Date of Award

2026

Document Type

Dissertation

Degree Name

PhD in Business

Department

Department of Computer Information Systems

First Advisor

Marco Marabelli

Second Advisor

M. Lynne Markus

Third Advisor

Silvia Masiero

Abstract

Governing emerging technologies such as Artificial Intelligence (AI) poses enduring challenges for policymakers, industries, and societies. Early-stage governance is often hindered by limited understanding of technological implications, rapid innovation cycles, and resistance from powerful industry actors who favor minimal oversight. Yet, timely and effective governance is essential, as new technologies are most malleable in their formative stages. This dissertation examines how emerging technologies can be governed effectively by using deepfakes technology as a focal case. This dissertation comprises three interrelated studies.

The first paper reviews the literature on deepfakes and emerging technology governance, identifying the distinct characteristics of deepfake technology and the limitations of existing theoretical frameworks in addressing AI-based systems.

The second paper empirically investigates how diverse stakeholders in the United States interact to shape deepfake governance. Using secondary qualitative data, it maps competing proposals and power dynamics, leading to the development of an Emerging Technology Governance Model that explains the interplay between legislative, industrial, and public initiatives.

The third paper extends the analysis through a cross-national comparison of deepfake governance in the United States and China, exploring how cultural, political, and institutional contexts influence regulatory trajectories. Together, these studies contribute to the literature on the governance of emerging technologies by revealing how stakeholder interactions, power asymmetries, and policy fragmentation shape governance outcomes. The findings offer both theoretical insights into multi-actor governance processes and practical guidance for designing more adaptive, inclusive, and effective governance mechanisms for AI-powered emerging technologies.

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