Exploring regulatory frameworks for AI/ML through different lenses: A comparative approach

Abstract

The recent rapid availability of AI/ML technologies to the general public has hastened responses varying from governments' consideration of imposing regulations to international and regional organizations in setting technical standards. Initiatives at national and international levels have thrown into sharp relief the differences in the way major global jurisdictions approach the governance and regulation of new, emerging technologies. The most prevalent model of analysing and characterising these approaches looks at the legal and socio-economic arrangements that define and govern the relation between the state, markets, enterprises, and citizens. This paper will use this model to map the respective roles of these stakeholders and their interaction within the emerging AI/ML ecosystem. The analysis will focus on the consumer/citizen lens under the watchful eyes of the governance and regulatory perspectives. This is followed by characterization of the governance and regulatory frameworks proposed by governments in the U.S., Europe, and China and identify the differences in policy priorities and preferences that shape their respective approaches. The paper concludes with an initial analysis of commonalities and divergences of these different approaches to AI/ML regulation, which could serve as a basis for further study.

Keywords: Artificial Intelligence, Machine Learning, Digital Governance, Regulatory Model, AI Ecosystem, Beneficial AI

DOI: 10.54941/ahfe1005080