Abstract As artificial intelligence (AI) systems increasingly permeate society, the challenge for policymakers is evolving from whether to regulate how to govern effectively in a complex global landscape. With the formal adoption of landmark frameworks like the EU’s AI Act and diverse national strategies taking shape worldwide, the need for balanced and adaptable governance is more pressing than ever. This study addresses this challenge by proposing a framework for creating effective AI regulation that fosters innovation while mitigating significant risks. The research synthesizes insights from foundational ethical theories and game-theoretic principles to critically analyse contemporary policy developments and regulatory case studies. It proposes a risk-based, tiered regulatory model that calibrates oversight in proportion to an application’s potential societal impact. This article puts forward evaluation criteria that consider not only technical performance but also scalability, the reversibility of effects, and the embedded values within technological systems, moving beyond a simplistic view of technology as morally neutral. The study concludes with actionable recommendations for implementing adaptive governance mechanisms, such as co-regulation and regulatory sandboxes, and underscores the necessity of international cooperation to address the global nature of AI development and prevent regulatory fragmentation. By integrating deep theoretical analysis with practical, up-to-date policy insights, this research provides a guide for navigating the intricate trade-offs between innovation, safety, and equity in the age of AI.
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Pitabas Mohanty
Tina Stephen
Statute Law Review
Xavier School of Management
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Mohanty et al. (Thu,) studied this question.
www.synapsesocial.com/papers/69f988e215588823dae17d9b — DOI: https://doi.org/10.1093/slr/hmag012