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Mistakes, failures, and transgressions committed by a robot are inevitable as robots become more involved in our society. When a wrong behavior occurs, it is important to understand what factors might affect how the robot is perceived by people. In this paper, we investigated how the type of transgressor (human or robot) and type of backstory depicting the transgressor's mental capabilities (default, physio-emotional, socio-emotional, or cognitive) shaped participants' perceptions of the transgressor's morality. We performed an online, between-subjects study in which participants (N=720) were first introduced to the transgressor and its backstory, and then viewed a video of a real-life robot or human pushing down a human. Although participants attributed similarly high intent to both the robot and the human, the human was generally perceived to have higher morality than the robot. However, the backstory that was told about the transgressors' capabilities affected their perceived morality. We found that robots with emotional backstories (i.e., physio-emotional or socio-emotional) had higher perceived moral knowledge, emotional knowledge, and desire than other robots. We also found that humans with cognitive backstories were perceived with less emotional and moral knowledge than other humans. Our findings have consequences for robot ethics and robot design for HRI. 

We expect children to learn new words, skills, and ideas from various technologies. When learning from humans, children prefer people who are reliable and trustworthy, yet children also forgive people's occasional mistakes. Are the dynamics of children learning from technologies, which can also be unreliable, similar to learning from humans? We tackle this question by focusing on early childhood, an age at which children are expected to master foundational academic skills. In this project, 168 4–7-year-old children (Study 1) and 168 adults (Study 2) played a word-guessing game with either a human or robot. The partner first gave a sequence of correct answers, but then followed this with a sequence of wrong answers, with a reaction following each one. Reactions varied by condition, either expressing an accident, an accident marked with an apology, or an unhelpful intention. We found that older children were less trusting than both younger children and adults and were even more skeptical after errors. Trust decreased most rapidly when errors were intentional, but only children (and especially older children) outright rejected help from intentionally unhelpful partners. As an exception to this general trend, older children maintained their trust for longer when a robot (but not a human) apologized for its mistake. Our work suggests that educational technology design cannot be one size fits all but rather must account for developmental changes in children's learning goals. 

Pretend play is a ubiquitous learning tool in early childhood, enabling children to explore possibilities outside of their current reality. Here, we demonstrate how pretend play can be leveraged to empower girls in scientific domains. American children ages 4 to 7 years ( N = 240) played a challenging science activity in one of three conditions. Children in the exposure condition heard about a successful gender-matched scientist, children in the roleplay condition pretended to be that scientist, and children in the baseline condition did not receive information about the scientist. Girls in the roleplay condition, but not in the exposure condition, persisted longer in the science activity than girls in the baseline condition. Pretending to be the scientist equated girls’ persistence to that of boys. These findings suggest that pretend play of role models motivates young girls in science and may help reduce gender gaps from their roots.