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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.

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User-Centered Design puts the users at the center of the design activity by involving them from the very beginning in the process and by iteratively testing and re-designing the product. In every testing and evaluation phase human error analysis plays an important role. Although it is not possible to design systems in which people do not make errors, much can be done to minimize the incidence of error, to maximize error detection, and to make easier error recovery. However, the qualitative analysis on human error has not received the attention that it deserves. In the paper the main features of the user-centered approach are sketched and a set of guidelines for handling human error is presented. An example drawn from our design experience is reported for each guideline.

The Zöllner illusion has been accounted for in terms of local interactions between the vertical lines and the crossing segments. Recently, however, some evidence supporting the importance of global figural characteristics--ie of figural elements that are not directly interacting with the test lines--in the occurrence of orientation illusions has been reported. Three experiments have been conducted with parts of the Zöllner figure to test whether this illusion is affected by the global figural characteristics. The results indicate that, similarly to what has been observed for other orientation illusions, the Zöllner illusion depends on both local and global characteristics of the stimulus configuration. In addition, results suggest a similar weight for both these figural characteristics in determining the occurrence of the illusory effect. Finally, relations among different orientation illusions are also discussed.