Police traffic stops are common, complex interactions that can be a tool to improve public safety or escalate to violence. Effective communication in these situations is crucial to ensure officer and civilian safety, enforce the law, and build public trust. This project develops artificial intelligence (AI) tools that enable researchers to analyze footage from officers’ body-worn cameras, learn about officer-driver communication and refine best practices for traffic stop outcomes. To achieve this, the project draws on collaborative research capacity developed between academic researchers, the Los Angeles Police Department, and over a dozen community organizations. The research team’s multidisciplinary, community-engaged approach ensures that the AI tools being developed reflect a wide range of viewpoints and address the concerns of these different stakeholders. These AI tools are trained on assessments created by individuals from varied backgrounds, including retired police officers and Angelenos with a mix of past positive and negative experiences interacting with the police. After development, these tools can be used by police departments and local governments across the country to lower costs and enhance transparency, accountability and learning. This project advances computer, social, and engineering science by developing video language models that incorporate multiple stakeholder perspectives and building infrastructure to support collaborative development of AI tools