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Defining ‘robotics’ for legal responsibility: A conceptual framework

Journal: RUDN Journal of Law (Vol.29, No. 2)

Publication Date:

Authors : ; ; ;

Page : 509-523

Keywords : robot; robotics; responsibility; artificial intelligence; autonomy; self-sufficiency; robotic device; machine learning; neural network;

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Abstract

Robotics offers significant potential, yet the absence of a universally accepted definition of the field and its components hinders the development of a clear conceptual model for legal liability. This study examines and analyzes the concepts, features, and key characteristics of “robotics” and “robot”, correlating them with the concept of “artificial intelligence”. It identifies problematic aspects of legal liability in the field of robotics to facilitate the development of a conceptual model of legal responsibility in this area. The research is based on the analysis of legal acts and scholarly literature. Methodology employed include system analysis, comparative legal analysis, formal legal analysis, and legal modeling, along with general scientific methods such as analysis, synthesis, induction, and deduction. The study compares various approaches to defining key concepts in robotics, particularly correlating “robot” and “artificial intelligence”. It highlights problematic aspects within the content of legal liability in robotics. The study argues that legal liability should differentiate between situations where harm is caused by an automated robot or robotic device and situations where harm occurs when a person collaborates with such a device. It concludes that legal responsibility in robotics should be differentiated based on the degree of autonomy (full or partial) and whether the robot performs the activity independently or in conjunction with a person. Given that artificial intelligence is currently created and managed by developers, it is essential to implement clear regulatory frameworks that define permissible and impermissible actions for developers and all stakeholders involved in the AI development process at every stage of its lifecycle.

Last modified: 2025-08-08 18:30:46