Relationships between User Demographics and User Trust in an Autonomous Agent

Hillesheim, Anthony J.; Rusnock, Christina F.; Bindewald, Jason M.; Miller, Michael E.

doi:10.1177/1541931213601560

Cited by 10 publications

(6 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…High complexity situations tended to result in lower levels of trust in the driver assist systems, while low complexity situations resulted in higher trust. This result is consistent with what would be expected behaviorally, as previous research as suggested that complex or high workload situations might negatively influence trust or reliance in automation (Hillesheim et al, 2017). It is expected that, had this same study been carried out within a driving simulator or on-road experiment, behavioral indicators of trust may have suggested similar levels of reliance and trust in the high complexity situations.…”

Section: Discussionsupporting

confidence: 90%

“…The complexity of the task and the expected workload involved will also influence how operators trust automated systems (Bailey & Scerbo, 2007;Hancock et al, 2011). Previous research has found that increases in workload will also negatively impact trust in automation (Hillesheim et al, 2017).…”

Section: Factors Impacting Trustmentioning

confidence: 99%

“…There are a variety of differences related to the individual using the automation that may impact how much trust they place in the system. This includes factor such gender and level of education (Hillesheim et al, 2017). Additionally, increased experience with a system can inform trust (Gold et al, 2015;Azevedo-Sa et al, 2020).…”

Section: Factors Impacting Trustmentioning

confidence: 99%

See 2 more Smart Citations

Assessing How Driving Self-Efficacy Influences Situational Trust in Driver Assist Technologies

Ferraro

Mouloua

2022

Proceedings of the Human Factors and Ergonomics Society Annual

View full text Add to dashboard Cite

As the movement toward fully autonomous driving continues, it is critical to assess factors that may impact how drivers interact with and perform in conjunction with automated driving systems. The trust drivers place in the driver assist technologies can impact how effectively these systems are utilized. Human factors research has found a variety of factors related to the environment, the system, and the user that influence trust in automated systems. The current study was designed to assess how situational factors influence how drivers trust different driver assist features, and how driving self-efficacy impacts this relationship. 101 participants reported situational trust scores based on 10 vignette traffic scenarios that described driving in high or low complexity situations while using one of five driver assist features. It was hypothesized that situation and automation-related factors would influence participants’ trust. Results indicated a significant interaction between the complexity of the driving scenario and the different driver assist features. Additional results indicated self-efficacy impacted relationships between the driver assist technologies and trust. These findings are consistent with previous results related to trust and use of automation and have implications for researchers interested in how drivers interact with current and emerging driving technologies. These results can be applied to the development of automated driving systems, informing decisions in the design of future automated vehicles.

show abstract

Section: Discussionsupporting

confidence: 90%

Section: Factors Impacting Trustmentioning

confidence: 99%

See 1 more Smart Citation

Assessing How Driving Self-Efficacy Influences Situational Trust in Driver Assist Technologies

Ferraro

Mouloua

2022

Proceedings of the Human Factors and Ergonomics Society Annual

View full text Add to dashboard Cite

show abstract

“…Gender can also play a role in the interactions that users have with technology. In one study, for example, female users tend to have less trust in automated agents (Hillesheim, Rusnock, Bindewald, & Miller, 2017). Finally, personality traits also have a bearing on users' tendency to trust others.…”

Section: A Review Of Variables That Impact Trustmentioning

confidence: 95%

Generational differences in trust in digital assistants

Noah

Sethumadhavan

2019

Proceedings of the Human Factors and Ergonomics Society Annual

View full text Add to dashboard Cite

Human trust in automation has been studied extensively within safety critical domains (military, aviation, process control, etc.) because harmful consequences are associated with the improper calibration of trust in automated systems in these domains (Parasuraman & Riley, 1997). As such, researchers have worked to identify important factors which help humans build trust in such systems (Hoff & Bashir, 2015). With the explosion of AI in consumer technologies, it is becoming equally critical to understand how humans interact with everyday devices. This study investigated how factors that have been identified to impact trust in automation in safety critical domains influence the trust and use of popular digital assistants (Siri, Cortana, Bixby or Google Now). We conducted an online survey with 278 regular users of digital assistants across three generations (GenX, GenY, and GenZ). The results demonstrate that, even after controlling for dispositional factors (i.e., individual characteristics such as age, culture, gender), GenZ exhibited higher trust in digital assistants than GenX. More interestingly, linear regression analyses revealed a different set of predictors of trust for each generation. Results from this survey have implications for the design of digital assistants.

show abstract

“…From the limited prior research, we do know that response to AI is not universal. For example, consumers that are younger and male (Araujo et al, 2020) as well as that have higher levels of education (Hillesheim et al, 2017) have more positive perceptions of AI. Also, consumers with higher political identity salience view AI‐enabled services such as checkouts more favorably, and political ideology serves as a boundary condition in this relation; specifically, liberals prefer AI‐enabled checkouts over self‐service checkouts, whereas conservatives are indifferent (Cui & van Esch, 2022).…”

Section: Ai In Marketingmentioning

confidence: 99%

The influence of religiosity on consumers' evaluations of brands using artificial intelligence

Minton

Kaplan

Cabano

2022

Psychology and Marketing

View full text Add to dashboard Cite

Prior research is limited that examines how consumers respond to artificial intelligence (AI) used by businesses and in marketing. Specifically, more research is needed that explores which consumers are more likely to support AI use in marketing as well as why this occurs to develop targeted marketing campaigns toward these consumers. Through three studies, our research addresses these gaps by testing the role of religiosity on AI evaluations. Study 1 shows that religiosity positively influences perceptions of AI in marketing, which is mediated by greater trust in AI. Study 2 primes religiosity to demonstrate the causality of the effects, showing that consumers exposed to a religiosity prime more positively evaluate companies and their employees when AI is used. Study 3 then better confirms the underlying mechanisms of these effects using a virtual conversational agent context by showing that higher religiosity consumers are more trusting of the unseen, which leads to greater trust of a company, and ultimately positively influences evaluations of companies using AI. We contribute to belief congruence theory in identifying the role of trust (specifically trust in the unseen related to AI) in the belief-behavior relationship. We also identify how marketers can use religious cues to increase trust in AI in marketing.

show abstract

Relationships between User Demographics and User Trust in an Autonomous Agent

Cited by 10 publications

References 14 publications

Assessing How Driving Self-Efficacy Influences Situational Trust in Driver Assist Technologies

Assessing How Driving Self-Efficacy Influences Situational Trust in Driver Assist Technologies

Generational differences in trust in digital assistants

The influence of religiosity on consumers' evaluations of brands using artificial intelligence

Contact Info

Product

Resources

About