Computational Modeling of the Dynamics of Human Trust During Human-Machine Interactions

We developed an experiment to elicit human trust dynamics in human-machine interaction contexts and established a quantitative model of human trust behavior with respect to these contexts. The proposed model describes human trust level as a function of experience, cumulative trust, and expectation b...

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Published in:IEEE transactions on human-machine systems Vol. 49; no. 6; pp. 485 - 497
Main Authors: Hu, Wan-Lin, Akash, Kumar, Reid, Tahira, Jain, Neera
Format: Journal Article
Language:English
Published: New York IEEE 01.12.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Affective computing
Autonomous systems
Behavioral sciences
Cultural differences
Data models
Demographics
Dynamics
Experiments
False alarms
Human behavior
Human computer interaction
Human error
man–machine systems
Parameter estimation
Security management
Stability analysis
ISSN:2168-2291, 2168-2305
Online Access:Get full text
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Abstract We developed an experiment to elicit human trust dynamics in human-machine interaction contexts and established a quantitative model of human trust behavior with respect to these contexts. The proposed model describes human trust level as a function of experience, cumulative trust, and expectation bias. We estimated the model parameters using human subject data collected from two experiments. Experiment 1 was designed to excite human trust dynamics using multiple transitions in trust level. Five hundred and eighty-one individuals participated in this experiment. Experiment 2 was an augmentation of Experiment 1 designed to study and incorporate the effects of misses and false alarms in the general model. Three hundred and thirty-three individuals participated in Experiment 2. Beyond considering the dynamics of human trust in automation, this model also characterizes the effects of demographic factors on human trust. In particular, our results show that the effects of national culture and gender on trust are significant. For example, U.S. participants showed a lower trust level and were more sensitive to misses as compared with Indian participants. The resulting trust model is intended for the development of autonomous systems that can respond to changes in human trust level in real time.
AbstractList We developed an experiment to elicit human trust dynamics in human–machine interaction contexts and established a quantitative model of human trust behavior with respect to these contexts. The proposed model describes human trust level as a function of experience, cumulative trust, and expectation bias. We estimated the model parameters using human subject data collected from two experiments. Experiment 1 was designed to excite human trust dynamics using multiple transitions in trust level. Five hundred and eighty-one individuals participated in this experiment. Experiment 2 was an augmentation of Experiment 1 designed to study and incorporate the effects of misses and false alarms in the general model. Three hundred and thirty-three individuals participated in Experiment 2. Beyond considering the dynamics of human trust in automation, this model also characterizes the effects of demographic factors on human trust. In particular, our results show that the effects of national culture and gender on trust are significant. For example, U.S. participants showed a lower trust level and were more sensitive to misses as compared with Indian participants. The resulting trust model is intended for the development of autonomous systems that can respond to changes in human trust level in real time.
Author Reid, Tahira
Hu, Wan-Lin
Akash, Kumar
Jain, Neera
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  surname: Jain
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  organization: School of Mechanical Engineering, Purdue University, West Lafayette, IN, USA
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Snippet We developed an experiment to elicit human trust dynamics in human-machine interaction contexts and established a quantitative model of human trust behavior...
We developed an experiment to elicit human trust dynamics in human–machine interaction contexts and established a quantitative model of human trust behavior...
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SubjectTerms Affective computing
Autonomous systems
Behavioral sciences
Cultural differences
Data models
Demographics
Dynamics
Experiments
False alarms
Human behavior
Human computer interaction
Human error
man–machine systems
Parameter estimation
Security management
Stability analysis
Title Computational Modeling of the Dynamics of Human Trust During Human-Machine Interactions
URI https://ieeexplore.ieee.org/document/8502860
https://www.proquest.com/docview/2322762869
Volume 49
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