In an era defined by extreme Volatility, Uncertainty, Complexity, and Ambiguity (VUCA), artificial intelligence (AI) governance must transcend passive compliance checklists to become an embedded, adaptive socio-technical architecture. This paper proposes a triadic synthesis of Reinforcement Learning (RL), Generative AI (GenAI), and Cybersecurity, organized within a Seven-Layer Integrated Architecture spanning perception, cognition, adaptation, generation, protection, embodiment, and governance. Central to the framework is a formal isomorphism between Predictive Processing (PP) and Reinforcement Learning, in which both systems minimize prediction error through Bayesian updating (Friston, 2010; Friston et al., 2009). This isomorphism is operationalized through a safety-constrained objective function that treats variational free energy as a regularizer, mitigating the class of failures known as “reward hacking” (Laidlaw et al., 2025; Shihab et al., 2025; Skalse et al., 2022). Illustrative comparison of the Asynchronous Advantage Actor-Critic (A3C) algorithm against legacy Q-Learning suggests materially faster and more stable policy convergence under the resource-constrained, high-packet-loss conditions typical of emerging economies. By integrating the sub-Saharan African relational philosophy of Ubuntu/Unhu with global AI4People principles (Floridi et al., 2018; Van Norren, 2023; Yilma, 2025), the framework embeds explicit digital forensics workflows and blockchain-anchored chain-of-custody protocols (Atlam et al., 2024; Patil et al., 2024). The framework is further extended and empirically grounded through a twentyproject, four-cluster Edge-AI case portfolio spanning domestic safety, environmental intelligence, sustainable energy and agriculture, and healthcare accessibility in the Indian context, demonstrating the triadic architecture’s applicability from enterprise-scale governance to grassroots micro, small, and medium enterprise (MSME) innovation. This synthesis serves as a blueprint for organizations in the Southern African Development Community (SADC) and India to assert digital sovereignty, ensuring that autonomous systems are antifragile, context-sensitive, and designed for communal flourishing rather than extractive optimization.
Gabriel Kabanda· Zenodo (CERN European Organi...· 0 citations
In an era defined by extreme Volatility, Uncertainty, Complexity, and Ambiguity (VUCA), artificial intelligence (AI) governance must transcend passive compliance checklists to become an embedded, adaptive socio-technical architecture. This paper proposes a triadic synthesis of Reinforcement Learning (RL), Generative AI (GenAI), and Cybersecurity, organized within a Seven-Layer Integrated Architecture spanning perception, cognition, adaptation, generation, protection, embodiment, and governance. Central to the framework is a formal isomorphism between Predictive Processing (PP) and Reinforcement Learning, in which both systems minimize prediction error through Bayesian updating (Friston, 2010; Friston et al., 2009). This isomorphism is operationalized through a safety-constrained objective function that treats variational free energy as a regularizer, mitigating the class of failures known as “reward hacking” (Laidlaw et al., 2025; Shihab et al., 2025; Skalse et al., 2022). Illustrative comparison of the Asynchronous Advantage Actor-Critic (A3C) algorithm against legacy Q-Learning suggests materially faster and more stable policy convergence under the resource-constrained, high-packet-loss conditions typical of emerging economies. By integrating the sub-Saharan African relational philosophy of Ubuntu/Unhu with global AI4People principles (Floridi et al., 2018; Van Norren, 2023; Yilma, 2025), the framework embeds explicit digital forensics workflows and blockchain-anchored chain-of-custody protocols (Atlam et al., 2024; Patil et al., 2024). The framework is further extended and empirically grounded through a twentyproject, four-cluster Edge-AI case portfolio spanning domestic safety, environmental intelligence, sustainable energy and agriculture, and healthcare accessibility in the Indian context, demonstrating the triadic architecture’s applicability from enterprise-scale governance to grassroots micro, small, and medium enterprise (MSME) innovation. This synthesis serves as a blueprint for organizations in the Southern African Development Community (SADC) and India to assert digital sovereignty, ensuring that autonomous systems are antifragile, context-sensitive, and designed for communal flourishing rather than extractive optimization.
Gabriel Kabanda· Zenodo (CERN European Organi...· 0 citations