Body camera footage as data: Using natural language processing to monitor policing at scale & in depth
Officer-worn body cameras are ubiquitous in modern law enforcement as a tool for accountability. The cameras’ mere presence may deter bad behavior, and recordings of misconduct can serve as evidence in the courtroom. We suggest an additional use for body camera footage: as data for identifying patterns in and ways of improving policing practices, which are often challenging to observe by other means. This use requires scaling up the analysis of body camera footage to the hundreds of recordings police departments collect each day. Natural language processing , a set of computational methods to process and analyze human language, is an important tool for this purpose. This tool typically uses artificial intelligence to extract key social components of speech—such as politeness, sentiment, or emotion—captured by body camera audio. We offer suggestions for using these tools to analyze body camera footage, and we identify issues relevant to the analysis, application, and governance of this footage. In the era of artificial intelligence, body camera footage is a promising source of data; the advice in this article is designed to maximize the chances that the conclusions drawn from that data are valid and in the public interest.
Authors
- Nicholas P. Camp (ORCID: https://orcid.org/0000-0001-9704-6133)
- Rob Voigt (ORCID: https://orcid.org/0000-0003-3743-0322)
Institutions
- Northwestern University (US)
- University of Michigan (US)
Publication Details
- Journal
- Behavioral Science & Policy
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1177/23794607241308636
- Citations
- 1
- Primary Topic
- Policing Practices and Perceptions
- Type
- article
- Field-Weighted Citation Impact
- 2.23