Unpacking the drivers of artificial intelligence regulation: driving forces and critical controls in artificial intelligence governance

Abstract

The burgeoning field of artificial intelligence (AI) necessitates a nuanced approach to governance that integrates technological advancement, ethical considerations, and regulatory oversight. As various AI governance frameworks emerge, a fragmented landscape hinders effective implementation. This article examines the driving forces behind AI regulation and the essential control mechanisms that underpin these frameworks. We analyze market-driven, state-driven, and rights-driven regulatory approaches, focusing on their underlying motivations. Furthermore, critical regulatory controls such as data governance, risk management, and human oversight are highlighted to demonstrate their roles in establishing effective governance structures. Additionally, the importance of international cooperation and stakeholder collaboration in addressing the challenges posed by rapid technological change is emphasized. By providing insights into the strengths, weaknesses, and potential synergies of different governance models, this study contributes to the development of equitable and effective AI regulatory frameworks that encourage innovation while safeguarding societal interests. Ultimately, the findings aim to inform policymakers, industry leaders, and civil society organizations in their efforts to foster a future where AI is utilized responsibly and equitably for the betterment of humanity.