TWO PARADIGMS OF ALGORITHMIC SECURITY GOVERNANCE: CENTRALISED INTEGRATION AND INTEROPERABLE FRAMEWORKS IN THE USE OF AI FOR STATE SECURITY

Abstract

Artificial intelligence (AI) plays an increasingly important role in counterterrorism by enabling the rapid processing of large volumes of data and the identification of patterns, anomalous behaviours, and emerging risks. This article examines two paradigms of algorithmic security: the centralised Chinese model and the decentralised, interoperable Israeli model. Adopting a comparative and primarily descriptive approach, the study draws on academic literature, policy documents, and native authors to analyse how AI is embedded within different institutional architectures A brief case study of the 2019 Hong Kong protests examines how predictive technologies were deployed in an urban context officially framed as a matter of security and public order. The analysis shows that the strategic impact of AI depends less on technological sophistication alone and more on governance structures, institutional coordination, and legal frameworks. The study also acknowledges limitations related to restricted data access and the evolving nature of AI-driven security systems.