Open Civil Court Data Initiative

In conjunction with the Rand Corporation, the lab is compiling a comprehensive data set of civil court data. These data will represent the most comprehensive list of case content, with machine learning algorithms utilized to determine the content, case outcomes, and type of case. Running a continuous crawl of these sites, we continue to update these data, which are being utilized in a series of research projects, such as the prediction of compensatory and punitive damages, identification of culpability thresholds, and other pertinent aspects of civil trials.

Identifying Human Trafficking

Human trafficking poses one of the most egregious crimes against humanity. For the past six years members of the Computation Justice Lab have worked intensively with law enforcement agencies to identify instances of human trafficking, including both labor and sex trafficking. These ground truth are currently being utilized by US attorneys and private-public partnerships to identify instances of human trafficking and inform law enforcement agencies of such instances. A current project, in conjunction with Liberty Asia, involves the identification of labor trafficking that examines financial transaction data at the transaction level in southeast Asia.

Enhancing Officer Safety

Officer safety is one of the most important issues that law enforcement agencies face. By improving officer safety, law enforcement agencies can attract higher quality officers. The overwhelming majority of officers that are killed or injured on the job result from domestic violence calls for service. Although this is often known after the fact, determining this information prior to the arrival of an officer could offer opportunities for law enforcement to enhance their safety. Working directly with administrative records from law enforcement agencies and established working relationships, we will develop algorithms that generate a risk score for law enforcement agents responding to calls for service. We will then utilize a randomized controlled trial to determine the effectiveness of the officer safety tool in reducing officer involved deaths and injuries.

Peer Effects in Law Enforcing

Peer effects in labor productivity, education and social interactions have been well-established. Police engage with numerous peers throughout their career, starting with their initial training. Working with a number of law enforcement agencies, this project aims to unearth the impact of law enforcement peer interactions on the quality of policing. Specifically, we examine how different peer interactions during the training process impacts downstream policing conduct, such as violent interactions that include officer involved shootings.