Enhancing Ethical Governance of Artificial Intelligence Through Dynamic Feedback Mechanism

The rapid advancement of Artificial Intelligence (AI) has ushered in significant opportunities while also giving rise to profound ethical concerns. Governments, non-governmental organizations, research institutions, and industries worldwide have fervently engaged in the exploration and implementation of AI ethics. This work reviews the research and practice of AI ethical governance issues worldwide, with a particular emphasis on AI ethics legislation and the practical application of ethical principles. Within the current landscape of AI ethics governance research, several pressing challenges emerge, including the establishment of a robust ethical decision-making framework, the integration of ethical principles into AI systems, and the formulation of guiding legal policies. Based on an extensive analysis of existing AI ethics governance theories and technological research, this study presents an innovative conceptual framework rooted in dynamic feedback reinforcement learning theory. This pioneering framework, cultivated through the collaboration of multiple stakeholders, encompasses various dimensions encompassing law, technology, and market dynamics. Additionally, it establishes an AI ethics governance committee tasked with supervising the behavior of AI systems, guiding their acquisition of ethical principles, and adapting to the ever-evolving environment. The overarching objective of this collaborative, multi-faceted AI ethics governance framework is to serve as a reference point for global AI ethics governance mechanisms and to promote the sustainable development of the AI industry. By taking into account legal, technological, and market factors, our aim is to facilitate a harmonious interaction between technology, humanity, and society, ultimately paving the way for a healthy and inclusive intelligent society.