OMB Individually Reported

DEA Drug Signature Program Models

Low riskExact public inventory row

Description

Understanding the manufacturing origin and distribution route of illicit drugs by analyzing the chemical composition of seized drugs is a core DEA task. The purpose of this use case is to use AI/ML techniques to develop, maintain, and improve models that enable designated forensic chemists to identify a notional geographic origin or notional manufacturing route of samples selected for DEA's Drug Signature Programs.

Detailed example

Designated forensic chemists responsible for a particular Signature Program are provided with the model's output - a notional geographic region of origin or a notional manufacturing route of samples -- which these forensic chemists then evaluate along with other available information to better understand drug trends.

AI / analytics pattern

Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).

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

The solution supports designated forensic chemists at DEA to automate analyses and to more quickly identify trend changes regarding drug sample notional geographic origin or notional manufacturing route.

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.