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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Bibliographic Details
Published inIEEE 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
LanguageEnglish
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
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Summary: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.
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ISSN:2168-2291
2168-2305
DOI:10.1109/THMS.2018.2874188