Offense Text Auto-Coder (OTAC) - Automated offense coder from offense charge text strings used for the BJS National Pretrial Reporting Program
Description
The purpose of this tool is to improve description and comparability of offense charges across jurisdictions. When using justice administrative data from various jurisdictions (localities, states, and federal), the way offenses are described (i.e., the exact text strings used) vary greatly. For example, assault and battery may be spelled out, or abbreviated in novel ways such as A&B, A & B, A+B, A?B, battery & aslt, etc. This tool is used to facilitate grouping identical concepts under one common set of offense codes. The data that BJS makes available will be aggregated or deidentified.
Detailed example
The output of this autocoder is common definitions for offense charge classification. It has been trained on an offense crosswalk for the BJS National Corrections Reporting Program (NCRP) (https://www.icpsr.umich.edu/files/NACJD/ncrp/Offense_Code_Crosswalk.xlsx) to convert plain-text offense descriptions into classifications routinely used by the NCRP.
AI / analytics pattern
Natural Language Processing: AI that processes, interprets, and shares information in human language.
Automation level / stage
c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
Expected benefit
Improved comparisons of criminal justice data
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: Yes; PIA: Not published
Data needed
The case owner relied on DOJ AI governance practices to select and prepare data, as well as evaluate performance.