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The present study was aimed at determining the age and gender distribution of the humanoid robots in the ABOT dataset, and providing a systematic data-driven formalization of the process of age and gender categorization of humanoid robots. We involved 153 participants in an online study and asked them to rate the humanoid robots in the ABOT dataset in terms of perceived age, femininity, masculinity, and gender neutrality. Our analyses disclosed that most of the robots in the ABOT dataset were perceived as young adults, and the vast majority of them were attributed a neutral or masculine gender. By merging our data with the data in the ABOT dataset, we discovered that humanlikeness is crucial to elicit social categorization. Moreover, we found out that body manipulators (e.g., legs, torso) guide the attribution of masculinity, surface look features (e.g., eyelashes, apparel) the attribution of femininity, and that robots without facial features (e.g., head, eyes) are perceived as older. Finally, yet importantly, we unveiled that men tend to attribute lower age scores and higher femininity ratings to humanoid robots than women. Our work provides evidence of an existing underlying bias in the design of humanoid robots that needs to be addressed: the under-representation of feminine robots and lack of representation of androgynous ones. We make the results of this study publicly available to the HRI community by attaching the dataset we collected to the present paper and creating a dedicated website.

BACKGROUND:The phenomenon of cyberbullying is on the rise among adolescents and in schools. OBJECTIVE: To evaluate the relationship between personality characteristics such as empathy, the tendency to implement cognitive mechanisms aimed at moral disengagement, and the use of social media. PARTICIPANTS: Italian students from first to fifth year in high school classes (n = 264). METHODS: A questionnaire was used to gather information on the sociodemographic characteristics of the participants, their use of social media, their level of empathy (Basic Empathy Scale, BES), and mechanisms of moral disengagement (Moral Disengagement Scale MDS). Two questions were included to determine whether each participant had ever been a victim of or witness to cyberbullying. RESULTS: Results suggest that offensive behaviors are related to mechanisms of moral disengagement and to interaction using forms of communication that allow anonymity. In addition, offensive behavior appears to be related to forms of Internet addiction, while prosocial behavior is linked with cognitive empathy. CONCLUSION: In order to promote the establishment of prosocial behavior, it would seem necessary for the various players involved -schools, parents, social network developers -to make an effort to implement educational environments and virtual social networks based on a hypothesis of "design for reflection", educating young people about the need to take the time to understand their feelings and relationships expressed via social media.

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