Author(s)

Tianran Liu ¹

Affiliation(s)

¹ Qinghai Minzu University, Xining, Qinghai, 810007, China

Corresponding Author

Tianran Liu

ABSTRACT

This paper examines the complex legal and administrative challenges surrounding responsibility attribution for autonomous systems, focusing on the intersection of administrative law principles and artificial intelligence governance frameworks. Through comprehensive analysis of current legal frameworks, comparative study of international approaches, and examination of practical implementation requirements, this research addresses the growing need for effective governance mechanisms in autonomous system deployment. The study identifies significant gaps in traditional responsibility attribution frameworks and proposes a multi-level governance model that balances innovation with accountability. The research methodology combines theoretical analysis with practical implementation considerations, drawing from international best practices and emerging regulatory approaches. Findings indicate that successful governance requires a layered approach to responsibility attribution, incorporating clear technical standards, robust monitoring mechanisms, and flexible adaptation capabilities. The proposed framework contributes to both theoretical understanding and practical implementation of autonomous system governance, offering structured approaches for addressing current challenges while maintaining adaptability for future technological advancement. This research has significant implications for policymakers, administrators, and legal practitioners involved in autonomous system deployment and oversight.

KEYWORDS

Legal responsibility; Administrative law; Artificial intelligence governance; Risk management

CITE THIS PAPER

Tianran Liu. Research on Legal Responsibility Attribution for Autonomous Systems: An AI Governance Perspective. Science of Law Journal (2024) Vol. 3: 166-174. DOI: http://dx.doi.org/DOI: 10.23977/law.2024.030722.

REFERENCES

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