Determinants that Are Believed to Influence the Acceptance and Adoption of Mission Critical Autonomous Systems

Matsuyama, Lisa; Zimmerman, Rileigh; Eaton, Casey; Weger, Kristin; Mesmer, Bryan; Tenhundfeld, Nathan L.; Bossuyt, Douglas L. Van; Semmens, Robert

doi:10.2514/6.2021-1156

Cited by 10 publications

(6 citation statements)

References 14 publications

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“…A possible explanation for this relationship may be that individuals who are over the age of 25 have less interest in exposure to AS technology in general. When examining these findings in light of our null results, users in both age groups may have an attitude of accepting a technology, but additional barriers and factors may be present when considering complete adoption (Matsuyama et al, 2021). For instance, this may manifest in the real world through the lack of clear tools and manuals available for actually adopting a technology effortlessly into daily routines.…”

Section: Discussionmentioning

confidence: 86%

“…For example, roadbased technologies could have different factors that predict the acceptance and adoption of air-based technologies. Future research could therefore benefit from exploring other types of AS given that different risks and safety considerations must be considered when dealing with any specific AS (e.g., Matsuyama et al, 2021). Despite these limitations, our study provides valuable insight into the nature of individual differences as they relate to the acceptance and adoption of technology.…”

Section: Discussionmentioning

confidence: 99%

“…While both acceptance and adoption are concerned with the users' sustained use of technology, acceptance is an attitude towards that technology (Davis, 1985). Research has found acceptance to be a deciding factor in the adoption of new technologies such that if a technology is available to be used, but the potential user does not accept it, then it may not be adopted (Davis, 1985;Matsuyama et al, 2021). Adoption is therefore a process that begins with the user becoming aware of the technology in question and finishes with the user utilizing it to its full capacity (Davis, 1985).…”

Section: Introductionmentioning

confidence: 99%

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Individual Differences in the Acceptance and Adoption of AI-enabled Autonomous Systems

Weger

Easley

Branham

et al. 2022

Proceedings of the Human Factors and Ergonomics Society Annual

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With the deployment of AI-enabled autonomous systems in various fields of application, it is critical to understand the factors affecting the acceptance and in turn the adoption of such technology. While previous research has established that individual differences have an impact on the acceptance and adoption of technology, little research has examined the extent and specificity of those individual differences. The current research attempts to address this gap in the literature by examining individual differences concerning the willingness to accept and adopt general technology versus specific AI-enabled autonomous systems. Our findings reveal several significant results between an individual’s personality traits of Openness, Emotionality, and Honesty-Humility, as well as age, gender, and career field with an individual’s level of acceptance and adoption of general versus specific AI-enabled AS technology. Our findings call for future research to further explore these individual differences in detail and to validate current technology models.

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Section: Discussionmentioning

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Individual Differences in the Acceptance and Adoption of AI-enabled Autonomous Systems

Weger

Easley

Branham

et al. 2022

Proceedings of the Human Factors and Ergonomics Society Annual

Self Cite

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“…Such mass trust die-offs have been seen in, for example, in government following the Watergate scandal (Keele, 2007), or in companies following CEO transgressions (Ferrin et al, 2018). These trust die-offs can have significant impacts on human behavior such as the use and adoption of these technologies (Matsuyama et al, 2021).…”

Section: Needs For Future Useful Measure Development For the Practiti...mentioning

confidence: 99%

Assessment of Trust in Automation in the “Real World”: Requirements for New Trust in Automation Measurement Techniques for Use by Practitioners

Tenhundfeld

Demir

Visser

2022

Journal of Cognitive Engineering and Decision Making

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Trust in automation is a foundational principle in Human Factors Engineering. An understanding of trust can help predict and alter much of human-machine interaction (HMI). However, despite the utility of assessing trust in automation in applied settings, there are inherent and unique challenges in trust assessment for those who seek to do so outside of the confines of the sterile lab environment. Because of these challenges, new approaches for trust in automation assessment need to be developed to best suit the unique demands of trust assessment in the real world. This paper lays out six requirements for these future measures: they should (1) be short, unobtrusive, and interaction-based, (2) be context-specific and adaptable, (3) be dynamic, (4) account for autonomy versus automation dependency, (5) account for task dependency, and (6) account for levels of risk. For the benefits of trust assessment to be realized in the “real world,” future research needs to leverage the existing body of literature on trust in automation while looking toward the needs of the practitioner.

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“…As such, failures in perpendicular parking could impact whether a user trusts the vehicle to drive itself on the highway. While these tasks are somewhat unrelated, this 'bleed-over' presents a potential real barrier to the adoption and acceptance of automation [58].…”

Section: Imperfect Automation May Have a Cost For Initial Adoption An...mentioning

confidence: 99%

Trust in Automated Parking Systems

Visser¹,

Phillips²,

Tenhundfeld³

et al. 2022

Preprint

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In two studies, we evaluated the trust and usefulness of automated compared to manual parking using an experimental paradigm and by surveying owners of vehicles with automated parking features. In Study 1, we compared participants' ability to manually park a Tesla Model X and use the Autopark feature to complete perpendicular and parallel parking maneuvers. We investigated differences in parking success and duration, intervention behavior, self-reported levels of trust in and workload associated with the automation, as well as eye and head movements related to monitoring the automation. We found higher levels of trust in the automated parallel parking maneuvers compared to perpendicular parking. The Tesla’s automated perpendicular parking was found to be less efficient than manually executing this maneuver. Study 2 investigated the frequency with which owners of vehicles with automated parking features used those features and probed why they chose not to use them. Vehicle owners reported using their vehicle's autonomous parking features in ways consistent with the empirical findings from Study 1: higher usage rates of autonomous parallel parking. The results from both studies revealed that 1) automated parking is error-prone, 2) drivers nonetheless have calibrated trust in the automated parking system, and 3) the benefits of automated parallel parking surpass those of automated perpendicular parking with the current state of the technology.

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Determinants that Are Believed to Influence the Acceptance and Adoption of Mission Critical Autonomous Systems

Cited by 10 publications

References 14 publications

Individual Differences in the Acceptance and Adoption of AI-enabled Autonomous Systems

Individual Differences in the Acceptance and Adoption of AI-enabled Autonomous Systems

Assessment of Trust in Automation in the “Real World”: Requirements for New Trust in Automation Measurement Techniques for Use by Practitioners

Trust in Automated Parking Systems

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