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[CBC News] China, which is fast-tracking development of artificial intelligence and robotics, has produced a research paper that models how drones, unmanned armored vehicles and robot dogs could be used to suppress urban protests.
On April 20, the South China Morning Post reported that a team led by Du Bo at Gongcheng University—an institution affiliated with the People’s Armed Police—published the paper in the peer-reviewed journal Command, Control and Simulation. The study lays out training scenarios that deploy unmanned units to contain and disperse demonstrations.
The researchers construct a scenario in which a crowd, stirred by rumors, assembles in a major city square to attack key government facilities. The plan calls for rapid identification and arrest of core instigators, an internet cut to stem information flow, and measures to trigger crowd dispersal.
Rather than relying on soldiers or conventional police units, the response in the paper is carried out by unmanned armored vehicles, drones and quadruped robots. Those systems are tasked to operate in a four-step sequence—reconnaissance, cordon and containment, information operations, and arrests—executing AI-driven tactics at each stage.
SCMP noted that the paper uses the terms “Red Army” and “Blue Army” and refers to Taipei as a “new city,” language that suggests the authors envisioned a post-unification scenario. The scenario also includes outside actors fomenting violence to delay the unification process.
During detention operations, the plan favors nonlethal tools—nets, tasers and similar devices—while reserving final authorization to human operators. Human supervisors are described as setting ethical parameters remotely and collaborating with unmanned units through real-time data sharing.
SCMP also highlighted that the People’s Armed Police, which has long emphasized human-machine collaboration, appears increasingly interested in operations that raise dependence on intelligent systems.
Security analysts cautioned that, if implemented, such concepts could lower the political cost of hardline crackdowns. They also warned of serious risks: civilian harm from misidentification, unresolved questions of moral and legal responsibility, and vulnerabilities to hacking of centralized AI systems and communications networks.
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