Trusting Digital Chameleons: The Effect of Mimicry by a Virtual Social Agent on User Trust

Verberne, F.M.F.; Ham, Jaap; Ponnada, Aditya; Midden, C.J.H.

doi:10.1007/978-3-642-37157-8_28

Cited by 42 publications

(46 citation statements)

References 21 publications

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“…In the same business negotiation task, Maddux et al (2008, Study 2) found that the amount of time participants self-reported mimicking their partner was significantly correlated with the partner's rating of trust towards the mimicker, and the partner's trust mediated a positive effect of mimicry on the likelihood of negotiating a successful deal. In line with these findings, Verberne et al (2013) found people rated more trust towards a virtual character that mimicked them, and mimicry also increased participants' willingness to trust the virtual character in a decision-making task. However, they could not replicate these results with a second character and a different behavioural measure.…”

Section: Affiliation and Trustsupporting

confidence: 68%

“…Participants who were mimicked rated the character as more effective on a composite scale which included likability (Bailenson & Yee, 2005), although the weighting of likeability was unclear. Another virtual mimicry study found a positive effect on liking for one out of two virtual characters that mimicked participants in the same way (Verberne, Ham, Ponnada, & Midden, 2013). Finally, Maddux, Mullen and Galinsky (2008, Study 2) instructed participants to either mimic or not mimic their partner during a business negotiation task, and found that mimicry did not lead the partners to rate more liking for each other.…”

Section: Abstract: Mimicry Imitation Nonverbal Behaviour Neurocognmentioning

confidence: 98%

“…The mimicry and control conditions are also well-matched, because the character is always animated with real movements made by a person being mimicked. Furthermore, the mimicry interaction can be perfectly replicated using the same computer code (Verberne et al, 2013), while characteristics of the character and the virtual environment can be endlessly tailored. For example, the researcher who wanted to investigate age could program a child character to mimic participants (Banakou, Groten, & Slater, 2013).…”

Section: Virtual Mimicrymentioning

confidence: 99%

“…Studies of virtual mimicry have reported similar effects to mimicry from human confederates even with minimal other behaviours (e.g. Bailenson & Yee, 2005;Verberne et al, 2013;Vrijsen, Lange, Dotsch, et al, 2010), suggesting this can be an effective alternative approach. …”

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confidence: 93%

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Cognitive mechanisms for responding to mimicry from others

Hale

Hamilton

2016

Neuroscience & Biobehavioral Reviews

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unclear how the complex behavioural effects of mimicry relate to neural systems which respond to being mimicked. Mimicry activates regions associated with mirror properties, selfother processing and reward. In this review, we outline three potential models linking these regions with cognitive consequences of being mimicked. The models suggest that positive downstream consequences of mimicry may depend upon self-other overlap, detection of contingency or low prediction error. Finally, we highlight limitations with traditional research designs and suggest alternative methods for achieving highly ecological validity and experimental control. We also highlight unanswered questions which may guide future research. Keywords: mimicry, imitation, nonverbal behaviour, neurocognitive modelsIt is often said that imitation is the sincerest form of flattery, and copying what other people do is a central feature of human social interaction (Frith & Frith, 2012; Hamilton, 2014; Meltzoff, 2010; Over & Carpenter, 2013). One way we copy others is through unconscious behavioural mimicry, also described as 'behaviour matching' (Bernieri & Rosenthal, 1991;Chartrand & Bargh, 1999) or the 'chameleon effect' (Chartrand & Bargh, 1999). This kind of mimicry occurs when one person unintentionally and effortlessly copies another person's posture or body movements without either one being aware (Chartrand & Lakin, 2013;Chartrand & van Baaren, 2009). Mimicry may extend to the contagion of facial expressions (Bavelas, Black, Lemery, & Mullett, 1986, 1987 Dimberg, Thunberg, & Elmehed, 2000;Hsee, Hatfield, Carlson, & Chemtob, 1990), moods (Hsee et al., 1990;Neumann & Strack, 2000) and speech (Giles & Powesland, 1975;Neumann & Strack, 2000).As well as mimicry, there are many other ways we coordinate our behaviour with other people during social interactions (Table 1). The umbrella term 'interpersonal coordination' covers a range of coordinated actions between two people, which can be linked in both space and time. Actions occurring at the same time are described as entrained or synchronous; this includes perfect synchrony where actions are matched in form and timing, as well as general synchrony where different actions are coordinated in time (see Table 1, column 1). Actions that occur after a delay but which are contingent on the other are termed imitation or mimicry if the form is the same, and complementary if the form is different (see column 2). There is a distinction between imitation, which is deliberate and goal-directed,and mimicry, which is unconscious and spontaneous. In this paper we will focus specifically on mimicry. For the main part we will limit our review to mimicry of postures and body movements, and we will not include literature on facial, emotional or vocal mimicry. We will also concentrate on adult mimicry rather than developmental literature. At the end, we will return to consider how future research may situate mimicry within a wider framework of interpersonal coordination. Whilst partners in real life social interac...

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Section: Affiliation and Trustsupporting

confidence: 68%

Section: Abstract: Mimicry Imitation Nonverbal Behaviour Neurocognmentioning

confidence: 98%

Section: Virtual Mimicrymentioning

confidence: 99%

mentioning

confidence: 93%

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Cognitive mechanisms for responding to mimicry from others

Hale

Hamilton

2016

Neuroscience & Biobehavioral Reviews

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“…For instance, knowing the participant's head location means that a virtual character can be programmed to orient their head and/or gaze towards participant's head (Forbes, Pan, & Hamilton, 2016; Pan & Hamilton, 2015) and to maintain an appropriate social distance by stepping back or forward (Pan, Gillies, Barker, Clark, & Slater, 2012). The ability to link the behaviour of a virtual character to the participant in real time also facilitated a series of studies on mimicry in VR, where the virtual character copies participants’ head movements (Bailenson & Yee, 2007; Verberne, Ham, Ponnada, & Midden, 2013), or both head and torso movements (Hale & Hamilton, 2016). …”

Section: The Foothills – How To Use Vrmentioning

confidence: 99%

Why and how to use virtual reality to study human social interaction: The challenges of exploring a new research landscape

Pan

Hamilton²

2018

British J of Psychology

550

346

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As virtual reality (VR) technology and systems become more commercially available and accessible, more and more psychologists are starting to integrate VR as part of their methods. This approach offers major advantages in experimental control, reproducibility, and ecological validity, but also has limitations and hidden pitfalls which may distract the novice user. This study aimed to guide the psychologist into the novel world of VR, reviewing available instrumentation and mapping the landscape of possible systems. We use examples of state‐of‐the‐art research to describe challenges which research is now solving, including embodiment, uncanny valley, simulation sickness, presence, ethics, and experimental design. Finally, we propose that the biggest challenge for the field would be to build a fully interactive virtual human who can pass a VR Turing test – and that this could only be achieved if psychologists, VR technologists, and AI researchers work together.

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Understanding voice‐based information uncertainty: A case study of health information seeking with voice assistants

Brewer

2023

Asso for Info Science & Tech

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Evaluating information quality online is increasingly important for healthy decision‐making. People assess information quality using visual interfaces (e.g., computers, smartphones) with visual cues like aesthetics. Yet, voice interfaces lack critical visual cues for evaluating information because there is often no visual display. Without ways to assess voice‐based information quality, people may overly trust or misinterpret information which can be challenging in high‐risk or sensitive contexts. This paper investigates voice information uncertainty in one high‐risk context—health information seeking. We recruited 30 adults (ages 18–84) in the United States to participate in scenario‐based interviews about health topics. Our findings provide evidence of information uncertainty expectations with voice assistants, voice search preferences, and the audio cues they use to assess information quality. We contribute a nuanced discussion of how to inform more critical information ecosystems with voice technologies and propose ways to design audio cues to help people more quickly assess content quality.

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Trusting Digital Chameleons: The Effect of Mimicry by a Virtual Social Agent on User Trust

Cited by 42 publications

References 21 publications

Cognitive mechanisms for responding to mimicry from others

Cognitive mechanisms for responding to mimicry from others

Why and how to use virtual reality to study human social interaction: The challenges of exploring a new research landscape

Understanding voice‐based information uncertainty: A case study of health information seeking with voice assistants

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