If your device could smile: People trust happy-sounding artificial agents more

Abstract

While it is clear that artificial agents that are able to express emotions increase trust in Human-Machine Interaction, most studies looking at this effect concentrated on the expression of emotions through the visual channel, e.g. facial expressions. However, emotions can be expressed in the vocal channel too, yet the relationship between trust and vocally expressive agents has not yet been investigated. We use a game theory paradigm to examine the influence of smiling in the voice on trusting behavior towards a virtual agent, who responds either trustworthily or untrustworthily in an investment game. We found that a smiling voice increases trust, and that this effect persists over time, despite the accumulation of clear evidence regarding the agent's level of trustworthiness in a negotiated interaction. Smiling voices maintain this benefit even in the face of behavioral evidence of untrustworthiness.

Evaluating If Trust and Personal Information Privacy Concerns Are Barriers to Using Health Insurance That Explicitly Utilizes AI

“…The increasing role of AI across the health insurance supply-chain brings new sources of distrust that come from the lack of human attributes in more stages of the supply chain, both front-end and back-end and the real or perceived unpredictability of AI. The consumer's trust in a virtual agent they are interacting with can be reduced by the lack of human factors like visual and auditory emotions (Torre, Goslin, and White 2020). As Figure 1 illustrates the interaction of the consumer can be divided into three scenarios: Firstly, a traditional face to face interaction without utilizing technology.…”

The influence of perceived vocal traits on trusting behaviours in an economic game

“…The only comparable studies to date are those by Torre et al (2015Torre et al ( , 2016Torre et al ( , 2020Torre, 2017). In those studies, the authors were able to detect main effects and interactions in linear mixed models using sample sizes in the order of 20 participants per condition.…”

“…Second, do voice-based first impressions interact over time with the voice owner's observed actions, further influencing the listener's behaviour? A small number of existing studies suggest that this may indeed be the case (Torre, 2017;Torre et al, 2015Torre et al, , 2016Torre et al, , 2020; however, the voice materials in these studies incorporated a number of different linguistic, social, and identity-related cues. The effects of voice quality alone on listener behaviour therefore remain unknown.…”

Instrumental learning in social interactions: trait learning from faces and voices

“…However, increasing the distinctiveness of the voice stimuli could itself interfere with learning from feedback. People readily form personality impressions from mere exposure to voices alone (McAleer et al, 2014) and there is evidence that these first impressions can interact with learning about the behaviour of those agents (Torre et al, 2020;Torre, Goslin, White, & Zanatto, 2018). Changing the sex, accent, or even just the pitch of the different vocal identities would likely have resulted in differences in their initial perceived attractiveness or trustworthiness, which could have biased learning about their behaviour.…”

“…Indeed, there is evidence that manipulating the physical characteristics of voices (e.g. expression of emotion) can affect participants' perception of personality traits in artificial agents (Torre, Goslin, & White, 2020).…”