Journal ArticleDOI
Extending the Technology Acceptance Model to assess automation
TLDR
The Automation Acceptance Model (AAM) is proposed to draw upon the IS and CE perspectives and take into account the dynamic and multi-level nature of automation use, highlighting the influence of use on attitudes that complements the more common view that attitudes influence use.Abstract:
Often joint human–automation performance depends on the factors influencing the operator’s tendency to rely on and comply with automation Although cognitive engineering (CE) researchers have studied automation acceptance as related to task–technology compatibility and human–technology coagency, information system (IS) researchers have evaluated user acceptance of technology, using the Technology Acceptance Model (TAM) The parallels between the two views suggest that the user acceptance perspective from the IS community can complement the human–automation interaction perspective from the CE community TAM defines constructs that govern acceptance and provides a framework for evaluating a broad range of factors influencing technology acceptance and reliance TAM is extensively used by IS researchers in various applications and it can be applied to assess the effect of trust and other factors on automation acceptance Likewise, extensions to the TAM framework use the constructs of task–technology compatibility and past experience to extend its description of the role of human–automation interaction in automation adoption We propose the Automation Acceptance Model (AAM) to draw upon the IS and CE perspectives and take into account the dynamic and multi-level nature of automation use, highlighting the influence of use on attitudes that complements the more common view that attitudes influence useread more
Citations
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Journal ArticleDOI
Human Trust in Artificial Intelligence: Review of Empirical Research
TL;DR: A new generation of technologies capable of interacting with the environment and aiming to simulate human intelligence, and the success of integrating AI into these technologies is being studied.
Journal ArticleDOI
Applied artificial intelligence and trust—The case of autonomous vehicles and medical assistance devices
TL;DR: This study illustrates the dichotomous constitution of trust in applied AI and provides tangible approaches to increase trust in the technology and illustrates the necessity of a democratic development process for applied AI.
Journal ArticleDOI
The roles of initial trust and perceived risk in public’s acceptance of automated vehicles
TL;DR: In this paper, a theoretical acceptance model was proposed by extending TAM with new constructs: initial trust and two types of perceived risk (i.e., perceived safety risk [PSR] and perceived privacy risk [PPR]).
Journal ArticleDOI
What drives people to accept automated vehicles? Findings from a field experiment
TL;DR: In this paper, the influence of direct experience of an automated vehicle (AV, Level 3) and explaining and predicting public acceptance of AVs through a psychological model was analyzed. But the authors considered the last two determinants, namely perceived usefulness (PU), perceived ease of use (PEU), trust related to SDVs, and perceived safety (PS) while riding in our AV.
Journal ArticleDOI
Introduction matters: Manipulating trust in automation and reliance in automated driving.
TL;DR: The results demonstrate that the individual trust level influences how much drivers monitor the environment while performing an NDRT and introductory information influences this trust level, reliance on an automated driving system, and if a critical take-over situation can be successfully solved.
References
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TL;DR: Ajzen, 1985, 1987, this article reviewed the theory of planned behavior and some unresolved issues and concluded that the theory is well supported by empirical evidence and that intention to perform behaviors of different kinds can be predicted with high accuracy from attitudes toward the behavior, subjective norms, and perceived behavioral control; and these intentions, together with perceptions of behavioral control, account for considerable variance in actual behavior.
Perceived Usefulness, Perceived Ease of Use, and User
TL;DR: Regression analyses suggest that perceived ease of use may actually be a causal antecdent to perceived usefulness, as opposed to a parallel, direct determinant of system usage.
Journal ArticleDOI
Perceived usefulness, perceived ease of use, and user acceptance of information technology
TL;DR: In this article, the authors developed and validated new scales for two specific variables, perceived usefulness and perceived ease of use, which are hypothesized to be fundamental determinants of user acceptance.
Book
Diffusion of Innovations
TL;DR: A history of diffusion research can be found in this paper, where the authors present a glossary of developments in the field of Diffusion research and discuss the consequences of these developments.