Search

The process of understanding the minds of other people, such as their emotions and intentions, is mimicked when individuals try to understand an artificial mind. The assumption is that anthropomorphism, attributing human-like characteristics to non-human agents and objects, is an analogue to theory-of-mind, the ability to infer mental states of other people. Here, we test to what extent these two constructs formally overlap. Specifically, using a multi-method approach, we test if and how anthropomorphism is related to theory-of-mind using brain (Experiment 1) and behavioural (Experiment 2) measures. In a first exploratory experiment, we examine the relationship between dispositional anthropomorphism and activity within the theory-of-mind brain network (n = 108). Results from a Bayesian regression analysis showed no consistent relationship between dispositional anthropomorphism and activity in regions of the theory-of-mind network. In a follow-up, pre-registered experiment, we explored the relationship between theory-of-mind and situational and dispositional anthropomorphism in more depth. Participants (n = 311) watched a short movie while simultaneously completing situational anthropomorphism and theory-of-mind ratings, as well as measures of dispositional anthropomorphism and general theory-of-mind. Only situational anthropomorphism predicted the ability to understand and predict the behaviour of the film's characters. No relationship between situational or dispositional anthropomorphism and general theory-of-mind was observed. Together, these results suggest that while the constructs of anthropomorphism and theory-of-mind might overlap in certain situations, they remain separate and possibly unrelated at the personality level. These findings point to a possible dissociation between brain and behavioural measures when considering the relationship between theory-of-mind and anthropomorphism., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

The social motivation theory proposes that individuals naturally orient their attention to the social world. Research has documented the rewarding value of social stimuli, such as biological motion, to typically developed individuals. Here, we used complementary eye tracking measures to investigate how social motion cues affect attention and arousal. Specifically, we examined whether viewing the human body moving naturally versus mechanically leads to greater attentional engagement and changes in autonomic arousal (as assessed by pupil size measures). Participants completed an attentional disengagement task in two independent experiments, while pupillary responses were recorded. We found that natural, human-like motion produced greater increases in attention and arousal than mechanical motion, whether the moving agent was human or not. These findings contribute an important piece to our understanding of social motivation by demonstrating that human motion is a key social stimulus that engages visual attention and induces autonomic arousal in the viewer., (Copyright © 2019. Published by Elsevier B.V.)

Protecting men's power is fundamental to understanding the origin, expression, and targets of hostile sexism, yet no prior theoretical or empirical work has specified how hostile sexism is related to experiences of power. In the current studies, we propose that the interdependence inherent in heterosexual relationships will lead men who more strongly endorse hostile sexism to perceive they have lower power in their relationship, and that these perceptions will be biased. We also predicted that lower perceptions of power would in turn promote aggression toward intimate partners. Across 4 studies, men who more strongly endorsed hostile sexism perceived lower power in their relationships. Comparisons across partners supported that these lower perceptions of power were biased; men who more strongly endorsed hostile sexism underestimated the power they had compared with their partners' reports of that power (Studies 1 and 2). These lower perceptions of power, in turn, predicted greater aggression toward female partners during couples' daily interactions (Study 1), observed during couples' video-recorded conflict discussions (Study 2), and reported over the last year (Studies 3 and 4). Moreover, the associations between hostile sexism, power, and aggression were specific to men perceiving lower relationship power rather than desiring greater power in their relationships (Studies 3 and 4), and they were not the result of generally being more dominant and aggressive (Studies 3 and 4), or more negative relationship evaluations from either partner (Studies 1-4). The findings demonstrate the importance of an interdependence perspective in understanding the experiences, aggressive expressions, and broader consequences associated with hostile sexism. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

The Social Motivation Theory posits that a reduced sensitivity to the value of social stimuli, specifically faces, can account for social impairments in Autism Spectrum Disorders (ASD). Research has demonstrated that typically developing (TD) individuals preferentially orient towards another type of salient social stimulus, namely biological motion. Individuals with ASD, however, do not show this preference. While the reward value of faces to both TD and ASD individuals has been well-established, the extent to which individuals from these populations also find human motion to be rewarding remains poorly understood. The present study investigated the value assigned to biological motion by TD participants in an effort task, and further examined whether these values differed among individuals with more autistic traits. The results suggest that TD participants value natural human motion more than rigid, machine-like motion or non-human control motion, but this preference is attenuated among individuals reporting more autistic traits. This study provides the first evidence to suggest that individuals with more autistic traits find a broader conceptualisation of social stimuli less rewarding compared to individuals with fewer autistic traits. By quantifying the social reward value of human motion, the present findings contribute an important piece to our understanding of social motivation in individuals with and without social impairments., (Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.)

Benevolent sexism prescribes that men are dependent on women in relationships and should cherish their partners. The current research examined whether perceiving male partners to endorse benevolent sexism attenuates highly anxious women's negative reactions to relationship conflict. Greater attachment anxiety was associated with greater distress and insecurity during couples' conflict discussions (Study 1), during daily conflict with intimate partners (Study 2), and when recalling experiences of relationship conflict (Study 3). However, this heightened distress and insecurity was attenuated when women (but not men) perceived their partner to strongly endorse benevolent sexism (Studies 1-3) and thus believed their partner could be relied upon to remain invested (Study 3B). These novel results illustrate that perceiving partners to endorse benevolent sexism alleviates anxious women's insecure reactions to relationship threat by conveying partner's continued reliability. Implications of these security-enhancing effects are considered in light of the role benevolent sexism plays in sustaining gender inequality., (© 2016 by the Society for Personality and Social Psychology, Inc.)

The current research demonstrated that women's adoption of benevolent sexism is influenced by their perceptions of their intimate partners' agreement with benevolent sexism. In 2 dyadic longitudinal studies, committed heterosexual couples reported on their own sexism and perceptions of their partner's sexism twice across 9 months (Study 1) and 5 times across 1 year (Study 2). Women who perceived that their male partner more strongly endorsed benevolent sexism held greater and more stable benevolent sexism across time, whereas lower perceptions of partners' benevolent sexism predicted declines in women's benevolent sexism across time. Changes in men's endorsement of sexism were unrelated to perceptions of their partner's sexist attitudes. The naturalistic change in sexist attitudes shown in Studies 1 and 2 was supported by experimental evidence in Studies 3 and 4: Manipulations designed to increase perceptions of partner's benevolent sexism led women (but not men) to report greater benevolent sexism. Studies 3 and 4 also provided evidence that perceptions of partner's benevolent sexism fosters perceived regard and relationship security in women, but not men, and these relationship factors enhance attitude alignment. Discriminant analyses demonstrated that these effects were specific to women's perceptions of partner's, rather than societal, levels of sexism. In sum, these studies illustrate that women endorse benevolent sexism when they perceive that the reverence and security that benevolent sexism promises women are accessible in their relationships., ((c) 2016 APA, all rights reserved).)

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 beliefs while optimizing human-like design., (© 2015 The Authors.)

Cook et al. overstate the evidence supporting their associative account of mirror neurons in humans: most studies do not address a key property, action-specificity that generalizes across the visual and motor domains. Multivariate pattern analysis (MVPA) of neuroimaging data can address this concern, and we illustrate how MVPA can be used to test key predictions of their account.

Numerous studies have investigated proxemics in the context of human–robot interactions, but little is known about whether these insights can be applied to human–drone interactions (HDI). As drones become more common in social settings, it is crucial to ensure they navigate in a socially acceptable and human-friendly way. Understanding how individuals position themselves around drones is vital to promote user well-being and drones' social acceptance. However, real-world constraints and risks associated with drones flying in close proximity to participants have limited research in this field. Virtual reality is a promising alternative for investigating HDI, as prior research suggests. This paper presents a proxemic user study (N = 45) in virtual reality, examining how drone height and framing influence participants' proxemic preferences. The study also explores participants' perceptions of social drones and their vision for the future of flying robots. Our findings show that drone height significantly impacts participants' preferred interpersonal distance, while framing had no significant effect. Thoughts on how participants envision social drones (e.g., interaction, design, applications) reveal interpersonal differences but also shows overall consistency over time. While the study demonstrates the value of using virtual reality for HDI experiments, further research is necessary to determine the generalizability of our findings to real-world HDI scenarios. [ABSTRACT FROM AUTHOR]

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]

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]

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. [ABSTRACT FROM AUTHOR]

In order to interpret and engage with the social world, individuals must understand how they relate to others. Self--other understanding forms the backbone of social cognition and is a central concept explored by research into basic processes such as action perception and empathy, as well as research on more sophisticated social behaviours such as cooperation and intergroup interaction. This theme issue integrates the latest research into self--other understanding from evolutionary biology, anthropology, psychology, neuroscience and psychiatry. By gathering perspectives from a diverse range of disciplines, the contributions showcase ways in which research in these areas both informs and is informed by approaches spanning the biological and social sciences, thus deepening our understanding of how we relate to others in a social world. [ABSTRACT FROM AUTHOR]

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 sensitive and appropriate categorical comparisons (human, animal, tool, or 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. As robots become increasingly present in human society, considerable gaps remain between expectations for the social roles these robots might play and their actual abilities. Research examining social cognition when interacting with robots offers a promising avenue for understanding how best to introduce robots to complex social settings, such as in schools, hospitals, and at home. Thanks to methodological advances in human neuroscience, such as mobile neuroimaging, human–robot interaction research is moving out of the laboratory and into the real world. [ABSTRACT FROM AUTHOR]