Artificial Intelligence (AI) tools are central to U.S. law enforcement and adjudication. However, their deployment also reveals deep-rooted racial biases and ethical concerns. For instance, peer-reviewed research shows that facial recognition algorithms underperform when analyzing the faces of women, young people, and individuals with darker skin tones, leading to wrongful arrests and false identifications that disproportionately impact communities of color. This talk explores how federal agencies, including Immigration and Customs Enforcement (ICE) and Customs and Border Protection (CBP), have leveraged AI and vast data resources—ranging from DMV databases to utility records—to conduct mass surveillance, fast-track deportations, and "predict" crime. As a scholar of law and society and immigration, I pay close attention to the intersection of AI, systemic racism, and immigration policy – and how law and technology must work together to address substantive justice and equal protection. I also discuss the urgent need for regulatory oversight to prevent the unchecked expansion of biased surveillance practices in immigration enforcement today.
