US Department of Homeland Security

Summary

ICE Enforcement Removal Operations’ Alternatives to Detention (ATD) program exists to ensure compliance with release conditions and provides important case management services for non-detained noncitizens. ATD consists of the Intensive Supervision Appearance Program (ISAP), which utilizes case management and technology tools to support noncitizens compliance with release conditions, court hearings, and final orders of removal, while allowing them to remain in their communities as they move through the immigration process or prepare for departure from the United States. Once individuals are in the ATD-ISAP program, officers periodically perform case reviews to determine if current levels of case management and technology assignment are appropriate for the noncitizen in the program or if they need to be adjusted. During the case review, the officer will consider numerous factors to include, but not limited to, current immigration status, supervision and compliance history, pending benefits, being a care giver or care provider, current immigration stage, pending criminal history and/or convictions, the hurricane score, and other factors. The factor known as the Hurricane Score is a quasi-binomial, binary classification machine learning (ML) model that is given information by an analyst that is known about an individual (factors from case management details and participant actions) and determines the probability that the individual will abscond based on absconding patterns the model has learned from inactive ATD-ISAP case data. The model returns a score from 1-5, with the higher number equating to a higher risk. The officer may use this score as one of the many factors previously described when deciding the appropriate level of case management and technology for noncitizens enrolled in the ATD-ISAP program. Because the hurricane score can quickly evaluate an enormous amount of information on thousands of noncitizens in the ATD-ISAP program, it provides officers with additional insight that they would not have otherwise had when performing a case review.

Intended Purpose & Expected Benefits

The Immigration and Customs Enforcement (ICE) Enforcement and Removal Operations (ERO) division would like to explore technology that could help lead to time savings and eliminate human error due to overburdened officers. An AI generated hurricane score could also minimize the risk that a factor is overlooked due to officers being overburdened. The hurricane score may be one factor that is used to inform the decision-making process. The “Hurricane Score” models the potential risk (1-5) that a noncitizen who is released from detention with the requirement to check in with ICE through monitoring will abscond from the program, with a higher number indicating a higher risk of absconding.

System Outputs

The Hurricane score model determines a probability of absconding and outputs a number (1-5), with a higher number indicating a higher risk of absconding. This number is used as one of many factors an officer uses when reviewing an ATD-ISAP case to determine the appropriate level of case management and technology for a noncitizen.

Active Status

Active

CAIO Determination Justification

Not Required

Risk Management

Key Risks

There is a risk that the Absconder Model may include false positives and model bias. A false positive would occur when non-absconders are incorrectly classified with a score indicating a high probability of absconding. Model bias can arise if the training data is not representative of the full range of participants, leading to poor performance on certain patterns or characteristics. These risks are identified and if necessary remediated through error analysis during model testing and model performance monitoring.