The Perception of Emotion in Artificial Agents

Hortensius, Ruud; Hekele, Felix; Cross, Emily S.

doi:10.1109/tcds.2018.2826921

Cited by 115 publications

(65 citation statements)

References 132 publications

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“…Future studies should continue to pay attention to this issue, as this question is equally important for the development of sophisticated robotic systems as well as studies on the human user (e.g. [7]).…”

Section: Discussionmentioning

confidence: 99%

From social brains to social robots: applying neurocognitive insights to human–robot interaction

Cross

Hortensius

Wykowska

2019

Phil. Trans. R. Soc. B

Self Cite

125

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Amidst the fourth industrial revolution, social robots are resolutely moving from fiction to reality. With sophisticated artificial agents becoming ever more ubiquitous in daily life, researchers across different fields are grappling with the questions concerning how humans perceive and interact with these agents and the extent to which the human brain incorporates intelligent machines into our social milieu. This theme issue surveys and discusses the latest findings, current challenges and future directions in neuroscience- and psychology-inspired human–robot interaction (HRI). Critical questions are explored from a transdisciplinary perspective centred around four core topics in HRI: technical solutions for HRI, development and learning for HRI, robots as a tool to study social cognition, and moral and ethical implications of HRI. Integrating findings from diverse but complementary research fields, including social and cognitive neurosciences, psychology, artificial intelligence and robotics, the contributions showcase ways in which research from disciplines spanning biological sciences, social sciences and technology deepen our understanding of the potential and limits of robotic agents in human social life. This article is part of the theme issue ‘From social brains to social robots: applying neurocognitive insights to human–robot interaction’.

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Section: Discussionmentioning

confidence: 99%

From social brains to social robots: applying neurocognitive insights to human–robot interaction

Cross

Hortensius

Wykowska

2019

Phil. Trans. R. Soc. B

Self Cite

125

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“…Differences in how an agent's appearance impacts person perception compared to the cognitive processes of ToM are further borne out by behavioral findings. For instance, emotions expressed by artificial agents, especially in the case of negative emotions, are sometimes difficult to recognize by human observers . Martini et al .…”

Section: Impact Of Artificial Agent's Visual Featuresmentioning

confidence: 99%

From automata to animate beings: the scope and limits of attributing socialness to artificial agents

Hortensius

Cross

2018

Annals of the New York Academy of Sciences

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Understanding the mechanisms and consequences of attributing socialness to artificial agents has important implications for how we can use technology to lead more productive and fulfilling lives. Here, we integrate recent findings on the factors that shape behavioral and brain mechanisms that support social interactions between humans and artificial agents. We review how visual features of an agent, as well as knowledge factors within the human observer, shape attributions across dimensions of socialness. We explore how anthropomorphism and dehumanization further influence how we perceive and interact with artificial agents. Based on these findings, we argue that the cognitive reconstruction within the human observer is likely to be far more crucial in shaping our interactions with artificial agents than previously thought, while the artificial agent's visual features are possibly of lesser importance. We combine these findings to provide an integrative theoretical account based on the "like me" hypothesis, and discuss the key role played by the Theory-of-Mind network, especially the temporal parietal junction, in the shift from mechanistic to social attributions. We conclude by highlighting outstanding questions on the impact of long-term interactions with artificial agents on the behavioral and brain mechanisms of attributing socialness to these agents.

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“…Many researchers, explore the design space of anthropomorphic or zoomorphic robots equipped with expressive faces (e.g., [5,[12][13][14][15][16]), emotional voices (see [17] for a survey), body language (e.g., [18][19][20][21]), and other features and capacities to make human-robot social interactions more human-like. While initially, Human-Robot Interaction (HRI) research on the emotional expressions of robots had largely focused on single modalities in isolation [22], more recently, researchers have begun to integrate multiple channels, in order to approach the richness of human emotional communication. For instance, HRI studies have examined the perception of emotional expressions involving faces [23], faces and gestures [24], gestures and voices [25] and face-voice-gesture [23] combinations.…”

Section: Introductionmentioning

confidence: 99%

Multimodal Integration of Emotional Signals from Voice, Body, and Context: Effects of (In)Congruence on Emotion Recognition and Attitudes Towards Robots

Tsiourti

Weiss

Wac

et al. 2019

Int J of Soc Robotics

133

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Humanoid social robots have an increasingly prominent place in today's world. Their acceptance in social and emotional human-robot interaction (HRI) scenarios depends on their ability to convey well recognized and believable emotional expressions to their human users. In this article, we incorporate recent findings from psychology, neuroscience, human-computer interaction, and HRI, to examine how people recognize and respond to emotions displayed by the body and voice of humanoid robots, with a particular emphasis on the effects of incongruence. In a social HRI laboratory experiment, we investigated contextual incongruence (i.e., the conflict situation where a robot's reaction is incongrous with the socio-emotional context of the interaction) and cross-modal incongruence (i.e., the conflict situation where an observer receives incongruous emotional information across the auditory (vocal prosody) and visual (whole-body expressions) modalities). Results showed that both contextual incongruence and cross-modal incongruence confused observers and decreased the likelihood that they accurately recognized the emotional expressions of the robot. This, in turn, gives the impression that the robot is unintelligent or unable to express "empathic" behaviour and leads to profoundly harmful effects on likability and believability. Our findings reinforce the need of proper design of emotional expressions for robots that use several channels to communicate their emotional states in a clear and effective way. We offer recommendations regarding design choices and discuss future research areas in the direction of multimodal HRI.

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The Perception of Emotion in Artificial Agents

Abstract: laude) in psychology and the M.Sc. degree in cognitive neuroscience from Utrecht University, Utrecht, The Netherlands, and the Ph.D. degree (cum laude) in social and affective neuroscience from Tilburg University,

Cited by 115 publications

References 132 publications

From social brains to social robots: applying neurocognitive insights to human–robot interaction

From social brains to social robots: applying neurocognitive insights to human–robot interaction

From automata to animate beings: the scope and limits of attributing socialness to artificial agents

Multimodal Integration of Emotional Signals from Voice, Body, and Context: Effects of (In)Congruence on Emotion Recognition and Attitudes Towards Robots

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