Human-Centred Autonomy: Designing Robots and Intelligent Machines That Work With People

Abstract

Autonomous and intelligent systems increasingly work alongside people in factories, vehicles, healthcare environments, service settings, and decision-support contexts. Their success, however, should not be defined by the extent to which human involvement can be eliminated. Highly autonomous systems may perform individual functions accurately while still producing poor operational outcomes when users misunderstand system capabilities, lose situational awareness, become over-reliant, cannot intervene effectively, or experience excessive cognitive workload. This editorial argues that successful autonomy should be evaluated through the quality of human–machine collaboration rather than maximum machine independence. Human-centred autonomy requires coordinated attention to trust calibration, shared control, situation awareness, cognitive ergonomics, explainability, communication, safe transfer of authority, inclusive design, training, and organizational responsibility. Current evidence also demonstrates that explanations, anthropomorphic interfaces, and greater automation do not automatically improve collaboration. Research should therefore prioritize standardized human-autonomy evaluation, longitudinal trust studies, adaptive and multimodal interfaces, safe control transitions, representative end-user testing, and interdisciplinary validation. Autonomous systems should ultimately augment human capability while preserving meaningful understanding, agency, intervention, and responsibility.