AI-Enhanced ICE Tip Processing
Description
This use case intends to solve the problem of the time-consuming manual effort required to review and categorize incoming tips.
Detailed example
This solution uses a large language model (LLM) to enrich web tips with two additional data elements: (1) a high-level summary of the tip (BLUF), and (2) a recommended case category. The LLM generates BLUFs in English, regardless of the language used in the raw tip submission. For non-English tips, analysts may click a button to translate the full tip violation summary data element into English. The LLM is configured to only recommend case categories from a list of predefined HSI case categories.
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 use of AI in this process enables the Tip Line team to more quickly identify and action tips recommended for urgent case categories. Additionally, the introduction of a BLUF field saves time by providing analysts with a high-level understanding of a tip before they review its details.
Controls / human review
ATO: Yes; PIA: Not published
Data needed
The system uses commercially available large language models trained on the public domain data by their providers. There was no additional training using agency data on top of what is available in the models’ base set of capabilities. During operation, the AI models interact with tip submissions.