Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Stereotype Content Model02:16

Stereotype Content Model

14.8K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.8K
Fundamental Attribution Error01:14

Fundamental Attribution Error

13.1K
According to some social psychologists, people tend to overemphasize internal factors as explanations—or attributions—for the behavior of other people. They tend to assume that the behavior of another person is a trait of that person, and to underestimate the power of the situation on the behavior of others. They tend to fail to recognize when the behavior of another is due to situational variables, and thus to the person’s state. This erroneous assumption is...
13.1K
Bias01:22

Bias

4.8K
Bias refers to any tendency that prevents a question from being considered unprejudiced. In research, bias occurs when one outcome or answer is selected or encouraged over others in sampling or testing. Bias can occur during any research phase, including study design, data collection, analysis, and publication.
In statistics, a sampling bias is created when a sample is collected from a population, and some members of the population are not as likely to be chosen as others (remember, each member...
4.8K
Confirmation Biases01:31

Confirmation Biases

6.4K
The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
6.4K
Naturalistic Observations02:30

Naturalistic Observations

15.8K
If you want to understand how behavior occurs, one of the best ways to gain information is to simply observe the behavior in its natural context. However, people might change their behavior in unexpected ways if they know they are being observed. How do researchers obtain accurate information when people tend to hide their natural behavior? As an example, imagine that your professor asks everyone in your class to raise their hand if they always wash their hands after using the restroom. Chances...
15.8K
Stereotypes, Prejudice, and Discrimination02:55

Stereotypes, Prejudice, and Discrimination

91.1K
Humans are very diverse and although we share many similarities, we also have many differences. The social groups we belong to help form our identities (Tajfel, 1974). These differences may be difficult for some people to reconcile, which may lead to prejudice toward people who are different. Prejudice is a negative attitude and feeling toward an individual based solely on one’s membership in a particular social group (Allport, 1954; Brown, 2010). Prejudice is common against people who...
91.1K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

"Are you sure about that?" The effects of calibrated classification model task accuracy and confidence on trustworthiness, trust, and performance.

Applied ergonomics·2025
Same author

A cognitive task analysis of emergency aeromedical evacuation personnel to motivate appropriate decision support system design.

Military psychology : the official journal of the Division of Military Psychology, American Psychological Association·2025
Same author

A comparison of deep versus awake tracheal extubation in adults: a randomized controlled trial.

BMC anesthesiology·2025
Same author

Affinity selection-mass spectrometry with linearizable macrocyclic peptide libraries.

Science advances·2025
Same author

pyBinder: Quantitation to Advance Affinity Selection-Mass Spectrometry.

Analytical chemistry·2025
Same author

Examining the human-centred challenges of human-swarm interaction.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences·2025

Related Experiment Video

Updated: Aug 31, 2025

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

17.4K

Differential biases in human-human versus human-robot interactions.

Gene M Alarcon1, August Capiola1, Izz Aldin Hamdan2

  • 1Air Force Research Laboratory, United States.

Applied Ergonomics
|August 22, 2022
PubMed
Summary

Humans show biases toward robots across trustworthiness perceptions, but not in trust behaviors. These findings suggest human-robot trust is more complex than previously understood, impacting human-robot interaction (HRI) research.

More Related Videos

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
11:01

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

Published on: November 24, 2015

13.2K
One Dimensional Turing-Like Handshake Test for Motor Intelligence
14:05

One Dimensional Turing-Like Handshake Test for Motor Intelligence

Published on: December 15, 2010

27.5K

Related Experiment Videos

Last Updated: Aug 31, 2025

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues
07:34

Perceptual and Category Processing of the Uncanny Valley Hypothesis' Dimension of Human Likeness: Some Methodological Issues

Published on: June 3, 2013

17.4K
SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
11:01

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

Published on: November 24, 2015

13.2K
One Dimensional Turing-Like Handshake Test for Motor Intelligence
14:05

One Dimensional Turing-Like Handshake Test for Motor Intelligence

Published on: December 15, 2010

27.5K

Area of Science:

  • Human-Robot Interaction
  • Social Psychology
  • Trust Dynamics

Background:

  • Human-robot interaction research suggests unique trust differences compared to human-human interactions.
  • Previous studies primarily focused on performance degradation as a key differentiator.
  • Trust is multifaceted, encompassing perceptions of ability, benevolence, and integrity.

Purpose of the Study:

  • To investigate differences in human-robot versus human-human trust.
  • To examine the impact of performance, consideration, and morality manipulations on trust.
  • To explore how these manipulations affect trust perceptions, intentions, and behaviors.

Main Methods:

  • A mixed factorial hierarchical linear model was employed.
  • Participants engaged in a trust game involving human and robot partners.
  • Trustworthiness was manipulated across performance, consideration, and morality dimensions.

Main Results:

  • Significant partner differences (human vs. robot) were observed in all trustworthiness perceptions.
  • Biases towards robots were more extensive than anticipated.
  • No significant differences were found in trust behaviors between human and robot partners, despite marginal effects on trust intentions.

Conclusions:

  • Human biases towards robots extend beyond performance and are complex.
  • Perceptual biases do not necessarily translate into behavioral differences in trust games.
  • Findings challenge existing models of human-robot trust and suggest a need for more nuanced research.