Background and research questions
Rapid advances in AI, particularly large-scale, autonomous, and generative systems, have intensified concerns over ethical risks, loss of control, and the inadequacy of existing governance frameworks. As AI systems increasingly operate across domains, jurisdictions, and social contexts, traditional regulatory approaches struggle to address extreme risks, value conflicts, and distributed responsibility. This raises fundamental questions about how AI risks should be conceptualized, governed, and aligned with societal values under conditions of uncertainty and rapid technological change.
Core research areas
Extreme AI risks and safety governance
Research in this area examines the risks associated with high-impact, potentially uncontrollable AI systems, including the lack of human oversight and unintended autonomous behavior. It explores governance approaches for managing extreme risks, safety investment incentives, and the role of international scientific consensus in defining safety thresholds and red lines.
Ethical frameworks for generative AI
From both the philosophical perspectives of technology and ethics, this research analyzes the value-laden nature of generative AI systems and the distribution of ethical responsibility among multiple actors, including developers, deployers, users, and regulators. It develops typological frameworks for AI ethical risks to support structured ethical assessment and policy design.
Agile governance for AI systems
This research focuses on governance models that can adapt to rapidly evolving AI technologies. It investigates agile governance approaches that emphasize institutional flexibility, multi-stakeholder coordination, scenario-based governance, and layered regulatory mechanisms across various governance objects and contexts.
Research outputs
Research in this area has contributed to international academic and policy debates on AI safety and ethics, including peer-reviewed publications on extreme AI risks and structured analytical frameworks for AI ethical governance. These outputs inform both domestic and international discussions on responsible AI development.
Projects
Research on the AI Governance Framework and Implementation Method
Research on AI Governance Evaluation System
Algorithm Optimization and Social Governance
