Mobile Device Forensics for Investigations
Description
The AI is intended to solve the problem of analysts having to manually organize, decode, and review large volumes of complex mobile device data, which makes it difficult to quickly identify information relevant to an investigation.
Detailed example
The platform’s AI outputs include: (1) AI‑suggested category tags for extracted media (videos and images) and apps, based on user‑selected categories (e.g., media: cars, drugs, weapons; apps: chat, spoofing, cryptocurrency);(ii) AI‑decoded app data artifacts, such as chats, contacts, and locations; and (iii) AI predictions about whether a media file was captured on the extracted device or obtained from another source.
AI / analytics pattern
Computer Vision: AI that processes and interprets visual data (e.g., images and videos).
Automation level / stage
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
AI-generated category tags, app artifacts, and origin classifications allow analysts to more effectively prioritize human review of mobile device data that may be responsive to the investigation.
Audit / financial statement impact
This use case falls into a presumptive high-impact category under M-25-21 Section 6 (j) due to its role in supporting law enforcement activities, specifically application of digital forensic techniques. However, it does not meet the definition of high-impact AI as outlined in OMB Memorandum M-25-21 because its outputs do not serve as a "principal basis" for decisions or actions with legal, material, binding, or significant effects on an individual or entity's civil rights, civil liberties, or privacy; or human health and safety. The AI capabilities, including classification, decoding, and origin analysis, are designed to assist analysts in prioritizing human review rather than independently determining outcomes. For example, AI-generated tags and app artifacts are suggestions that require manual validation and further investigation before enforcement actions are taken. All outputs are reviewed as part of a broader investigative process before any actions are taken.
Controls / human review
ATO: Not reported; PIA: Not published