Recent technological developments in robotics has driven the design and production of different humanoid robots. Several studies have highlighted that the presence of human-like physical features could lead both adults and children to anthropomorphize the robots. In the present study we aimed to compare the attribution of mental states to two humanoid robots, NAO and Robovie, which differed in the degree of anthropomorphism. Children aged 5, 7, and 9 years were required to attribute mental states to the NAO robot, which presents more human-like characteristics compared to the Robovie robot, whose physical features look more mechanical. The results on mental state attribution as a function of children’s age and robot type showed that 5-year-olds have a greater tendency to anthropomorphize robots than older children, regardless of the type of robot. Moreover, the findings revealed that, although children aged 7 and 9 years attributed a certain degree of human-like mental features to both robots, they attributed greater mental states to NAO than Robovie compared to younger children. These results generally show that children tend to anthropomorphize humanoid robots that also present some mechanical characteristics, such as Robovie. Nevertheless, age-related differences showed that they should be endowed with physical characteristics closely resembling human ones to increase older children’s perception of human likeness. These findings have important implications for the design of robots, which also needs to consider the user’s target age, as well as for the generalizability issue of research findings that are commonly associated with the use of specific types of robots.

Studying trust in the context of human-robot interaction is of great importance given the increasing relevance and presence of robotic agents in the social sphere, including educational and clinical. We investigated the acquisition, loss, and restoration of trust when preschool and school-age children played with either a human or a humanoid robot in vivo. The relationship between trust and the representation of the quality of attachment relationships, Theory of Mind, and executive function skills was also investigated. Additionally, to outline children's beliefs about the mental competencies of the robot, we further evaluated the attribution of mental states to the interactive agent. In general, no substantial differences were found in children's trust in the play partner as a function of agency (human or robot). Nevertheless, 3-year-olds showed a trend toward trusting the human more than the robot, as opposed to 7-year-olds, who displayed the reverse pattern. These findings align with results showing that, for 3-and 7-yearolds, the cognitive ability to switch was significantly associated with trust restoration in the human and the robot, respectively. Additionally, supporting previous findings, we found a dichotomy between attributions of mental states to the human and robot and children's behavior: while attributing to the robot significantly lower mental states than the human, in the Trusting Game, children behaved in a similar way when they related to the human and the robot. Altogether, the results of this study highlight that similar psychological mechanisms are at play when children are to establish a novel trustful relationship with a human and robot partner. Furthermore, the findings shed light on the interplay-during development-between children's quality of attachment relationships and the development of a Theory of Mind, which act differently on trust dynamics as a function of the children's age as well as the interactive partner's nature (human vs. robot).

Studying trust within human-robot interaction is of great importance given the social relevance of robotic agents in a variety of contexts. We investigated the acquisition, loss and restoration of trust when preschool and school-age children played with either a human or a humanoid robot in-vivo. The relationship between trust and the quality of attachment relationships, Theory of Mind, and executive function skills was also investigated. No differences were found in children’s trust in the play-partner as a function of agency (human or robot). Nevertheless, 3-years-olds showed a trend toward trusting the human more than the robot, while 7-years-olds displayed the reverse behavioral pattern, thus highlighting the developing interplay between affective and cognitive correlates of trust.

Attributing mental states to others, such as feelings, beliefs, goals, desires, and attitudes, is an important interpersonal ability, necessary for adaptive relationships, which underlies the ability to mentalize. To evaluate the attribution of mental and sensory states, a new 23-item measure, the Attribution of Mental States Questionnaire (AMS-Q), has been developed. The present study aimed to investigate the dimensionality of the AMS-Q and its psychometric proprieties in two studies. Study 1 focused on the development of the questionnaire and its factorial structure in a sample of Italian adults (N = 378). Study 2 aimed to confirm the findings in a new sample (N = 271). Besides the AMS-Q, Study 2 included assessments of Theory of Mind (ToM), mentalization, and alexithymia. A Principal Components Analysis (PCA) and a Parallel Analysis (PA) of the data from Study 1 yielded three factors assessing mental states with positive or neutral valence (AMS-NP), mental states with negative valence (AMS-N), and sensory states (AMS-S). These showed satisfactory reliability indexes. AMS-Q’s whole-scale internal consistency was excellent. Multigroup Confirmatory Factor Analysis (CFA) further confirmed the three-factor structure. The AMS-Q subscales also showed a consistent pattern of correlation with associated constructs in the theoretically predicted ways, relating positively to ToM and mentalization and negatively to alexithymia. Thus, the questionnaire is considered suitable to be easily administered and sensitive for assessing the attribution of mental and sensory states to humans. The AMS-Q can also be administered with stimuli of nonhuman agents (e.g., animals, inanimate things, and even God); this allows the level of mental anthropomorphization of other agents to be assessed using the human as a term of comparison, providing important hints in the perception of nonhuman entities as more or less mentalistic compared to human beings, and identifying what factors are required for the attribution of human mental traits to nonhuman agents, further helping to delineate the perception of others’ minds.

Including robots in children's lives calls for reflection on the psychological and moral aspects of such relationships, especially with respect to children's ability to differentiate intentional from unintentional false statements, that is, lies from mistakes. This ability calls for an understanding of an interlocutor's intentions. This study examined the ability of 5‐6‐year‐olds to recognize, and morally evaluate, lies and mistakes produced by a human as compared to a NAO robot, and to attribute relevant emotions to the deceived party. Irrespective of the agent, children had more difficulty in understanding mistakes than lies. In addition, they were disinclined to attribute a lie to the robot. Children's age and their understanding of intentionality were the strongest predictors of their performance on the lie‐mistake task. Children's Theory of Mind, but not their executive function skills, also correlated with their performance. Our findings suggest that, regardless of age, a robot is perceived as an intentional agent. Robot behaviour was more acceptable for children because his actions could be attributed to someone who programmed it to act in a specific way. Highlights The ability to recognize an intention to lie or not in different agents represents a significant developmental step. Children saw a human/robot making intentionally or unintentionally false statements, and understanding the mistake was more difficult than the lie. Robots may be associated with the human concept by younger children with important implications for use of cHRI in education.