Research Update: Addressing the Struggles & Surprises

Project Title: Algorithmic Law Enforcement: Exploring the Human and Civil Rights Implications of Predictive Policing

Reflecting on my first three weeks dedicated to my research project exploring the human and civil rights implications of data-driven and predictive policing, I am feeling satisfied with my project, and grateful for all I have learned through this process. Through reviewing a large chunk of the academic literature regarding these law enforcement technologies, alongside news stories and investigations (some of which include firsthand accounts from people targeted by predictive policing programs), I have gained so much insight into the complexity of evaluating predictive policing through a multidisciplinary, human rights centered lens. I have so much appreciation for this process, but it has certainly brought up surprises, struggles, and even somewhat philosophical questions.

For starters, data-driven policing programs are not monolithic, and contrarily, there exists a great variety between departments that implement the technology. The most wide-level distinction is between place-based and person-based predictive policing programs. The first is more common and predicts where crime is most likely to be committed and where police efforts should be concentrated while the second predicts who is most likely to commit a crime based on aggregated person data and records. There is of course great variety even within these categories, and both have great potential to discriminantly concentrate police efforts on certain individuals, acknowledging differences between subtypes of this technology is important when making high-level claims about their potential to violate human rights. 

This open-access article in AI and Ethics does a good job diving into some of these concerns, among many others in a very readable fashion: Five ethical challenges facing data-driven policing by Jeremy Davis, Duncan Purves, Juan Gilbert & Schuyler Sturm 

Pasco County, Florida, where I am from, and where I am conducting my project, implemented a person-based program that led to community outrage starting back in 2020 following a Pulitzer Prize-winning Tampa Bay Times investigative piece entitled “Targeted.” This highlights another frustration in my research: the painstaking process of finding any updates on legal action regarding intelligence-led policing programs. For example, the U.S. Department of Justice very recently reached a settlement with Pasco County Schools that stemmed from the efforts of the P.A.S.C.O. Coalition: People Against the Surveillance of Children and Overpolicing, an organization formed following community outrage about data sharing between the public school system and the Pasco County Police Department.

This is because the police department was alleged to be factoring data from the public school systems (such as disciplinary infractions) into their intelligence-led, predictive policing program. The DOJ found that Pasco County schools violated the civil rights of students with disabilities, outlining important changes that will be implemented in the upcoming school year. This is an important step toward protecting the rights of students, but the predictive policing program remains unaddressed by the DOJ. 

Read the settlement: Settlement Agreement between the United States and the Pasco County School District

In that same vein, legal and political updates are often disappointing from a research angle. As shown by the Florida House and Senate Bill pictured below, in 2021 legislators attempted to regulate intelligence-led policing programs. In both the House and Senate, this bill died in the first committee it was heard in, effectively squashing the legislators’ attempt to increase the transparency of these programs in Florida. 

As much as it can be frustrating when updates are unsatisfying or unresolved, this is ultimately the nature of studying technological advancements in law enforcement; they tend to rapidly outpace the legislation that governs them. This is partially what motivates my research. To achieve progress in the laws that govern technological advancements and their application for governmental surveillance, awareness of these issues must be increased. Overall, to push forward through all of the inconveniences, surprises, and struggles that come with this work, I think back to my community. After witnessing the impact of intelligence-led policing in my hometown community, I am motivated to do my due diligence with my research project.