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BackChinese Police Force Study Envisions Autonomous Machines Managing Urban Unrest
Chinese Police Force Study Envisions Autonomous Machines Managing Urban Unrest
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SCMP Economy4/20/2026Tech1 min readChina

Chinese Police Force Study Envisions Autonomous Machines Managing Urban Unrest

People's Armed Police engineers outline scenario with roadblocks, facial recognition and internet blackouts without human officers

Quick Look

  • A study by China's People's Armed Police Force engineers outlines a scenario where autonomous machines manage urban unrest through roadblocks, facial recognition, and internet blackouts without human police intervention.
  • The scenario depicts a crowd protesting after a military takeover assaulting government installations.

AI-generated summary

Why It Matters

The study emerges as China continues to expand its technological surveillance capabilities, including facial recognition systems and social credit scoring. The PAP is China's internal security force responsible for maintaining public order and combating unrest.

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A new study from mainland China's internal security forces offers a glimpse into a future where urban unrest is managed by autonomous machines instead of police in riot gear. In a scenario laid out by engineering experts from the People's Armed Police Force (PAP), a crowd – incited by rumours following a military takeover of a large city – gathers in a central square to assault key government installations. Their protest meets a swift response: roadblocks are suddenly deployed, cutting off their advance. Key instigators in the crowd are swiftly identified and captured. Cut off from the internet and unable to broadcast their cause, the demonstrators eventually disperse on their own. Throughout the entire ordeal, they do not confront a soldier or police officer in person.

Open Questions

  • When was this study actually published?
  • What specific technologies are being developed?
  • Is this scenario theoretical or are these systems already deployed?

Related Topics

This article was originally published by SCMP Economy.

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