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Paper short abstract

Comparing Cape Town's operational predictive policing with Lagos's emerging surveillance infrastructure reveals how colonial legacies and corporate power shape algorithmic security governance across African cities, demanding new accountability frameworks.

Paper long abstract

This paper comparatively examines predictive policing adoption in Cape Town and Lagos, revealing how colonial legacies, political economies, and urban geographies shape AI-driven security governance. Drawing on 18 months of multi-sited ethnographic research, I analyze two divergent trajectories of algorithmic policing in major African cities.

Cape Town deploys operational predictive algorithms forecasting gang violence in Bellville and the Cape Flats, while Vumacam's license plate recognition network generates thousands of daily alerts. These systems extend South Africa's spatial surveillance history—from apartheid pass laws to contemporary management of racialized inequality—yet face growing civil society resistance challenging discriminatory impacts.

Lagos follows a different path: predictive policing remains in pilot phases, but the city has invested hundreds of millions in Chinese-built "safe city" infrastructure—CCTV cameras, facial recognition systems, and centralized monitoring centers from Huawei and ZTE. This surveillance apparatus creates the technical capacity and data infrastructure for algorithmic crime prediction while questions of data sovereignty, corporate influence, and accountability remain unaddressed.

Comparing Cape Town's operational systems with Lagos's emergent infrastructure reveals how global technologies are locally adapted, resisted, and reimagined. I argue that understanding AI governance in African cities requires analyzing not merely implemented algorithms but the broader sociotechnical assemblages—surveillance networks, public-private partnerships, colonial spatial logics—that make predictive systems possible, contested, and consequential. This comparative approach illuminates critical intervention points for accountability and alternative visions of urban security beyond punitive algorithmic control.