The Role of Perceived Moral Agency of a Humanoid Robot on the Willingness to Self-Disclose, Trustworthiness, Goodwill, and Liking

Abstract Little is known about how a robot’s moral behavior shapes robot perception and behavioral intentions toward robots. In a series of four experiments, we investigated the influence of immoral versus moral behavior of a robot on this robot’s perceived trustworthiness, goodwill, likeability, and willingness to self-disclose toward it. To do so, a robot was depicted as either cheating a human (Experiment 1–2) or exerting physical harm against a human (Experiment 3–4). Moral behavior of the robot was manipulated either through short videos or text vignettes. In Experiment 2–4, we examined mind perception of the robot and the preferred length of a future conversation with it. As hypothesized, in all experiments the immoral robot was perceived as less trustworthy and as possessing less goodwill. In three experiments, the immoral robot was also liked less. Only in Experiment 4 - which used videos that displayed a robot physically harming a human – participants reported less willingness to self-disclose toward that robot. In none of the experiments, moral behavior of a robot influenced mind perception. The preferred conversation time was not affected by the type of behavior shown by the robot. These inconsistent results might be due to the severity of the harm caused and the operationalization of a robot’s moral behavior. The present findings demonstrate that immoral robot behavior results in negative evaluations of robots which go beyond mere judgments of robot morality.

Authors

Institutions

Publication Details

Journal
International Journal of Social Robotics
Published
2026-05-29
DOI
https://doi.org/10.1007/s12369-026-01405-y
Primary Topic
Social Robot Interaction and HRI
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The Role of Perceived Moral Agency of a Humanoid Robot on the Willingness to Self-Disclose, Trustworthiness, Goodwill, and Liking

Friederike Eyssel, Angelika Augustine
International Journal of Social Robotics
Social Robot Interaction and HRI
article

The Role of Perceived Moral Agency of a Humanoid Robot on the Willingness to Self-Disclose, Trustworthiness, Goodwill, and Liking

Friederike Eyssel, Angelika Augustine
article en

Abstract

Abstract Little is known about how a robot’s moral behavior shapes robot perception and behavioral intentions toward robots. In a series of four experiments, we investigated the influence of immoral versus moral behavior of a robot on this robot’s perceived trustworthiness, goodwill, likeability, and willingness to self-disclose toward it. To do so, a robot was depicted as either cheating a human (Experiment 1–2) or exerting physical harm against a human (Experiment 3–4). Moral behavior of the robot was manipulated either through short videos or text vignettes. In Experiment 2–4, we examined mind perception of the robot and the preferred length of a future conversation with it. As hypothesized, in all experiments the immoral robot was perceived as less trustworthy and as possessing less goodwill. In three experiments, the immoral robot was also liked less. Only in Experiment 4 - which used videos that displayed a robot physically harming a human – participants reported less willingness to self-disclose toward that robot. In none of the experiments, moral behavior of a robot influenced mind perception. The preferred conversation time was not affected by the type of behavior shown by the robot. These inconsistent results might be due to the severity of the harm caused and the operationalization of a robot’s moral behavior. The present findings demonstrate that immoral robot behavior results in negative evaluations of robots which go beyond mere judgments of robot morality.

International Journal of Social RoboticsVol. 18(5)
Bielefeld University (DE)
Universität Bielefeld
Peace, Justice and strong institutions
Openalex Percentile: Top 4%
Social Robot Interaction and HRI
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.