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Robots interacting with humans in public spaces often need to collect users' private information in order to provide the required services. Current privacy legislation in major jurisdictions requires organisations to disclose information about their data collection process and obtain user's consent prior to collecting privacy sensitive information. In this study, we consider a privacy-sensitive design of a data collection system for face identification. We deployed a face enrolment system on a humanoid robot with human-like gesturing and speech. We compared it with an equivalent system, in terms of capability and interactive process, on a screen-based interactive kiosk. In our previous contribution, we investigated the effects that embodiment has on users' privacy considerations. We found that an embodied humanoid robot is capable of collecting more private information from users in comparison to a disembodied interactive kiosk. However, this effect was statistically significant only when the two compared systems were using a transparent interface, i.e. an interface communicating to users the privacy policies for data processing and storage. Thus, in this work, we aim to further investigate the effects of transparency on users' privacy considerations and their experience with robot applications. We found that when comparing a non-transparent vs. transparent interface within the same system (i.e. on an embodied robot or on a disembodied kiosk) transparency does not lead to significant effects on users' privacy considerations. However, we found that transparency leads to a significantly better user experience for both systems. Therefore, our overall analyses suggest that both the interactive robot and the interactive kiosk are capable of enhancing the user experience by providing transparent information to users, which is required by privacy legislation. However, an interactive kiosk providing transparent information elicits significantly more privacy concerns in users as compared to the robot supplying the very same transparent information. This exploratory study provides conclusions that provide valuable insights for designing robot applications dealing with users privacy and it discusses the related legal implications, concluding with recommendations for privacy policymakers. [ABSTRACT FROM AUTHOR]

This study addresses how people perceive self-directed actions. Self-directed actions are behaviors performed by an individual (the actor) toward himself or herself. These behaviors include encouraging or controlling oneself. Affect Control Theory (ACT) makes predictions about behaviors and emotions based on confirmation of affective meanings. Previous research by Britt and Heise (1992) explored self-directed actions using ACT. This theory allows researchers to quantify affect and mathematically model affective processes. For this study, new affective meanings of self-directed actions were collected using a research design similar to Britt and Heise (1992) but with some improvements. The primary improvement on the previous research design is the use of a new sentence structure for behaviors that differentiates self-directed actions from social actions. These improvements produced significant differences from previously collected affective meanings and models of self-directed actions. The data indicate that actors perceive self-directed and social actions differently. In addition, new models of self-directed actions are significantly different from previous models but share similar patterns as models of social actions. ..PAT.-Unpublished Manuscript [ABSTRACT FROM AUTHOR]

The integration of social robots within service industries requires social robots to be persuasive. We conducted a vignette experiment to investigate the persuasiveness of a human, robot, and an information kiosk when offering consumers a restaurant recommendation. We found that embodiment type significantly affects the persuasiveness of the agent, but only when using a specific recommendation sentence. These preliminary results suggest that human-like features of an agent may serve to boost persuasion in recommendation systems. However, the extent of the effect is determined by the nature of the given recommendation. [ABSTRACT FROM AUTHOR]

This study uses Affect Control Theory and a series of simulations to predict emotions that people will experience as a result of behaviors focused toward others (social) or toward oneself (reflexive). Exploring the differences between emotion predictions of social events and reflexive events informs researchers of how social and reflexive behaviors impact an actor's feelings of self and the effectiveness of using particular behaviors to manage emotions. Using identical social and reflexive behaviors, with appropriate equations (Heise 1991; Clark 2008; Averett and Heise 1987), predictions indicate that social events tend to produce emotions with positive EPA ratings while reflexive events tend to produce emotions with negative EPA ratings. Results suggest that individuals who are social will improve their emotions and those that are not social, and thus performing more reflexive behaviors, will dampen or diminish their emotions. Also, reflexive behaviors may be more focused on bringing down one's emotions after experiencing abnormally positive emotions. Implications for emotional change are discussed as well as issues concerning simulation methodology in Affect Control Theory. [ABSTRACT FROM AUTHOR]