X-HAZOP: A Family of Techniques For Ethical Hazard Analysis of Assistive Robots
This paper presents X-HAZOP, a family of participatory design techniques for conducting ethical hazard analysis on assistive robots. The methodology combines CHAZOP (creative hazard analysis), which uses guide words to create accessible narrative texts describing the robot, and EHAZOP (ethical hazard analysis), which uses those narratives to identify potential ethical harms in collaborative workshops. The authors validate the approach through preliminary workshops with writers and students, demonstrating that the techniques help foster inclusive stakeholder participation and uncover novel ethical hazards.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
This paper is for robotics researchers, developers, and ethicists seeking structured and inclusive methods to identify ethical risks in assistive technologies.
What the document contains
The document covers the definition and application of the X-HAZOP methodology, specifically detailing CHAZOP for generating accessible narrative texts and EHAZOP for identifying ethical hazards using pre-defined guide words. It discusses findings from validation workshops involving professional writers and secondary students evaluating social assistive robots.
The document does not provide a comprehensive automated software tool for executing these workshops, nor does it cover industrial or safety-critical non-assistive robotics in depth.
- X-HAZOP provides a structured framework combining creative narrative generation and ethical hazard analysis for assistive robots.
- CHAZOP helps make robotic systems understandable to non-technical stakeholders through accessible narrative descriptions.
- EHAZOP uses guide-word prompts in collaborative workshops to systematically identify ethical hazards.
- Preliminary validation workshops demonstrate that these techniques help uncover both standard and novel ethical risks, such as cultural flattening and erosion of confidence.
- The collaborative nature of the workshops fosters teamwork and improves inclusivity by engaging traditionally marginalised demographics.
· I. Introduction · II. Literature Review · III. EHAZOP and CHAZOP · IV. Validation Workshops · V. Discussion and Analysis · VI. Conclusion
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
1/5Clear responsibility for AI outcomes
Existing work on the ethics of robots and AI systems [2]–[4] describe the ethical properties which are desirable for these systems, including fairness, transparency, freedom from bias and preservation of privacy.
II. LITERATURE REVIEW
screening score · 2026-10-23
Privacy
2/5Protection of personal data and private life
All Lack of privacy The user’s privacy is compromised by the robot’s monitoring
TABLE IV
screening score · 2026-10-23
Transparency
1/5Openness about how AI systems work and are used
Existing work on the ethics of robots and AI systems [2]–[4] describe the ethical properties which are desirable for these systems, including fairness, transparency, freedom from bias and preservation of privacy.
II. LITERATURE REVIEW
screening score · 2026-10-23
Enforcement
0/5Consequences and compliance mechanisms with real force
IV. VALIDATION WORKSHOPS
screening score · 2026-10-23
Impact Assessment
4/5Required assessment of an AI system's risks/impacts before or during use
This paper presents X-HAZOP, a family or toolbox of techniques for conducting ethical hazard analysis of an assistive robot by utilising structured, facilitated workshops.
Abstract
screening score · 2026-10-23