Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 May 24:9:733504.
doi: 10.3389/frobt.2022.733504. eCollection 2022.

A Compliance-Reactance Framework for Evaluating Human-Robot Interaction

Annika Boos  1 , Olivia Herzog  1 , Jakob Reinhardt  1 , Klaus Bengler  1 , Markus Zimmermann  2
Affiliations

A Compliance-Reactance Framework for Evaluating Human-Robot Interaction

Annika Boos et al. Front Robot AI. .

Abstract

When do we follow requests and recommendations and which ones do we choose not to comply with? This publication combines definitions of compliance and reactance as behaviours and as affective processes in one model for application to human-robot interaction. The framework comprises three steps: human perception, comprehension, and selection of an action following a cue given by a robot. The paper outlines the application of the model in different study settings such as controlled experiments that allow for the assessment of cognition as well as observational field studies that lack this possibility. Guidance for defining and measuring compliance and reactance is outlined and strategies for improving robot behaviour are derived for each step in the process model. Design recommendations for each step are condensed into three principles on information economy, adequacy, and transparency. In summary, we suggest that in order to maximise the probability of compliance with a cue and to avoid reactance, interaction designers should aim for a high probability of perception, a high probability of comprehension and prevent negative affect. Finally, an example application is presented that uses existing data from a laboratory experiment in combination with data collected in an online survey to outline how the model can be applied to evaluate a new technology or interaction strategy using the concepts of compliance and reactance as behaviours and affective constructs.

Keywords: compliance; human-robot interaction; reactance; robotics; trust.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Process model of compliance and reactance as actions following the perception and cognition of a given cue.
FIGURE 2
FIGURE 2
Structural probability tree diagram depicting the compliance–reactance framework, as proposed in this paper.
FIGURE 3
FIGURE 3
Probability tree for context A: human and robot with similar task urgency, corresponding to a difference in task urgency of zero.
FIGURE 4
FIGURE 4
Probability tree for context B: the robot is assigned a task that is perceived as marginally more urgent than that of the participant, corresponding to a difference in task urgency of one.
See this image and copyright information in PMC

References

    1. Agnihotri R., Gaur S. (2016). Robotics: A New Paradigm in Geriatric Healthcare. Gerontechnology 15, 146–161. 10.4017/gt.2016.15.3.004.00 - DOI
    1. Axelrod R., Hamilton W. D. (1981). The Evolution of Cooperation. science 211, 1390–1396. 10.1126/science.7466396 - DOI - PubMed
    1. Babel F., Kraus J. M., Baumann M. (2020). Development and Testing of Psychological Conflict Resolution Strategies for Assertive Robots to Resolve Human-Robot Goal Conflict. Front. Robot. AI 7, 591448. 10.3389/frobt.2020.591448 - DOI - PMC - PubMed
    1. Backhaus N., Rosen P. H., Scheidig A., Gross H.-M., Wischniewski S. (2018). “Somebody Help Me, Please?!” Interaction Design Framework for Needy Mobile Service Robots,” in 2018 IEEE Workshop on Advanced Robotics and its Social Impacts (ARSO) (Genova, Italy: IEEE; ), 54–61.
    1. Bartneck C., Nomura T., Kanda T., Suzuki T., Kennsuke K. (2005). “A Cross-Cultural Study on Attitudes towards Robots,” in Proceedings of the HCI International, Las Vegas (Mahwah: Lawrence Erlbaum Associates; ).

LinkOut - more resources