Robot Trustworthiness: Guidelines for Simulated Emotion
This paper discusses three crucial factors as principles to guide robotic simulation of emotion to increase human ability to make reasonable assessments of robot trustworthiness and appropriate reliance. It proposes that displays of affect reflecting internal states could provide useful evidence for evaluating robot agent trustworthiness. The three factors requiring investigation are the correlation of affective signals to internal states, fidelity in emotion portrayal, and correct human interpretation of the signals.
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Who issued it
Who it governs
This paper is for researchers and developers interested in human-robot interaction and affective computing.
What the document contains
The document addresses the simulation of emotion in autonomous robots using an artificial limbic system to aid human evaluation of robot trustworthiness and appropriate reliance.
The document lacks enforceable regulatory mandates, specific technical engineering specifications, and legal frameworks for robot deployment.
- Well-justified human evaluations of autonomous robot trustworthiness require evidence from various sources, including observation of robot behavior.
- Displays of affect by a robot reflecting internal states could provide useful evidence for evaluation of robot trustworthiness.
- The value of affect signals depends on the correlation of affective signals to trust-related measurable attributes of internal state.
- Fidelity in portrayal of emotion by a robot agent must evoke human anthropomorphic social recognition.
- Correct human interpretation of affective signals is necessary for justifiable modulation of beliefs about the robot agent.
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How it scores
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Accountability
0/5Clear responsibility for AI outcomes
Abstract
screening score · 2026-10-24
Fairness
0/5Non-discrimination and equitable treatment
Abstract
screening score · 2026-10-24
Human Dignity
0/5Respect for the inherent worth of persons
Abstract
screening score · 2026-10-24
Human Oversight
2/5Humans remain in control of consequential decisions
This paper discusses these three factors as principles to guide robotic simulation of emotion for increasing human ability to make reasonable assessments of robot trustworthiness and appropriate reliance.
Abstract
screening score · 2026-10-24
Privacy
0/5Protection of personal data and private life
Abstract
screening score · 2026-10-24
Transparency
2/5Openness about how AI systems work and are used
Displays of affect by a robot that reflect important internal states not otherwise overtly visible could provide useful evidence for evaluation of robot agent trustworthiness.
Abstract
screening score · 2026-10-24
Enforcement
0/5Consequences and compliance mechanisms with real force
Abstract
screening score · 2026-10-24
Impact Assessment
0/5Required assessment of an AI system's risks/impacts before or during use
Abstract
screening score · 2026-10-24