Toward Trustworthy Physical AI for Human Interaction

2026-10-05

AI Summary

This study addresses the absence of systematic trustworthiness criteria for robots operating within human environments. To bridge this gap, we propose a cross-level framework that integrates safety, behavioral interpretability, and perceptual alignment, unifying the physical, control, and cognitive layers. By synthesizing multimodal interaction modeling, embodied intelligence control, and cognitive psychology techniques, the proposed approach dynamically aligns physical AI capabilities with user expectations. The primary contribution of this work lies in establishing, for the first time, a trust emergence mechanism for dynamic human–robot interaction alongside a comprehensive trustworthiness evaluation system for physical AI. This framework significantly enhances user acceptance in collaborative scenarios, offering a principled foundation for deploying trustworthy robotic systems in shared human spaces.

Abstract

Robots are entering human spaces faster than we can establish when they deserve trust. We propose a framework for trustworthy physical AI that integrates Safety, Behavioral Intelligibility, and Perceptual Alignment across embodiment, control, cognition, and design. Trustworthiness emerges from aligning physical capabilities, observable behavior, and expectations people form during interaction.

Problem

• Trustworthy AI
• Physical AI
• Human-Robot Interaction
• Trust

Innovation

• Trustworthy Physical AI
• Perceptual Alignment
• Behavioral Intelligibility
• Human-Robot Interaction
• Embodiment