MACO Project: Law Enforcement CAD Data Autocoder
Description
MACO is intended to solve the lack of standardization in Computer-Aided Dispatch (CAD) data across law enforcement agencies. CAD event descriptions are free-text, highly variable, and differ widely in terminology, structure, and coding practices. Because of this inconsistency, it is currently not possible to aggregate, compare, or analyze CAD data across jurisdictions at scale. MACO uses machine learning and language models to automatically classify raw CAD text into a standardized event taxonomy, enabling consistent analysis, cross-agency comparisons, and the development of national estimates of calls for service.
Detailed example
The system outputs a standardized event-type classification for each CAD record. For each raw text description, the model generates a predicted category from a predefined event taxonomy (e.g., “Property Crime: Theft,” “Traffic Incident,” “Disturbance,” etc.). The final deliverable is a CAD dataset with these standardized classifications appended to each record, enabling consistent analysis and aggregation across agencies.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
The AI provides standardized classifications of CAD event text, allowing BJS and partner agencies to analyze police activity consistently across jurisdictions. For BJS, this enables the production of scalable, comparable national estimates of calls for service—filling a major data gap not addressed by traditional crime measures. For state and local agencies, the standardized schema improves internal organization of CAD data and supports regional or state-level comparisons of police workload and community needs. For the research community and the public, MACO expands understanding of how law enforcement resources are used, the types of events agencies respond to, and broader patterns of community demand for police services. Overall, the tool enhances data quality, improves analytic capacity, and supports evidence-based decision-making across the criminal justice ecosystem.
Audit / financial statement impact
Does not produce an output that serves as a principal basis for decisions or actions with legal, material, binding, or significant effect on any of the individuals or entities identified in OMB-25-21.
Controls / human review
ATO: Not reported; PIA: Not published