Project Challenge �
Traffic stops conducted by police officers are both mundane and potentially deadly. Past studies have shown harmful racial disparities in how civilians are communicated with during these stops. How can we engage diverse stakeholders and develop new machine-learning tools to define and measure high-quality communication in these contexts? How can communication in these contexts be improved?
Everyday Respect: Measuring & Improving Police Officer Communication During Motor Vehicle Stops
Los Angeles, California
NSF Award ID: SES-2228785
PI: Morteza Dehghani, University of Southern California
2022 Civic Innovation Challenge
Pilot Vision
- Build stakeholder-informed machine learning tools to measure communication between officers and community members (as captured by bodyworn video).
- Evaluate patterns in communication to identify possible disparities in how groups are treated and to identify successful strategies for achieving de-escalation and mutual understanding.
- Collaborate with LAPD to develop new training materials based on these findings.
Civic Partners:
- The Los Angeles Police Department
- The LEWIS Registry
- Center for Justice Innovation
- WARD Church
- RIDE
- The Hero in You Foundation
Research Partners:
- Georgetown University
- UC Riverside
- Loyola Marymount University
Research Questions
- What aspects of communication (e.g., tone, language, information content) do stakeholders believe are most salient in constituting good communication during motor vehicle stops?
- How do individuals’ views on “good” communication vary across stakeholder groups?