The growing use of data-centric technologies is transforming criminal justice in the United States. These technologies affect the scale and nature of collected data, enable the detection of discriminatory patterns of policing, and influence bail recommendations for pretrial detainees, and management of prison populations. Modern computational and statistical methods offer the promise of increased efficiency, equity, and transparency, but their use raises complex legal, social, and ethical questions. In this course, we will discuss the application of techniques from machine learning and statistics to a variety of criminal justice issues, analyze recent court decisions, and examine the relationships between law, public policy, and data. Special attention is paid to the rules of evidence as they apply to electronic or digital evidence, the role of expert witnesses, and the laws and regulations governing electronic surveillance.

Students completing this course will be able to: 

• Describe the substantive legal, policy and ethical dimensions of big data, predictive analytics, machine learning and decision-making and related technologies through exposure to a variety of sources of information and diverse perspectives.
• Describe the critical issues in policing and corrections in the use of data management and organization, surveillance, use of new technologies, evaluations of success, legitimacy, ethics, accountability, and professionalism.
• Explore data sources for understanding the geography of crime and various uses of GIS in Criminal Justice
• Recognize and describe common forms of criminal justice data including detection systems, CCTV, Database and Information Exchange Systems, Digital Video recording, Rapid ID System, Computer Aided dispatch and monitoring systems and 3D Imaging of Crime/Incident scenes