Open AccessHuman, Hybrid, or Machine? Exploring the Trustworthiness of Voice-Based Assistants
Author(s) -
Lisa Weidmüller
Publication year - 2022
Publication title -
human machine communication journal/human-machine communication journal
Language(s) - English
Resource type - Journals
eISSN - 2638-6038
pISSN - 2638-602X
DOI - 10.30658/hmc.4.5
Subject(s) - trustworthiness , computer science , human–machine system , artificial intelligence , human resources , human–computer interaction , machine learning , psychology , data science , internet privacy , management , economics
This study investigates how people assess the trustworthiness of perceptually hybrid communicative technologies such as voice-based assistants (VBAs). VBAs are often perceived as hybrids between human and machine, which challenges previously distinct definitions of human and machine trustworthiness. Thus, this study explores how the two trustworthiness models can be combined in a hybrid trustworthiness model, which model (human, hybrid, or machine) is most applicable to examine VBA trustworthiness, and whether this differs between respondents with different levels of prior experience with VBAs. Results from two surveys revealed that, overall, the human model exhibited the best model fit; however, the hybrid model also showed acceptable model fit as prior experience increased. Findings are discussed considering the ongoing discourse to establish adequate measures for HMC research.