Predicting prejudice from empathy : a multiple regression analysis

Past research has demonstrated that empathy can reduce prejudicial attitudes as it leads people to share a sense of common identity with other cultural groups (Stephan & Finlay, 1999) or by arousing feelings of injustice (Finlay & Stephan, 2000). However, the current volume of research largely centers around administering empathy-inducing scenarios to participants and then assessing levels of prejudicial attitudes as opposed to examining initial levels of empathy. In addition, there is a lack of research regarding modern prejudicial attitudes towards individuals of Aboriginal descent. The present study examines the predictive value of ethnocultural empathy, age, gender, and social desirability on the levels of those prejudicial attitudes. One hundred and sixty eight undergraduate students from the University of Saskatchewan completed a questionnaire, including the Scale of Ethnocultural Empathy (Wang, Davidson, Yakushko, Savoy, Tan, & Bleier, 2003), the Prejudiced Attitudes Towards Aboriginals Scale (Morrison, 2007), and Form C of the Marlowe Crowne Social Desirability Scale (Reynolds, 1982). The multiple regression analysis revealed that ethnocultural empathy and age were predictive of modern prejudicial attitudes toward Aboriginals. Participants with higher levels of ethnocultural empathy reported reduced levels of modern prejudicial attitudes. However, contrary to expectation, gender was not a significant predictor variable. Practical applications and limitations of these findings are discussed as well as directions for future research

Effects of Victim Gendering and Humanness on People’s Responses to the Physical Abuse of Humanlike Agents

With the deployment of robots in public realms, researchers are seeing more cases of abusive disinhibition towards robots. Because robots embody gendered identities, poor navigation of antisocial dynamics may reinforce or exacerbate gender-based marginalization. Consequently, it is essential for robots to recognize and effectively head off abuse. Given extensions of gendered biases to robotic agents, as well as associations between an agent\u27s human likeness and the experiential capacity attributed to it, we quasi-manipulated the victim\u27s humanness (human vs. robot) and gendering (via the inclusion of stereotypically masculine vs. feminine cues in their presentation) across four video-recorded reproductions of the interaction. Analysis from 422 participants, each of whom watched one of the four videos, indicates that intensity of emotional distress felt by an observer is associated with their gender identification and support for social stratification, along with the victim\u27s gendering—further underscoring the criticality of robots\u27 social intelligence

Sketching the contours of state authenticity

We outline a program of research in which we examined state authenticity, the sense of being one’s true self. In particular, we describe its phenomenology (what it feels like to be experience authenticity), its correlates(e.g.,emotions,needs),itsnomologicalnetwork(e.g.,real-idealselfoverlap,publicandprivate self-consciousness), its cultural parameters (Easter and Western culture), its precursors or determinants (congruency, positivity, and hedonism), and its psychological health implications. We conclude by arguing that state authenticity deserves its own conceptual status, distinct from trait authenticity, and by setting an agenda for future research

A Systematic Review on Social Robots in Public Spaces: Threat Landscape and Attack Surface

There is a growing interest in using social robots in public spaces for indoor and outdoor applications. The threat landscape is an important research area being investigated and debated by various stakeholders. Objectives: This study aims to identify and synthesize empirical research on the complete threat landscape of social robots in public spaces. Specifically, this paper identifies the potential threat actors, their motives for attacks, vulnerabilities, attack vectors, potential impacts of attacks, possible attack scenarios, and mitigations to these threats. Methods: This systematic literature review follows the guidelines by Kitchenham and Charters. The search was conducted in five digital databases, and 1469 studies were retrieved. This study analyzed 21 studies that satisfied the selection criteria. Results: Main findings reveal four threat categories: cybersecurity, social, physical, and public space. Conclusion: This study completely grasped the complexity of the transdisciplinary problem of social robot security and privacy while accommodating the diversity of stakeholders’ perspectives. Findings give researchers and other stakeholders a comprehensive view by highlighting current developments and new research directions in this field. This study also proposed a taxonomy for threat actors and the threat landscape of social robots in public spaces.publishedVersio

ロボットナビゲーションにおける人間への意図伝達に関する研究

早大学位記番号:新7327早稲田大