Increasing Accountability and Compliance with Robot Advice
This research paper explores how consumers comply with advice given by service robots in organizational frontlines, specifically in health and elderly care settings. Through six studies, including four field experiments, the authors demonstrate that consumers are significantly more likely to comply with robot advice when the robot attributes the advice to a human service provider rather than giving it on its own. This increase in compliance is driven by a heightened sense of accountability, which persists over time, though the compliance gap can also be attenuated when the robot embeds social cues in its advice.
Summary and content fields are drawn from the document text and are pending editorial review.
Who issued it
Who it governs
Researchers, AI developers, and service managers interested in human-robot interaction and improving consumer compliance with automated recommendations.
What the document contains
The document investigates human-robot interaction in service settings, exploring how the attribution of robot advice to human providers or the inclusion of social cues influences consumer compliance, mediated by social presence and accountability.
The text does not provide regulatory mandates, legal enforcement mechanisms, or formal policy guidelines for AI deployment.
- Consumers are more likely to comply with service robot advice when the advice is presented as coming from a human source rather than solely from the robot.
- The increased compliance is driven by a higher sense of accountability—the expectation of having to justify one's actions to others.
- Heightened adherence to robot advice invoking a human service provider persists over time and does not wear off across repeated interactions.
- Differences in accountability and compliance between robot-only advice and robot advice with a human source are attenuated when the robot embeds social cues in its advice.
- Embedding goal-oriented social cues in robot-only advice enhances the robot's perceived social presence, thereby increasing user accountability and compliance.
· Theoretical Framework and Hypotheses Development · Study 1: Field Studies · Study 2: Longitudinal Field Study · Study 3: Accountability as Underlying Process · Study 4: Social Cues · General Discussion
How it scores
Each score is backed by a quote verified against the document text. Editorial review has not yet confirmed them.
Accountability
4/5Clear responsibility for AI outcomes
Rooted primarily in social and organizational psychology, accountability is broadly defined as the implicit or explicit expectation that one may be called on to justify one's beliefs, feelings, and actions to others
Introduction
screening score · 2026-10-24
Fairness
0/5Non-discrimination and equitable treatment
N/A
screening score · 2026-10-24
Human Dignity
0/5Respect for the inherent worth of persons
N/A
screening score · 2026-10-24
Human Oversight
0/5Humans remain in control of consequential decisions
N/A
screening score · 2026-10-24
Privacy
0/5Protection of personal data and private life
N/A
screening score · 2026-10-24
Transparency
1/5Openness about how AI systems work and are used
By doing so, a robot shows that it can go beyond simple task execution in an if-then fashion and is able to meaningfully act
Theoretical Framework and Hypotheses Development
screening score · 2026-10-24
Enforcement
0/5Consequences and compliance mechanisms with real force
N/A
screening score · 2026-10-24
Impact Assessment
0/5Required assessment of an AI system's risks/impacts before or during use
N/A
screening score · 2026-10-24