The U.S. Department of Homeland Security Center of Excellence for Cross-Border Threat Screening and Supply Chain Defense, CBTS, led by Texas A&M AgriLife Research, worked with a Summer Research Team at the University of North Texas (UNT) to examine how game theory tools could be used to examine alternative processes for adjudicating asylum requests by foreign nationals who are unable to return or fear returning to their home countries due to past persecution or a well- founded fears of being harmed. The University of North Texas team included the Principal Investigator Dr. Michel Fathi in the Department of Information Technology & Decision Sciences, and one of his students, Ramkumar Santhanam.
Media analysis, and natural language processing
While many migration and asylum studies have used forecasting techniques, social media analysis, and natural language processing to examine asylum decisions, the University of North Texas Team approached the asylum-granting process by analyzing hypothetical asylum decisions within a game theory context. Over the ten-week project, the team examined the U.S. immigration system and the asylum seekers from the perspective of revealed preferences, which could be used to improve asylum processes while also minimizing the number of cases considered for asylum. Interestingly, no information or personally identifiable information from actual asylum seekers was used in this summer’s efforts. Instead, they relied on academic literature on asylum systems and immigration policy to examine options and investigated the use of game theory approaches.
Combining applied mathematics and data analysis principles
By combining applied mathematics and data analysis principles this team developed sophisticated models that simulate the interactions between asylum seekers, immigration officials, and various stakeholders. Their models consider factors such as regional conflicts, socio-economic conditions, and policy decisions to predict the outcomes of different scenarios. Despite the complexity, the researchers worked to identify how different strategies might improve the asylum process, minimize backlogs, and ensure fairness while maintaining national security. Based on simulation and analysis, the research was designed to identify optimal strategies that could lead to more efficient and equitable asylum processes, including changes to asylum application workflows, decision-making criteria, or resource allocation. The goal was to find approaches that minimize delays, enhance fairness, and address national security concerns. The work is still in progress, but it provides valuable insights into the potential consequences of different policy choices that could be used by policymakers to make evidence-based decisions about the design and implementation of future effective asylum policies that balance humanitarian and national security interests.
The UNT team plans to continue using game theory applications to analyze and solve asylum problems to aid the interests of various stakeholders affected by the asylum process. For those along the border who play key roles in safeguarding national security and managing immigration, completion of this study holds the potential to offer valuable insights into developing more effective and efficient asylum policies. Ultimately, the study’s findings and policy recommendations have the potential to create significant improvements in the lives of those seeking refuge while aligning with mandates to protect national security.