Robot’s Social Gaze Affects Conflict Resolution but not Conflict Adaptations

Ciardo, Francesca; Wykowska, Agnieszka

doi:10.5334/joc.189

Cited by 5 publications

(4 citation statements)

References 72 publications

(117 reference statements)

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“…Gaze cueing effects of robotic gaze have been consistently found with different anthropomorphic robots, including sophisticated ones with eye movement (Kompatsiari et al, 2021;Ciardo and Wykowska, 2022) and those without eye movement (Chaminade and Okka, 2013;Morillo-Mendez et al, 2022. This finding does not automatically categorize such robots as social agents as non-social stimuli such as arrows can also induce automatic gaze cueing effects (Kawai, 2011;Slessor et al, 2016).…”

Section: Robots Gaze Following and The Adoption Of The Intentional St...mentioning

confidence: 98%

Can the robot “see” what I see? Robot gaze drives attention depending on mental state attribution

Morillo-Mendez,

Stower,

Sleat

et al. 2023

Front. Psychol.

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Mentalizing, where humans infer the mental states of others, facilitates understanding and interaction in social situations. Humans also tend to adopt mentalizing strategies when interacting with robotic agents. There is an ongoing debate about how inferred mental states affect gaze following, a key component of joint attention. Although the gaze from a robot induces gaze following, the impact of mental state attribution on robotic gaze following remains unclear. To address this question, we asked forty-nine young adults to perform a gaze cueing task during which mental state attribution was manipulated as follows. Participants sat facing a robot that turned its head to the screen at its left or right. Their task was to respond to targets that appeared either at the screen the robot gazed at or at the other screen. At the baseline, the robot was positioned so that participants would perceive it as being able to see the screens. We expected faster response times to targets at the screen the robot gazed at than targets at the non-gazed screen (i.e., gaze cueing effect). In the experimental condition, the robot's line of sight was occluded by a physical barrier such that participants would perceive it as unable to see the screens. Our results revealed gaze cueing effects in both conditions although the effect was reduced in the occluded condition compared to the baseline. These results add to the expanding fields of social cognition and human-robot interaction by suggesting that mentalizing has an impact on robotic gaze following.

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Section: Robots Gaze Following and The Adoption Of The Intentional St...mentioning

confidence: 98%

Can the robot “see” what I see? Robot gaze drives attention depending on mental state attribution

Morillo-Mendez,

Stower,

Sleat

et al. 2023

Front. Psychol.

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“…For example, group identity can alter the neural processing of information during social attention (Kawai, 2011;Kawakami et al, 2014Kawakami et al, , 2017, and learning (Hobson & Inzlicht, 2016). Studies showed that the mere presence of others can influence how people perceive reward and feedback (i.e., social facilitation; Ciardo & Wykowska, 2022;Simon et al, 2014;Zajonc, 1965).…”

Section: Introductionmentioning

confidence: 99%

Temporal interplay between cognitive conflict and attentional markers in social collaboration

Abubshait,

Perez‐Osorio,

De Tommaso

et al. 2024

Psychophysiology

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Cognitive processes deal with contradictory demands in social contexts. On the one hand, social interactions imply a demand for cooperation, which requires processing social signals, and on the other, demands for selective attention require ignoring irrelevant signals, to avoid overload. We created a task with a humanoid robot displaying irrelevant social signals, imposing conflicting demands on selective attention. Participants interacted with the robot as a team (high social demand; n = 23) or a passive co‐actor (low social demand; n = 19). We observed that theta oscillations indexed conflict processing of social signals. Subsequently, alpha oscillations were sensitive to the conflicting social signals and the mode of interaction. These findings suggest that brains have distinct mechanisms for dealing with the complexity of social interaction and that these mechanisms are activated differently depending on the mode of the interaction. Thus, how we process environmental stimuli depends on the beliefs held regarding our social context.

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“…Robot verbal feedback has been shown to influence participants' choices (Ham and Midden, 2014). However, robot feedback could also be provided through the non-verbal behavior, like facial expressions, gaze behavior and gestures for instance (Gonsior et al, 2011;Ciardo & Wykowska, 2022;Parenti et al, 2022). Yet, the effects of nonverbal feedback from the robot remain relatively understudied.…”

Section: Introductionmentioning

confidence: 99%

Differences in social expectations about robot signals and human signals

Parenti¹,

Belkaid²,

Wykowska³

2023

Preprint

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Decision-making processes are involved in a large portion of humans’ everyday life and often occur in social situations. Although social decision-making has received increasing interest in literature, the influence of communicative signals, like social cues and feedback, on social decision-making is still poorly understood. In particular, the issue of whether social signals exhibited by non-human agents influence decision making has not yet been addressed. This question is of great importance today, in the new era in which artificial agents, such as robots or avatars start interacting with humans on a daily basis. This study aimed to examine whether robot non-verbal communicative behavior has an effect on human decision-making and can be perceived as a social signal. To this end, we implemented a 2-alternative-choice task with a between-subjects design where a robot acted as a game partner. We manipulated robot’s cues before participant’s decision and robot’s feedback after the decision. We found that manipulating robot signals affected participants’ performance. In particular, participants were slower in the condition where cues were mostly invalid and the robot reacted positively to wins. We show that this effect could not be attributed to attentional mechanisms, feedback expectation, or cognitive control. Instead, our results suggest that the effect is rather due to the violation of expectations about the incongruence between social signals. Our findings also indicate differences in these social expectations when they are about robot signals compared to human signals.

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Robot’s Social Gaze Affects Conflict Resolution but not Conflict Adaptations

Cited by 5 publications

References 72 publications

Can the robot “see” what I see? Robot gaze drives attention depending on mental state attribution

Can the robot “see” what I see? Robot gaze drives attention depending on mental state attribution

Temporal interplay between cognitive conflict and attentional markers in social collaboration

Differences in social expectations about robot signals and human signals

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