Trust and Accountability in Autonomous Robotic Systems

Abstract

Trust and accountability in autonomous robotic systems are foundational requirements for socially beneficial deployment of robotics across healthcare, logistics, eldercare, manufacturing, and public infrastructure domains. Trust -- the human willingness to accept vulnerability to robotic system behaviour -- is both a prerequisite for adoption and a potential risk: inappropriate trust (over-reliance) is as ethically problematic as inappropriate distrust (under-utilisation). Accountability -- the institutional and technical mechanisms through which responsibility for robotic system harms is assigned, verified, and remedied -- is challenged by autonomous systems whose behaviour emerges from trained models rather than explicit programming, creating novel accountability gaps. This paper proposes the Robot Trust and Accountability Framework (RoTAF), a systematic analysis of five trust dimensions and four accountability mechanisms across six robotic deployment contexts: surgical robots, eldercare robots, autonomous warehouse systems, delivery drones, collaborative manufacturing robots, and autonomous emergency response robots. RoTAF introduces the Trust-Accountability Quality Score (TAQS) and evaluates current governance adequacy across all six contexts. Key results: eldercare robots achieve the lowest TAQS (0.484) due to emotional dependency risk and dignity concerns; surgical robots achieve the highest TAQS (0.724) driven by strong medical accountability frameworks; over-trust is the most prevalent trust pathology across all contexts. The framework provides trust calibration and accountability design guidance.