Trust and Accountability in Autonomous Robotic Systems
This paper proposes the Robot Trust and Accountability Framework (RoTAF) to systematically analyze trust dimensions and accountability mechanisms across six robotic deployment contexts: surgical robots, eldercare robots, autonomous warehouse systems, delivery drones, collaborative manufacturing robots, and autonomous emergency response robots. It introduces the Trust-Accountability Quality Score (TAQS) to evaluate current governance adequacy, finding that eldercare robots have the lowest score and surgical robots the highest. The research highlights over-trust as the most prevalent trust pathology and provides trust calibration and accountability design guidance.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Researchers, robotics developers, and policymakers looking for a structured evaluation framework for trust and accountability in autonomous robotic systems.
What the document contains
The paper covers the Robot Trust and Accountability Framework (RoTAF), the Trust-Accountability Quality Score (TAQS) metric, an evaluation of five trust dimensions and four accountability mechanisms across six robotic deployment contexts, and an analysis of trust pathologies like over-trust and under-trust.
The document does not provide binding legislation or legally enforceable regulatory mandates, as it is an academic research paper proposing a conceptual framework.
- RoTAF introduces a systematic analysis of five trust dimensions and four accountability mechanisms across six robotic deployment contexts.
- Surgical robots achieve the highest TAQS score of 0.724 driven by strong medical accountability frameworks.
- Eldercare robots achieve the lowest TAQS score of 0.484 due to emotional dependency risks and dignity concerns.
- Over-trust is identified as the most prevalent trust pathology across four of the six evaluated deployment contexts.
- The framework recommends pre-deployment trust calibration training and dedicated regulations for eldercare robotics.
· 1. Introduction · 2. Background: Trust and Accountability in Robotics · 3. The RoTAF Framework · 4. Results · 5. Discussion · 6. Conclusion
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
4/5Clear responsibility for AI outcomes
Accountability -- the institutional and technical mechanisms through which responsibility for robotic system harms is assigned, verified, and remedied
ABSTRACT
screening score · 2026-10-24
Fairness
2/5Non-discrimination and equitable treatment
Values alignment trust: the user's belief that the robot's behaviour reflects appropriate values -- particularly relevant when robots make trade-off decisions
2.1 Five Trust Dimensions and Trust Calibration
screening score · 2026-10-24
Human Dignity
4/5Respect for the inherent worth of persons
The dignity concern is two-dimensional: process dignity (being treated as a person rather than a process unit during robotic care interactions) and outcome dignity
5.1 Eldercare Robots: The Accountability and Dignity Governance Gap
screening score · 2026-10-24
Human Oversight
4/5Humans remain in control of consequential decisions
Professional accountability: human professional (surgeon, care worker) retains accountability for decisions made with robotic assistance; most appropriate where professional maintains meaningful human control
2.2 Four Accountability Mechanisms for Robotic Systems
screening score · 2026-10-24
Transparency
4/5Openness about how AI systems work and are used
Transparency trust: the user's ability to understand why the robot is doing what it does -- explainability for robotic systems; most critical for professional operators
2.1 Five Trust Dimensions and Trust Calibration
screening score · 2026-10-24
Enforcement
4/5Consequences and compliance mechanisms with real force
Product liability: manufacturer responsible for design defects; EU AI Liability Directive (2024) extends product liability to AI-enabled products
2.2 Four Accountability Mechanisms for Robotic Systems
screening score · 2026-10-24
Impact Assessment
4/5Required assessment of an AI system's risks/impacts before or during use
Certification and conformity assessment: pre-deployment safety verification (CE marking, FDA 510(k) for medical)
2.2 Four Accountability Mechanisms for Robotic Systems
screening score · 2026-10-24