Beyond Tools and Persons: Who Are They? Classifying Robots and AI Agents for Proportional Governance

TL;DR

This paper introduces a new classification framework for autonomous systems based on their integration across physical, social, and cognitive dimensions, aiming to inform proportional governance and regulatory standards.

Contribution

It proposes a novel CPST-based taxonomy and assessment protocol for classifying AI and robotic entities to guide governance and legal responsibilities.

Findings

Developed a three-tier taxonomy: Confined Actors, Socially-Aware Interactors, CPST-Integrated Agents.

Identified standardized metrics for assessing entities across four CPST dimensions.

Outlined policy steps for international adoption before the 2027 EU AI Act review.

Abstract

The rapid commercialization of humanoid robots and generative AI agents is outpacing legal frameworks built on a binary distinction between ``tools'' and ``persons.'' Current regulations, including the EU AI Act, classify systems by risk level but lack a foundational ontology for determining \emph{what kind of entity} an autonomous system is -- and what governance follows from that determination. We propose a classification framework grounded in Cyber-Physical-Social-Thinking (CPST) space theory, which categorizes autonomous entities by their degree of integration across four interconnected dimensions: computational, embodied, relational, and cognitive. The resulting three-tier taxonomy -- Confined Actors, Socially-Aware Interactors, and CPST-Integrated Agents -- provides principled scaffolding for proportional governance: enhanced product liability for isolated systems, relational duties of care for interactive companions, and qualified legal personhood for deeply integrated agents. We operationalize this taxonomy by identifying standardized assessment metrics drawn from robotics, human--robot interaction research, social computing, and cognitive science, and we propose a composite assessment protocol for regulatory use. We further address temporal dynamics -- how entities transition between categories as they evolve -- and the institutional design necessary for credible classification. We call for international standardization of this taxonomy before the 2027 review of the EU AI Act, and outline three concrete policy steps toward implementation.