EHAZOP: A Proof of Concept Ethical Hazard Analysis of an Assistive Robot
This paper presents EHAZOP, a method for conducting ethical hazard analyses on assistive robots by adapting collaborative safety engineering techniques. The authors describe a proof-of-concept case study applying EHAZOP to the Ari assistive robot across cognitive, social, and coaching functions. Results demonstrate that EHAZOP successfully identifies diverse ethical hazards, including novel concerns not captured in standard frameworks like BS8611.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Researchers, developers, and ethicists interested in practical methodologies for identifying and mitigating ethical hazards in assistive robotics.
What the document contains
The document introduces the EHAZOP methodology, detailing its guide words (More, Less, Early, Late, Opposite, In addition, Never) and how they apply to robot functions, characteristics, and autonomy. It covers a proof-of-concept case study evaluating an assistive robot's social and coaching functions, enumerating resulting ethical hazards and discussing the utility of the method.
The document does not provide a comprehensive, finalized regulatory framework or an exhaustive list of all possible ethical hazards for every category of robotic system.
- EHAZOP adapts safety engineering HAZOP techniques to identify ethical hazards in assistive robots through structured, facilitated discussions.
- A proof of concept study using the Ari assistive robot evaluated cognitive, social, and coaching functions using specific guide words.
- The method identified 21 distinct ethical hazard applications, including novel concerns such as erosion of confidence and lack of associative control.
- EHAZOP provides a collaborative and creative process suitable for gathering diverse stakeholder perspectives on robot ethics.
- Traceability between ethical hazards and associated scenarios is a valuable artifact of the EHAZOP process.
· I. Introduction · II. Existing Literature · III. EHAZOP Description and Methodology · IV. Proof of Concept Case Study · V. Results and Observations · VI. Discussion · VII. Conclusion and Future Work
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Human Dignity
2/5Respect for the inherent worth of persons
wider societal ethical impacts including culture flattening and compromise of human dignity.
Abstract
screening score · 2026-10-23
Privacy
2/5Protection of personal data and private life
(ethical hazard: lack of privacy ), a scenario where the user had not understood that Ari was monitoring them
Section V-A
screening score · 2026-10-23
Enforcement
0/5Consequences and compliance mechanisms with real force
screening score · 2026-10-23
Impact Assessment
4/5Required assessment of an AI system's risks/impacts before or during use
This paper presents EHAZOP, a method for conducting an ethical hazard analysis on an assistive robot.
Abstract
screening score · 2026-10-23