Managing Runaway AI: Lessons from Inflation Control for a Sustainable Artificial Intelligence Governance

Abstract

The exponential growth of artificial intelligence (AI) presents governance challenges resembling runaway inflation dynamics—marked by self-reinforcing feedback loops, instability, and the erosion of regulatory con-trol. This paper draws a novel parallel between the management of inflation by central banks and the urgent need for structured oversight in AI development. By adapting proven inflation control tools such as risk forecasting, centralized intervention, and international coordination, the study proposes a framework for sustainable AI governance. Emerging real-world cases, including AI safety bodies, regulatory impact assessments, and international cooperation efforts, support theoretical insights. This framework offers a proactive approach to balancing innovation with ethical and economic stability. As AI continues to transform industries, robust governance mechanisms—akin to monetary pol-icy regimes—are vital to preventing unintended consequences and ensuring that technological progress serves the broader public interest. Future research should evaluate and refine these regulatory models through applied case stud-ies to enhance their global relevance and enforceability.