Artificial Intelligence for Economic Resilience and Global Stability

Résumé fourni par la source

The current world economies are in a highly volatile framework characterized by thick interdependencies, and quick changing risk factors. The classical econometric models with their assumption of the stasis and restrictive data granularity cannot predict systemic shocks and timely interventions. This chapter provides a technical review of how Artificial Intelligence can increase economic resilience via predictive governance. It is a conceptualization of AI as a multi-layered analytical architecture that achieves high-frequency data streams, machine-learning prediction models, and policy optimization structures. The capabilities of deep learning, reinforcement learning, and network-based models to detect the emergent signals, forecast macroeconomic anomalies and simulate the counterfactual policy outcomes are put under stress. Transparency in algorithms, interpretable models and ethics in macro-level applications are also discussed in the chapter. It can be argued that AI-enabled predictive governance is necessary to develop resilient, adaptive, sustainable economic systems.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.