Algorithmic Sovereignty and the New Security Dependencies: How Foreign AI Surveillance Technologies Reshape Domestic Autonomy in the Global Sout

Abiade, Sheriffdeen Folaranmi (2025) Algorithmic Sovereignty and the New Security Dependencies: How Foreign AI Surveillance Technologies Reshape Domestic Autonomy in the Global Sout. World Journal of Advanced Research and Reviews, 27 (2). pp. 162-180. ISSN 2581-9615

The proliferation of artificial intelligence (AI) technologies has intensified global interdependencies, particularly in the realm of digital surveillance and governance infrastructure. As AI surveillance tools become increasingly embedded in public security, migration control, and political intelligence operations, countries in the Global South face a new paradigm of strategic vulnerability algorithmic sovereignty. This refers to a nation’s capacity to exercise full control over the data, infrastructure, and decision logic that underpin algorithmic systems operating within its borders. However, many states in the Global South have adopted foreign-built AI surveillance platforms primarily from dominant geopolitical actors without full access to source code, algorithmic parameters, or data governance rights. This dependency introduces critical security, privacy, and political risks, enabling vendor states to potentially monitor, manipulate, or extract sensitive domestic information under the guise of technological partnership. This study explores how such foreign AI surveillance technologies reshape domestic autonomy through opaque systems integration, extraterritorial data flows, and algorithmic opacity. By drawing on case studies from Africa, Southeast Asia, and Latin America, the paper highlights how imported AI infrastructures embed a form of digital neocolonialism, eroding institutional accountability and creating asymmetrical power relations. It further examines how these dependencies undermine local capacity-building efforts, distort national cybersecurity priorities, and challenge democratic oversight in public sector surveillance programs. The analysis concludes by advocating for regional algorithmic governance frameworks, indigenous AI development initiatives, and strategic procurement policies that reclaim sovereign control over data-driven decision systems. Addressing algorithmic sovereignty is not merely a technical concern but a fundamental aspect of maintaining political independence and safeguarding civil liberties in an increasingly AI-mediated global order.