Predictive Peace”: ECOWAS and the Use of Artificial Intelligence, Mobile Data and Community Resilience

Abstract

This article proposes a policy-oriented “Predictive Peace” framework to ECOWAS. Differential capacity to share intelligence, combined with the porous nature of borders, transnational extremist networks, and rapid digital communications in West Africa, produces an environment that facilitates the growth of terrorist threats in the region. The “Predictive Peace” framework considers artificial intelligence (AI), mobile-data analytics and community resilience as mutually constraining elements of a regional early warning system. It analyzes qualitative documents in the field of peer-reviewed literature on cybersecurity and predictive analytics, and is complemented bycounter-terrorism and community intelligence. The legal and policy instruments of ECOWAS and the African Union are considered. The analysis identifies three key findings. First, AI is not sufficient to aid fully-automated Counter-Terrorism (CT) decisions, and mobile-data can help strengthen situational awareness. Second, there are legal and policy-related issues pertaining to the use of mobile-data to support situational awareness. Third, while community engagement can strengthen the quality, and legitimacy, of threat assessments, reporting systems, and other security architecture, this is true only if systems are designed to protect the citizen from retaliation and unaccountable and discriminatory decisions made by state actors based on algorithms. This article therefore positions predictive security as a model of governance. It argues that trust, a human-centered and rights-based approach, can be institutionally integrated into ECOWAS legislation and policy, and controlled by community oversight.

The contribution presents a well-grounded model, integrating the relationships between legal and policy authority, institutions, and social trust, with the right balance of technology.