This dissertation’s aim is to improve the understanding of the credibility attribution process toward social robots. Their intended use as information-sharing agents in educational institutions, retail stores, or at home results in the apparent need to comprehend users’ ways of evaluating the suitability of social robots as a source of information. This applies in particular because credibility is not a static feature of a robot but an ascription that is depending on users’ perceptions. Thus, misattributions can occur that either impair the credibility of well-designed robotic systems or create unjustified good credibility ratings of questionably programmed robots. As a result, the potential influence of highly credible robots has severe implications if it is used to manipulate people’s behavior in favor of a third party’s interests or if it determines how much of the informational content of the robot is consumed. Thus, understanding the credibility attribution process toward social robots is crucial in order to provide guidance for users to avoid misattributions of credibility as well as unfavorable behavioral decisions. Based on theoretical arguments, the credibility attribution process is assumed to be influenced not exclusively by the features of a respective robot itself, such as its design or mentalizing abilities, but also by user-related characteristics such as a person’s reliance on technology as well as by the context in which an interaction takes place, for example, a setting where a robot is used for recommending a company’s own products. Additionally, the attribution of credibility is connected with the way a robot’s information is used for upcoming behavioral decisions. These decisions can be as simple as whether to purchase a product recommended by a robot or whether to continue an interaction with it. Since all three factors, the robot-related, the user-related, and the context-related one are supposed to explain the outcome of people’s credibility evaluations as well as the behavioral ...
Credibility Attributions in Human-Robot Interactions: Empirical Investigations on Users’ Perceptions of Social Robots as a Source of Information
2024-02-16
Theses
Electronic Resource
English
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