China’s PAP explores automated crowd control amid systemic urban unrest: systemic risks of dehumanised security

Indigenous epistemologies universally reject the dehumanisation of conflict resolution, framing security as a relational process rather than a technological fix. In China, this critique is echoed by marginalised groups like the Uyghurs, who experience state violence as a continuation of colonial-era suppression of Turkic identity. The PAP’s proposal ignores these traditions, instead normalising a model of control that aligns with settler-colonial logics of erasure and containment.

The use of 'neutral' technology to justify repression has deep historical roots, from colonial-era fingerprinting to 20th-century eugenics and modern facial recognition. China’s experiment mirrors Cold War-era crowd-control tactics in the US and USSR, where 'scientific' policing was used to suppress dissent under the guise of order. The PAP’s scenario also echoes historical urban unrest responses, such as the 1989 Tiananmen Square crackdown, where technology (e.g., tanks, surveillance) was deployed to 'restore stability.'

Cross-culturally, the rejection of automated coercion is evident in movements like India’s anti-CAA protests, where communities organised human chains to resist state violence, or South Africa’s Truth and Reconciliation Commission, which prioritised dialogue over algorithmic punishment. In contrast, China’s model aligns with Singapore’s 'technocratic authoritarianism,' where efficiency is weaponised to justify repression. These comparisons reveal how 'neutral' tech solutions often serve as Trojan horses for cultural erasure.

The PAP’s proposal lacks peer-reviewed validation on the psychological and social impacts of automated crowd control, relying instead on internal engineering studies. Research on algorithmic bias (e.g., in facial recognition) suggests such systems disproportionately target marginalised groups, while studies on crowd dynamics show that dehumanised responses often escalate rather than de-escalate violence. The absence of independent oversight in the PAP’s scenario raises ethical and methodological red flags.

Artistic and spiritual traditions universally frame violence as a failure of imagination, not a failure of technology. Chinese ink wash paintings often depict unrest as a natural force to be harmonised, not suppressed, while African griot traditions use storytelling to resolve conflicts without coercion. The PAP’s proposal ignores these traditions, instead reducing human complexity to a problem solvable by machines—a hubristic stance that spiritual traditions would label as 'technological idolatry.'

If implemented, China’s automated crowd control could set a global precedent for 'predictive policing' in authoritarian states, normalising dehumanised governance. Scenario modelling suggests this could lead to a feedback loop where dissent is preemptively crushed, eroding social trust and fueling underground resistance. The long-term risk is a bifurcated world: democratic societies grappling with algorithmic accountability, while authoritarian regimes perfect the art of invisible repression.

The PAP’s scenario entirely excludes the voices of protesters, who are framed as a 'crowd' to be managed rather than agents of legitimate grievance. In China, marginalised groups like the Uyghurs, Tibetans, and Falun Gong practitioners have long experienced state violence under the guise of 'stability maintenance,' yet their perspectives are systematically erased from such narratives. The lack of representation in the PAP’s study reflects a broader pattern of silencing dissent in authoritarian systems.