Ethical Asymmetry in Human-Robot Interaction – An Empirical Test of Sparrow’s Hypothesis
This empirical study investigates Sparrow's ethical asymmetry hypothesis in human-robot interaction by testing whether humans are more inclined to condemn negative actions toward robots than to praise positive ones. Using an online questionnaire with manipulated moral permissibility and four cardinal virtue types, the research tests observer evaluations of human actors. The findings reveal a symmetrical, cubic relationship between perceived moral permissibility and perceived virtue scores, contradicting Sparrow's asymmetry hypothesis.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Researchers and ethicists studying human-robot interaction and moral psychology should read this to understand empirical perceptions of robot-directed behavior.
What the document contains
The document covers an empirical mixed-methods experiment examining human moral judgments of actions toward robots, specifically testing Sparrow's hypothesis of ethical asymmetry and adapting the Questionnaire on Cardinal Virtues.
It does not provide regulatory compliance guidelines, legal frameworks for robot rights, or enforceable governance policies.
- The study empirically tested Sparrow's ethical asymmetry hypothesis regarding human treatment of robots.
- Results showed no evidence of ethical asymmetry, as participants praised positive behaviors as much as they condemned negative ones.
- The relationship between perceived moral permissibility of action and perceived virtue scores was best described by a symmetrical cubic model.
- Factor analysis of the adapted Questionnaire on Cardinal Virtues revealed a single unified dimension rather than four distinct cardinal virtues.
- Participant judgments of human action toward robots appear to operate along a general good-bad behavior gradient rather than distinct virtue categories.
· Introduction · Virtue Ethics · Measurement tools development · Method · Results · Discussion · Conclusions
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
how institutions frame responsibility and care, and how designers intentionally or unintentionally script moral responses.
1 Introduction
screening score · 2026-10-23
Human Dignity
2/5Respect for the inherent worth of persons
The ethics of human-robot interaction (HRI) have been discussed extensively based on three traditional frameworks: deontology, consequentialism, and virtue ethics.
1 Introduction
screening score · 2026-10-23
Human Oversight
0/5Humans remain in control of consequential decisions
N/A
screening score · 2026-10-23
Privacy
0/5Protection of personal data and private life
N/A
screening score · 2026-10-23
Enforcement
0/5Consequences and compliance mechanisms with real force
N/A
screening score · 2026-10-23
Impact Assessment
1/5Required assessment of an AI system's risks/impacts before or during use
Prior to interpreting the main effects of the General Linear Model (GLM), the assumptions underlying the multivariate analysis were evaluated.
5.3 Manipulation check
screening score · 2026-10-23