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Department of Homeland Security Artificial Intelligence Use Case Inventory

In October 2023, the Department of Homeland Security published a list of 50 ways it uses AI tools in administration of immigration.

The US federal government wants to promote the use of “trustworthy artificial intelligence.” Rebecca HeilWeil, a reporter with FedScoop, reported that in October, “U.S. Citizenship and Immigration Services, which manages the country’s immigration application system, disclosed that it was using several forms of AI to adjudicate cases, including an AI-powered “evidence classifier,” a fraud detection system and a tool for predicting workloads.”

While Ms. Heilweil said she was not able to get DHS to comment on the inventory, we downloaded the list from USCIS and found it provides an excellent lens into the type of efficiency leaps DHS seeks in these tools.

The “use case” titled, “Timeseries Analysis and Forecasting,” in use by USCIS, is described as follows:

“USCIS is the component within DHS that oversees lawful immigration to the United States. That means USCIS receives, processes, and maintains all applications for admission for Lawful permanent residents (LPRs), or adjustments to LPR status. Also known as “green card” holders, LPRs are non-citizens who are lawfully authorized to live permanently within the United States and are required to fill out Form I-90, Application to Replace Permanent Resident Card (Green Card). Since there has been a considerable influx of green card applications, USCIS used a combination of exploratory data analysis to determine the most used categories for applicants submitting I-90’s and machine learning to create predictions of workloads. As a follow-on, USCIS used Autoregressive Integrated Moving Average (ARIMA) models on the I-90 form, which allowed the prediction of the total number of forms for a 2-year period. ARIMA is one of the easiest and effective machine learning algorithms to perform time series forecasting. This capability has been deployed in production for more than a year. This model was eventually enhanced using ML model to have better reusability and performance.”

Another USCIS tool, “Asylum Text Analytics,” “employs machine learning and data graphing techniques to identify plagiarism-based fraud in applications for asylum status and for the withholding of removal by scanning the digitized narrative sections of the associated forms and looking for common language patterns.”

The Customs and Border Protection department, uses the “Port of Entry Risk Assessments” AI tool “to develop, inform, and augment risk assessment processes that evaluate trade and travel data in real-time.  AI methods are applied to CBP data holdings, and the results are used to inform decision making.  These tools are continuously evaluated to ensure accuracy and precision, and support CBP’s core mission as part of the layered risk assessment strategy.”

The “Facial Recognition Service” tool, used by ICE (Immigration and Customs Enforcement) “is used during investigations conducted by HSI agents and analysts for identification of known individuals, as well as extracting faces for further investigations from perpetrators including child exploitation offenses, human rights atrocities, and war criminals.”

The USCIS “Person-Centric Identity Services Deduplication Model” AI tool, helps the USCIS unit, Person-Centric Identity Services (PCIS), “to be the authoritative source of trusted biographical and biometric information that provides real-time, two-way visibility between services into an individual’s comprehensive immigration history and status.”  When a person is submitting, sometimes over many years, huge volumes of data to pursue their visas or other immigration objectives, USCIS is inundated with mountains of paper. Even when it’s all scanned in, it can take USCIS humans months and months to organize and analyze the data. So it’s a natural application to use machine learning to digest all that data, and recording “dataset includes biographic information (name, date of birth, Alien #, Social Security #, passport #, etc.) as well as biographic information (fingerprint IDs, eye color, hair color, height, weight, etc.) for model training and matching purposes.”

This is of course the tip of the iceberg. While Hollywood has told us for years AI would take over the world, the truth of AI is that it’s an incredibly strong use of computers to corral massive databases into easy to manage datasets that assist rather than hinder the process. Over the past decade or more, we’ve seen processing times balloon from several months to many years.  AI will our government agencies bring speed back into the process.

Read More: Imwong

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