Human, Hybrid, or Machine? Exploring the Trustworthiness of Voice-Based Assistants

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Abstract

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.

Details

OriginalspracheEnglisch
Seiten (von - bis)85-110
Seitenumfang26
FachzeitschriftHuman-Machine Communication
Jahrgang4
Ausgabenummer1
PublikationsstatusVeröffentlicht - 2022
Peer-Review-StatusJa

Externe IDs

Mendeley 29226576-4dbd-3f03-a9bb-0a8d37a2c57b
unpaywall 10.30658/hmc.4.5
Scopus 85148019654

Schlagworte

Schlagwörter

  • trust, trustworthiness, hybrid, prior experience, scale, survey, voice-based assistant