In the past few decades, there has been an embrace of “smart borders” within immigration systems where the development of Artificial Intelligence (AI), machine learning, and other related technologies for use in shaping migration policy and border management can be seen as a socio-technological problem at the intersection of state power, technological affordances, and human rights. Focusing specifically on Automated Decision-Making (ADM) systems in the United States and the European Union, this paper examines three main use cases of ADM within migration policy and border management: early-warning systems for migrating forecasting, border management via pre-screening and border checks, and migrant resettlement services. By laying out a human rights framework for assessing ADM technologies based on privacy, transparency, fairness, and more, this paper draws on case studies of specific software and programs within each distinct use case to argue that ADM is more appropriate in some use cases than in others. Ultimately, this study finds that, overall, ADM used for pre-screening and border management is incredibly controversial as it possesses a tremendous risk of surveillance, profiling, and a large potential for abuse of people and power. In contrast, ADM is much better suited for use in early-warning systems and migrant resettlement software as these technologies are generally used to aid immigrants and humanitarian/ non-profit agencies.
Bots, Borders, and Beyond: An Analysis of Automated Decision-Making Technologies in Migration Policy and Border Management
- Fellow: Nidhi Salian
- Advisor: Ellen Goodman