A Storytelling Robot managing Persuasive and Ethical Stances via ACT-R: an Exploratory Study
This study presents a storytelling social robot controlled via the ACT-R cognitive architecture that utilizes persuasive techniques and ethical stances to converse about COVID-19 rules and vaccines. The model integrates a needs-driven approach and cognitive theories to evaluate dialogue management, storytelling strategies, and argumentative techniques. An exploratory evaluation involving 63 participants assessed the effectiveness of these persuasive strategies and ethical settings.
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Who issued it
Who it governs
Researchers and developers in human-robot interaction and AI ethics looking to understand cognitive models for persuasive social robots.
What the document contains
The document covers the design, implementation, and exploratory evaluation of a cognitive architecture-based robot model that employs storytelling, persuasion techniques, and ethical stances during conversations about COVID-19 rules and vaccines.
The text does not provide legal frameworks, regulatory enforcement mechanisms, or formal compliance guidelines for deploying persuasive robots outside of experimental settings.
- The paper introduces a storytelling social robot model controlled via the ACT-R cognitive architecture to manage persuasive and ethical stances.
- The system integrates psychological theories like the Elaboration Likelihood Model and dual process theories of reasoning into dialogue management.
- An exploratory evaluation with 63 participants demonstrated that framing and ad verecundiam arguments had measurable persuasive effects on skeptical users.
- The combination of a storytelling strategy and an open-minded ethical stance significantly helped users re-evaluate their original beliefs.
· 1 Introduction · 2 Related Works · 3 Agent’s Cognitive Model · 4 Implementation details and an example of interaction · 5 Exploratory Evaluation · 6 Discussions and Future Works
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
0/5Clear responsibility for AI outcomes
screening score · 2026-10-24
Fairness
0/5Non-discrimination and equitable treatment
screening score · 2026-10-24
Human Dignity
0/5Respect for the inherent worth of persons
screening score · 2026-10-24
Human Oversight
0/5Humans remain in control of consequential decisions
screening score · 2026-10-24
Privacy
0/5Protection of personal data and private life
screening score · 2026-10-24
Transparency
0/5Openness about how AI systems work and are used
screening score · 2026-10-24
Enforcement
0/5Consequences and compliance mechanisms with real force
screening score · 2026-10-24
Impact Assessment
3/5Required assessment of an AI system's risks/impacts before or during use
The paper presents the results of an exploratory evaluation of the system on 63 participants.
ABSTRACT
screening score · 2026-10-24