walks past a digital camera, the privacy and security impacts of facial recognition are profound and troubling. This Article explores the constitutional design problem at the heart of facial recognition surveillance systems. One might hope that the Fourth Amendment – designed to restrain police power and enacted to limit governmental overreach – would have something to say about this powerful and permeating surveillance technology. But current doctrine and constitutional theory offers little privacy protection and less practical security than one might expect. Even worse, by studying the Fourth Amendment through the lens of facial recognition technology other doctrinal limitations come into focus. Issues of error rates, racial bias, unfairness, and transparency in policing more generally become magnified when trying to design a new surveillance system for law enforcement. The Article then offers a constitutional design solution to some forms of facial recognition surveillance. The Supreme Court’s recent cases on digital technologies suggest a way to “future-proof” the Fourth Amendment in the face of certain types of mass surveillance technologies. In addition, this Article suggests a new legislative framework for facial recognition to fill in the privacy and legitimacy gaps left by the current Fourth Amendment doctrine.

Download the article from SSRN at the link.

Joh on The Consequences of Automating and Deskilling the Police @elizabeth_joh @UCDavisLaw

Elizabeth E. Joh, University of California, Davis, School of Law, is publishing The Consequences of Automating and Deskilling the Police in the UCLA L. Rev. Discourse (2019). Here is the abstract.

Almost no one thinks of automation and the consequences it will bring to policing. This is a mistake. Automation — the combination of artificial intelligence and robotics — is spreading everywhere. Whatever its benefits, we will also face problems as automation replaces human labor. One consequence may be mass unemployment in affected industries. Another consequence of automation is deskilling. The term deskilling refers to the skills and knowledge needed to perform a job that are lost when automation takes over. What happens when the police become deskilled? The deskilling of policing is inevitable because automation is increasingly a part of policing. Many American police departments already use artificial intelligence: it drives automatic license plate recognition, social media threat analysis, predictive policing software, security robots, facial recognition technology, and autonomous drones. Observers of the military have already begun to discuss the legal and policy effects that similar automation will have on soldiers, and on the nature of waging war itself. The deskilling associated with automation will apply to the police, too. The increasing role that artificial intelligence and robotics will play in policing will mean not only that automation will help traditional policing, but that it will also replace some policing altogether. Replacement will mean that human police officers will face a deskilling issue. They will lose some of the core skills we associate with policing. These changes may lie in the future, yet we can already identify some of the law and policy questions they will raise. First, automation and deskilling would undermine the Fourth Amendment’s premise that the police possess a specialized skill requiring judicial deference. Second, automation and deskilling may lead to dramatically different ways of organizing the police. Third, automation and deskilling force us to consider whether diminishing the social aspects of policing is worth the benefit of increased automation.

Download the article from SSRN at the link.

Joh on AI and Policing: First Questions @elizabeth_joh

Elizabeth Joh, University of California, Davis, School of Law, is publishing Artificial Intelligence and Policing: First Questions in the Seattle University Law Review (2018). Here is the abstract.

Artificial intelligence is playing an increasingly larger role in all sectors of society, and that includes policing. Many police departments are already using artificial intelligence to help predict and identify suspicious persons and places. Increased computational power and oceans of data have given rise to inferences about violence and threats. Artificial intelligence (AI) will change policing just as it will healthcare, insurance, commerce, and transportation. But what questions should we ask about AI and policing?

Download the article from SSRN at the link.