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Related Experiment Video

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Reciprocity in computer-human interaction: source-based, norm-based, and affect-based explanations.

Seungcheol Austin Lee¹, Yuhua Jake Liang

¹1 Department of Communication, Northern Kentucky University , Highland Heights, Kentucky.

Cyberpsychology, Behavior and Social Networking

|March 25, 2015

Summary

People treat computers socially, a phenomenon called the Computers Are Social Actors (CASA) effect. This study found that reciprocity, a norm-based influence, increased compliance with computer requests, not source evaluations.

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Area of Science:

Human-Computer Interaction
Social Psychology
Cognitive Science

Background:

The Computers Are Social Actors (CASA) effect describes the tendency for individuals to apply social rules and expectations when interacting with computers.
Understanding the psychological mechanisms behind CASA is crucial for designing more effective human-computer interactions.
Previous research suggests factors like source evaluations, normative influence, and affective states influence compliance.

Purpose of the Study:

To investigate the influence of source evaluations (competence, warmth), normative influence (reciprocity), and affective influence (mood) on human compliance with computer agents.
To determine which of these factors significantly predict compliance within the CASA framework.
To build and test a structural equation model explaining compliance with computer requests.

Main Methods:

Utilized computer agents to solicit human compliance on a pattern recognition task.
Employed structural equation modeling to analyze the relationships between key influencing factors and compliance.
Measured perceived competence, warmth, reciprocity, and mood as independent variables.

Main Results:

Norm-based influence, specifically reciprocity, was found to significantly increase the likelihood of human compliance with computer requests.
Evaluations toward the computer agent, including perceived competence and warmth, did not show a significant impact on compliance.
Affective influence (mood) was not explicitly detailed as a significant factor in the final model.

Conclusions:

Reciprocity emerges as a key driver of compliance in human-computer interactions, aligning with social norms.
Source credibility and affective states appear less influential than social norms in eliciting compliance from computer agents.
Findings suggest focusing on leveraging social norms, like reciprocity, may be more effective for increasing compliance in human-computer interaction design.