Matthew Aloysius Burke

Bridging Borders with AI: Improving Immigration Processing Through Multilingual Communication Tools

Matthew is currently completing his Honors thesis, which analyzes the shortcomings of the U.S. immigration system and border security. One of the most pressing issues Matthew has identified is the inefficiency of processing due to chronic understaffing and outdated infrastructure. Millions of migrants are left waiting at the U.S.-Mexico border, often without access to timely legal information or documentation. This issue is especially severe for non-English speakers, who face additional barriers to understanding their rights, court procedures, and legal obligations.  

Matthew's proposed project explores how artificial intelligence can be used to address this problem by creating a multilingual communication toolkit designed to reduce wait times and improve access to information. The toolkit would include an AI-powered chatbot capable of answering frequently asked questions in multiple languages, translation tools for legal documentation, and an interactive system that helps users track their court dates and understand the legal process. Individuals who do not speak English would, in theory, gain full access to essential legal documentation, information about court proceedings, and resources regarding rights violations in their native language—bridging a communication gap that has historically disadvantaged millions. 

This project directly supports Matthew's academic and professional goals in immigration law and international policy while offering a potential model for more humane, efficient, and accessible border processing systems. It also doubles as an extension of his Honors thesis, enriching the existing project to exist in a more modern context. The tangible outcomes of this project will include a prototype interface for the communication toolkit and a policy brief assessing its feasibility, ethical implications, and potential for real-world application. These deliverables will be informed by research, stakeholder interviews, and case studies, all of which will culminate to explain either the current applicability of AI in this setting, or its future use.
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