Using Trust to Determine User Decision Making &amp; Task Outcome During a Human-Agent Collaborative Task

Herse, Sarita; Vitale, Jonathan; Johnston, Benjamin; Williams, Mary-Anne

doi:10.1145/3434073.3444673

Cited by 7 publications

(5 citation statements)

References 40 publications

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“…Models and techniques such as decision-making under partial observability [10], limited resources, and time constraints are used to tackle such problems. Trust calibration [118] methodologies and the integration of social interaction strategies [119] like "face-work" are other areas of research in this field [120]. Communication Models are the backbone of this theme.…”

Section: B Decision-making and Planningmentioning

confidence: 99%

Human-Agent Teaming: A System-Theoretic Overview

Meimandi,

Bolton,

Beling

2024

Preprint

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Section: B Decision-making and Planningmentioning

confidence: 99%

Human-Agent Teaming: A System-Theoretic Overview

Meimandi,

Bolton,

Beling

2024

Preprint

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Section: Introductionmentioning

confidence: 99%

“…Trust is central to effective interactions and collaborations with robots [1,2]. The ability to establish and sustain trust in a robot determines the functionality and success of the interaction between humans and robots [1]. Too much trust may lead to over-reliance in the capabilities of the robot, whereas too little trust leads to under-utilisation [1].…”

Section: Introductionmentioning

confidence: 99%

“…The ability to establish and sustain trust in a robot determines the functionality and success of the interaction between humans and robots [1]. Too much trust may lead to over-reliance in the capabilities of the robot, whereas too little trust leads to under-utilisation [1]. Given the important role of trust in human-robot interaction, an understanding of how distinct social cues shape trust behaviour is vital.…”

Section: Introductionmentioning

confidence: 99%

“…Previous research focused on influencing trust via alterations of the robot, e.g., introducing more human-like features or changing other aspects of its appearance [8]. However, trust is not only directly mediated by the features and behaviour of a robot by itself, but also by the human perception of these features and behaviours while interacting with a robot [1,9]. One effective way to manipulate trust during human-robot interaction is to focus on a feature of the robot that can be easily changed with the current technological advances and is an established social communication channel in humans, namely smell.…”

Section: Introductionmentioning

confidence: 99%

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No effect of the smell of hexanal on trust in human-robot interaction

Croijmans¹,

Erp²,

Bakker³

et al. 2022

Preprint

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The level of interpersonal trust among people is partially determined through the sense of smell. Hexanal, a molecule which smell resembles freshly cut grass, can increase trust in people. Here, we ask the question if smell can be leveraged to facilitate human-robot interaction and test whether hexanal also increases the level of trust during collaboration with a social robot. In a preregistered double-blind, placebo-controlled study, we tested if trial-by-trial and general trust during perceptual decision making in collaboration with a social robot is affected by hexanal across two samples (n = 46 and n = 44). It was hypothesized that unmasked hexanal and hexanal masked by eugenol, a molecule with a smell resembling clove, would increase the level of trust in human-robot interaction, compared to eugenol alone or a control condition consisting of only the neutral smelling solvent propylene glycol. Contrasting previous findings in human interaction, no significant effect of unmasked or eugenol-masked hexanal on trust in robots was observed. These findings indicate that the conscious or nonconscious impact of smell on trust might not generalise to interactions with social robots. One explanation could be category- and context-dependency of smell leading to a mismatch between the natural smell of hexanal, a smell also occurring in human sweat, and the mechanical physical or mental representation of the robot.

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Human–Robot Coordination and Collaboration in Industry 4.0

Ghanghorkar,

Pillai

2024

Disruptive Technologies and Digital Transformations for Society 5.0

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Using Trust to Determine User Decision Making & Task Outcome During a Human-Agent Collaborative Task

Cited by 7 publications

References 40 publications

Human-Agent Teaming: A System-Theoretic Overview

Human-Agent Teaming: A System-Theoretic Overview

No effect of the smell of hexanal on trust in human-robot interaction

Human–Robot Coordination and Collaboration in Industry 4.0

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