Collaborative Governance and Algorithmic Accountability: Regulating Risks and Restructuring Organizations for AI Integration
TL;DR
A normative analysis of thirteen recent studies on the challenges of technology implementation, ethical trust, and legal regulation suggests that the current governance dilemma stems not only from technological limitations but also from institutional neglect, which enables accountability avoidance.
Abstract
The widespread application of artificial intelligence (AI) in corporate resource planning and public decision-making has provided impetus for improving management efficiency and creating social value. However, the complex structure and opacity of algorithms have led to a crisis of trust, posing challenges to traditional public management accountability mechanisms. Drawing on socio-technical systems theory, this paper provides a normative analysis of thirteen recent studies on the challenges of technology implementation, ethical trust, and legal regulation. The findings suggest that the current governance dilemma stems not only from technological limitations but also from institutional neglect, which enables accountability avoidance. Although the EU AI Act proposes a preliminary form of collaborative governance, it still has shortcomings in terms of procedural justice and the feasibility of human oversight. The governance logic should shift from individual oversight to an organization-in-the-loop approach, to achieve sustainable and responsible AI governance through the construction of a procedural justice framework.