The Influence of robot personality on the development of uncanny feelings

Paetzel-Prüsmann, Maike; Perugia, Giulia; Castellano, Ginevra

doi:10.1016/j.chb.2021.106756

Cited by 47 publications

(22 citation statements)

References 76 publications

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“…(2) progressively exposing people to the multimodal behaviors of a robot improves people's perception of it (Paetzel and Castellano, 2019); and (3) the perceptual dimensions that contribute to people's mental image of the robot stabilize over time (Paetzel et al, 2020;Paetzel-Prüsmann et al, 2021). Hence, besides investigating the role of gaze patterns in a joint task with a focus on engagement, in this paper, we also focus on understanding how mutual gaze in a social chat develops over time within and between interaction sessions and how it relates to people's perception of the robotic interaction partner.…”

Section: Tracking Gaze Over Timementioning

confidence: 99%

I Can See It in Your Eyes: Gaze as an Implicit Cue of Uncanniness and Task Performance in Repeated Interactions With Robots

et al. 2021

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Over the past years, extensive research has been dedicated to developing robust platforms and data-driven dialog models to support long-term human-robot interactions. However, little is known about how people's perception of robots and engagement with them develop over time and how these can be accurately assessed through implicit and continuous measurement techniques. In this paper, we explore this by involving participants in three interaction sessions with multiple days of zero exposure in between. Each session consists of a joint task with a robot as well as two short social chats with it before and after the task. We measure participants' gaze patterns with a wearable eye-tracker and gauge their perception of the robot and engagement with it and the joint task using questionnaires. Results disclose that aversion of gaze in a social chat is an indicator of a robot's uncanniness and that the more people gaze at the robot in a joint task, the worse they perform. In contrast with most HRI literature, our results show that gaze toward an object of shared attention, rather than gaze toward a robotic partner, is the most meaningful predictor of engagement in a joint task. Furthermore, the analyses of gaze patterns in repeated interactions disclose that people's mutual gaze in a social chat develops congruently with their perceptions of the robot over time. These are key findings for the HRI community as they entail that gaze behavior can be used as an implicit measure of people's perception of robots in a social chat and of their engagement and task performance in a joint task.

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Section: Tracking Gaze Over Timementioning

confidence: 99%

I Can See It in Your Eyes: Gaze as an Implicit Cue of Uncanniness and Task Performance in Repeated Interactions With Robots

et al. 2021

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“…Many previous studies have more or less done similar work in exploring robots' potential for expressing personality traits or studying the effects or properties of robot personalities [14][15][16][17][18][19][20][21][22][23]. They offer valuable scientific insights into the roles of robot personality in human-robot interaction.…”

Section: Goals and The Limitations Of The State Of The Art In The Eng...mentioning

confidence: 99%

Identifying Personality Dimensions for Engineering Robot Personalities in Significant Quantities with Small User Groups

2022

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Future service robots mass-produced for practical applications may benefit from having personalities. To engineer robot personalities in significant quantities for practical applications, we need first to identify the personality dimensions on which personality traits can be effectively optimised by minimising the distances between engineering targets and the corresponding robots under construction, since not all personality dimensions are applicable and equally prominent. Whether optimisation is possible on a personality dimension depends on how specific users consider the personalities of a type of robot, especially whether they can provide effective feedback to guide the optimisation of certain traits on a personality dimension. The dimensions may vary from user group to user group since not all people consider a type of trait to be relevant to a type of robot, which our results corroborate. Therefore, we had proposed a test procedure as an engineering tool to identify, with the help of a user group, personality dimensions for engineering robot personalities out of a type of robot knowing its typical usage. It applies to robots that can imitate human behaviour and small user groups with at least eight people. We confirmed its effectiveness in limited-scope tests.

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“…Previous work in human-human interaction has highlighted that spontaneous facial mimicry signals liking in first acquaintances ( Chartrand and Bargh, 1999 ; Kulesza et al, 2015 ) and rapport in established relationships ( Hess et al, 1995 ; Fischer et al, 2012 ). Liking and rapport are complex constructs known to be influenced by factors such as the appearance and embodiment of an agent ( Perugia et al, 2021 ; Paetzel et al, 2020 ; Paetzel-Prüsmann et al, 2021 ). In this study, besides understanding the role of embodiment and humanlikeness in facial mimicry, we aim to gain more insights on the relationship between spontaneous facial mimicry and a few of the perceptual dimensions known to influence rapport and liking.…”

Section: Research Questions and Hypothesesmentioning

confidence: 99%

Does the Goal Matter? Emotion Recognition Tasks Can Change the Social Value of Facial Mimicry Towards Artificial Agents

et al. 2021

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In this paper, we present a study aimed at understanding whether the embodiment and humanlikeness of an artificial agent can affect people’s spontaneous and instructed mimicry of its facial expressions. The study followed a mixed experimental design and revolved around an emotion recognition task. Participants were randomly assigned to one level of humanlikeness (between-subject variable: humanlike, characterlike, or morph facial texture of the artificial agents) and observed the facial expressions displayed by three artificial agents differing in embodiment (within-subject variable: video-recorded robot, physical robot, and virtual agent) and a human (control). To study both spontaneous and instructed facial mimicry, we divided the experimental sessions into two phases. In the first phase, we asked participants to observe and recognize the emotions displayed by the agents. In the second phase, we asked them to look at the agents’ facial expressions, replicate their dynamics as closely as possible, and then identify the observed emotions. In both cases, we assessed participants’ facial expressions with an automated Action Unit (AU) intensity detector. Contrary to our hypotheses, our results disclose that the agent that was perceived as the least uncanny, and most anthropomorphic, likable, and co-present, was the one spontaneously mimicked the least. Moreover, they show that instructed facial mimicry negatively predicts spontaneous facial mimicry. Further exploratory analyses revealed that spontaneous facial mimicry appeared when participants were less certain of the emotion they recognized. Hence, we postulate that an emotion recognition goal can flip the social value of facial mimicry as it transforms a likable artificial agent into a distractor. Further work is needed to corroborate this hypothesis. Nevertheless, our findings shed light on the functioning of human-agent and human-robot mimicry in emotion recognition tasks and help us to unravel the relationship between facial mimicry, liking, and rapport.

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The Influence of robot personality on the development of uncanny feelings

Cited by 47 publications

References 76 publications

I Can See It in Your Eyes: Gaze as an Implicit Cue of Uncanniness and Task Performance in Repeated Interactions With Robots

I Can See It in Your Eyes: Gaze as an Implicit Cue of Uncanniness and Task Performance in Repeated Interactions With Robots

Identifying Personality Dimensions for Engineering Robot Personalities in Significant Quantities with Small User Groups

Does the Goal Matter? Emotion Recognition Tasks Can Change the Social Value of Facial Mimicry Towards Artificial Agents

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