In spite of the potential benefits of using body-worn camera footage to improve community interaction, increase officer safety and evaluate training, police departments are only minimally using the information available at their fingertips. The crux of the problem comes down to time: It is impossible for agencies to dedicate the manpower required to review hundreds of thousands of hours of footage generated by body-worn cameras.
Criminal justice experts at Washington State University (WSU) are hoping to solve this problem by using advanced scientific tools and techniques – such as data analytics, biometrics and machine learning – to examine the complex factors that shape interactions between police and community members.
Researchers in the new Complex Social Interaction (CSI) laboratory at WSU are designing algorithms and software that analyzes body-worn camera footage. Led by Dr. David Makin, the research team includes Dr. Dale Willits within the Department of Criminal Justice and Criminology, Dr. Rachel Baily within the Murrow College of Communication, and Dr. Bryce Dietrich from the University of Iowa, Iowa Informatics Initiative (UI3).
Since its launch early this year, the lab has analyzed more than 2,000 interactions between the police and community members and numerous records from law enforcement incidents to identify, code and catalog key variables associated with a range of outcomes, positive to negative. Location, lighting, time of day, number of people present, gender, race, verbal and physical stress, and intensity of the interaction are among the contextual factors assessed.