4 ways to address the failures we found along the US border’s “virtual wall”

MIT Technology Review today published our investigation into how many people have died near the “virtual wall” of surveillance towers that the US government has installed along the US-Mexico border. We found cases of people who walked undetected through areas surveilled by advanced, AI-enabled towers and later died nearby, where their bodies remained unnoticed for weeks or months. These cases reflect systemic flaws in the virtual wall: broken towers, algorithms that failed to detect people, and agents who simply did not respond to alerts. This story is part of Dying on Camera , a collaboration between MIT Technology Review and Times of San Diego . Journalists in both newsrooms spent the past year examining the failures of border surveillance technology and uncovering the stories of the people who die in the borderlands . Each of these deaths should have raised alarms inside US Customs and Border Protection (CBP) about the flaws in the agency’s surveillance network. This is particularly true for cases near the latest towers built by the defense company Anduril, which continues to win major contracts and is poised to benefit from the windfall of federal money slated for border security. The US is set to spend $1 billion to triple the size of the virtual wall by 2034. Here are four ideas for what CBP should do next to address these failures. 1. Conduct a comprehensive audit of deaths near the virtual wall In this June 16, 2021, file photo, a family from Venezuela moves to a Border Patrol transport vehicle after they and other migrants crossed the U.S.-Mexico border and turned

AI surveillance system failures led to deaths

The failure of AI-enabled surveillance towers to detect people and prevent deaths along the US-Mexico border represents a serious humanitarian and systemic flaw, worsening harm to vulnerable populations. This negligence and malfunction decrease human flourishing significantly. The evidence is recent, specific, and well documented.

This is primary investigative reporting with specific figures showing an AI-enabled surveillance system implicated in deaths through detection failures and human non-response, alongside lack of transparency and planned expansion. The evidence is strong and directly tied to loss of life, not speculative, supporting a materially concerning score rather than an extreme one since the issue is bounded to a specific program.

The article provides evidence of AI-enabled surveillance towers failing to detect people who subsequently died, with bodies remaining unnoticed for extended periods. This indicates a severe failure of technology intended for border security, leading to tragic loss of human life and systemic flaws in a critical system. The score reflects a strong negative implication for human well-being and governmental accountability.

The article reports failures of AI-enabled surveillance towers leading to deaths. The US plans to expand this system despite known flaws. This implies a significant risk to human life.

SOURCE     MIT Technology Review: AI (tier 1)
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DOCUMENT   a62db509-e5db-4431-a54e-03292dfc398c
           https://technologyreview.com/2026/09/21/1144164/border-towers-surveillance-policy-recommendations
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EVIDENCE   3 extracted excerpts
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MODEL RUN  5 runs, methodology 1.0.1
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SCORE      -73  (Strongly adverse)
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CONFIDENCE 84%