9 results on '"Cross, Emily S."'
Search Results
2. Social Robots on a Global Stage: Establishing a Role for Culture During Human–Robot Interaction
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Lim, Velvetina, Rooksby, Maki, and Cross, Emily S.
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- 2021
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3. People's dispositional cooperative tendencies towards robots are unaffected by robots' negative emotional displays in prisoner's dilemma games.
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Hsieh, Te-Yi and Cross, Emily S.
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PRISONER'S dilemma game , *SADNESS , *SOCIAL robots , *ROBOTS - Abstract
The study explores the impact of robots' emotional displays on people's tendency to cooperate with a robot opponent in prisoner's dilemma games. Participants played iterated prisoner's dilemma games with a non-expressive robot (as a measure of cooperative baseline), followed by an angry, and a sad robot, in turn. Based on the Emotion as Social Information model, we expected participants with higher cooperative predispositions to cooperate less when a robot displayed anger, and cooperate more when the robot displayed sadness. Contrarily, according to this model, participants with lower cooperative predispositions should cooperate more with an angry robot and less with a sad robot. The results of 60 participants failed to support the predictions. Only the participants' cooperative predispositions significantly predicted their cooperative tendencies during gameplay. Participants who cooperated more in the baseline measure also cooperated more with the robots displaying sadness and anger. In exploratory analyses, we found that participants who accurately recognised the robots' sad and angry displays tended to cooperate less with them overall. The study highlights the impact of personal factors in human–robot cooperation, and how these factors might surpass the influence of bottom-up emotional displays by the robots in the present experimental scenario. [ABSTRACT FROM AUTHOR]
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- 2022
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4. Social Cognition in the Age of Human–Robot Interaction
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Henschel, Anna, Hortensius, Ruud, Cross, Emily S., Leerstoel Aarts, Social-cognitive and interpersonal determinants of behaviour, Leerstoel Aarts, and Social-cognitive and interpersonal determinants of behaviour
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Social Cognition ,0301 basic medicine ,Computer science ,Neuroimaging ,social cognition ,Human–robot interaction ,03 medical and health sciences ,Cognition ,0302 clinical medicine ,Artificial Intelligence ,Social cognition ,social robotics ,human–robot interaction ,Humans ,Cognitive science ,Social robot ,General Neuroscience ,Field (Bourdieu) ,fMRI ,Neurosciences ,Robotics ,Social cue ,artificial intelligence ,Object (philosophy) ,030104 developmental biology ,Embodied cognition ,Robot ,030217 neurology & neurosurgery - Abstract
Artificial intelligence advances have led to robots endowed with increasingly sophisticated social abilities. These machines speak to our innate desire to perceive social cues in the environment, as well as the promise of robots enhancing our daily lives. However, a strong mismatch still exists between our expectations and the reality of social robots. We argue that careful delineation of the neurocognitive mechanisms supporting human–robot interaction will enable us to gather insights critical for optimising social encounters between humans and robots. To achieve this, the field must incorporate human neuroscience tools including mobile neuroimaging to explore long-term, embodied human–robot interaction in situ. New analytical neuroimaging approaches will enable characterisation of social cognition representations on a finer scale using\ud sensitive and appropriate categorical comparisons (human, animal, tool, or\ud object). The future of social robotics is undeniably exciting, and insights from human neuroscience research will bring us closer to interacting and collaborating with socially sophisticated robots.
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- 2020
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5. Resonance as a Design Strategy for AI and Social Robots.
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Lomas, James Derek, Lin, Albert, Dikker, Suzanne, Forster, Deborah, Lupetti, Maria Luce, Huisman, Gijs, Habekost, Julika, Beardow, Caiseal, Pandey, Pankaj, Ahmad, Nashra, Miyapuram, Krishna, Mullen, Tim, Cooper, Patrick, van der Maden, Willem, and Cross, Emily S.
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SOCIAL robots ,RESONANCE ,SOCIAL perception ,ARTIFICIAL intelligence ,SOCIAL interaction - Abstract
Resonance, a powerful and pervasive phenomenon, appears to play a major role in human interactions. This article investigates the relationship between the physical mechanism of resonance and the human experience of resonance, and considers possibilities for enhancing the experience of resonance within human–robot interactions. We first introduce resonance as a widespread cultural and scientific metaphor. Then, we review the nature of "sympathetic resonance" as a physical mechanism. Following this introduction, the remainder of the article is organized in two parts. In part one, we review the role of resonance (including synchronization and rhythmic entrainment) in human cognition and social interactions. Then, in part two, we review resonance-related phenomena in robotics and artificial intelligence (AI). These two reviews serve as ground for the introduction of a design strategy and combinatorial design space for shaping resonant interactions with robots and AI. We conclude by posing hypotheses and research questions for future empirical studies and discuss a range of ethical and aesthetic issues associated with resonance in human–robot interactions. [ABSTRACT FROM AUTHOR]
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- 2022
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6. From social brains to social robots: applying neurocognitive insights to human–robot interaction
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Cross, Emily S., Hortensius, Ruud, Wykowska, Agnieszka, Leerstoel Aarts, Social-cognitive and interpersonal determinants of behaviour, Leerstoel Aarts, and Social-cognitive and interpersonal determinants of behaviour
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Cognitive science ,Ethics ,0303 health sciences ,Introduction ,Artificial intelligence ,Social robot ,business.industry ,Social robotics ,Robotics ,Human-brain ,General Biochemistry, Genetics and Molecular Biology ,Human–robot interaction ,03 medical and health sciences ,0302 clinical medicine ,Social neuroscience ,General Agricultural and Biological Sciences ,Psychology ,business ,Neurocognitive ,030217 neurology & neurosurgery ,030304 developmental biology - Abstract
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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- 2019
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7. Mind Meets Machine: Towards a Cognitive Science of Human–Machine Interactions.
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Cross, Emily S. and Ramsey, Richard
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COGNITIVE science , *COGNITIVE neuroscience , *COGNITIVE ability , *HUMAN-robot interaction , *SOCIAL perception - Abstract
As robots advance from the pages and screens of science fiction into our homes, hospitals, and schools, they are poised to take on increasingly social roles. Consequently, the need to understand the mechanisms supporting human–machine interactions is becoming increasingly pressing. We introduce a framework for studying the cognitive and brain mechanisms that support human–machine interactions, leveraging advances made in cognitive neuroscience to link different levels of description with relevant theory and methods. We highlight unique features that make this endeavour particularly challenging (and rewarding) for brain and behavioural scientists. Overall, the framework offers a way to study the cognitive science of human–machine interactions that respects the diversity of social machines, individuals' expectations and experiences, and the structure and function of multiple cognitive and brain systems. Although machines designed to socially interact with humans are proliferating, our understanding of the mental processes supporting such interactions remains limited. The cognitive and brain sciences can make considerable theoretical and methodological contributions to this endeavour. To date, the modal approach to cognitive science-informed human–robot interaction research has been grounded in social cognition. We widen the lens through which much of this research has been framed to incorporate diverse and interacting forms of cognition, which emphasise the complexity of understanding human–robot interaction on a mechanistic level. Our framework seeks to account for the unusual demands on (neuro)cognition presented by engaging with social machines, focusing on machine variety, diverse neurocognitive systems, and unique contextual factors such as media-skewed expectations. [ABSTRACT FROM AUTHOR]
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- 2021
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8. A neurocognitive investigation of the impact of socializing with a robot on empathy for pain.
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Cross, Emily S., Riddoch, Katie A., Pratts, Jaydan, Titone, Simon, Chaudhury, Bishakha, and Hortensius, Ruud
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INTERPERSONAL relations , *BRAIN imaging , *EMPATHY , *SOCIAL robots , *SOCIALIZATION - Abstract
To what extent can humans form social relationships with robots? In the present study, we combined functional neuroimaging with a robot socializing intervention to probe the flexibility of empathy, a core component of social relationships, towards robots. Twenty-six individuals underwent identical fMRI sessions before and after being issued a social robot to take home and interact with over the course of a week. While undergoing fMRI, participants observed videos of a human actor or a robot experiencing pain or pleasure in response to electrical stimulation. Repetition suppression of activity in the pain network, a collection of brain regions associated with empathy and emotional responding, was measured to test whether socializing with a social robot leads to greater overlap in neural mechanisms when observing human and robotic agents experiencing pain or pleasure. In contrast to our hypothesis, functional region-of-interest analyses revealed no change in neural overlap for agents after the socializing intervention. Similarly, no increase in activation when observing a robot experiencing pain emerged post-socializing. Whole-brain analysis showed that, before the socializing intervention, superior parietal and early visual regions are sensitive to novel agents, while after socializing, medial temporal regions show agent sensitivity. A region of the inferior parietal lobule was sensitive to novel emotions, but only during the pre-socializing scan session. Together, these findings suggest that a short socialization intervention with a social robot does not lead to discernible differences in empathy towards the robot, as measured by behavioural or brain responses. We discuss the extent to which long-term socialization with robots might shape social cognitive processes and ultimately our relationships with these machines. [ABSTRACT FROM AUTHOR]
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- 2019
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9. The shaping of social perception by stimulus and knowledge cues to human animacy.
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Cross, Emily S., Ramsey, Richard, Liepelt, Roman, Prinz, Wolfgang, and de C. Hamilton, Antonia F.
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ROBOTS , *SOCIAL interaction , *SOCIAL perception , *HUMAN behavior , *SOCIAL networks - Abstract
Although robots are becoming an ever-growing presence in society, we do not hold the same expectations for robots as we do for humans, nor do we treat them the same. As such, the ability to recognize cues to human animacy is fundamental for guiding social interactions.We review literature that demonstrates cortical networks associated with person perception, action observation and mentalizing are sensitive to human animacy information. In addition, we show that most prior research has explored stimulus properties of artificial agents (humanness of appearance or motion), with less investigation into knowledge cues (whether an agent is believed to have human or artificial origins). Therefore, currently little is known about the relationship between stimulus and knowledge cues to human animacy in terms of cognitive and brain mechanisms. Using fMRI, an elaborate belief manipulation, and human and robot avatars, we found that knowledge cues to human animacy modulate engagement of person perception and mentalizing networks, while stimulus cues to human animacy had less impact on social brain networks. These findings demonstrate that self--other similarities are not only grounded in physical features but are also shaped by prior knowledge. More broadly, as artificial agents fulfil increasingly social roles, a challenge for roboticists will be to manage the impact of pre-conceived beliefswhile optimizing human-like design. [ABSTRACT FROM AUTHOR]
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- 2016
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