Robots as Malevolent Moral Agents: Harmful Behavior Results in Dehumanization,Not Anthropomorphism

A robot's decision to harm a person is sometimes considered to be the ultimate proof of it gaining a human-like mind. Here, we contrasted predictions about attribution of mental capacities from moral typecasting theory, with the denial of agency from dehumanization literature. Experiments 1 and 2 investigated mind perception for intentionally and accidentally harmful robotic agents based on text and image vignettes. Experiment 3 disambiguated agent intention (malevolent and benevolent), and additionally varied the type of agent (robotic and human) using short computer-generated animations. Harmful robotic agents were consistently imbued with mental states to a lower degree than benevolent agents, supporting the dehumanization account. Further results revealed that a human moral patient appeared to suffer less when depicted with a robotic agent than with another human. The findings suggest that future robots may become subject to human-like dehumanization mechanisms, which challenges the established beliefs about anthropomorphism in the domain of moral interactions.     

Education biases perception of social robots

IntroductionRecent research on human–robot interactions (HRI) emphasizes a role of user's attitudes in perceiving robot's with different robot embodiments of varying levels of human likenesses. However, other human factors such as educational background may also help understanding of what conditions contribute to enhance social perception of robot's features.ObjectivesThis study aimed to determine how people's attitudes towards and familiarization with robots influence social perception of particular features of robots.MethodFirst, we measured attitudes towards robots among undergraduate students with diverse educational background (engineering vs. psychology). Then, participants were presented with short movies showing the behaviour of three robots with different levels of sociability. Finally, participants evaluated the characteristics of these robots on a scale.ResultsPeople more familiar with social robots and with more positive attitudes towards them evaluate robots with human traits more highly.ConclusionHuman perception of social robots resembles social phenomena related to human perception of other people.     

Constrained Choice: Children's and Adults’ Attribution of Choice to a Humanoid Robot

Young children, like adults, understand that human agents can flexibly choose different actions in different contexts, and they evaluate these agents based on such choices. However, little is known about children's tendencies to attribute the capacity to choose to robots, despite increased contact with robotic agents. In this paper, we compare 5- to 7-year-old children's and adults’ attributions of free choice to a robot and to a human child by using a series of tasks measuring agency attribution, action prediction, and choice attribution. In morally neutral scenarios, children ascribed similar levels of free choice to the robot and the human, while adults were more likely to ascribe free choice to the human. For morally relevant scenarios, however, both age groups considered the robot's actions to be more constrained than the human's actions. These findings demonstrate that children and adults hold a nuanced understanding of free choice that is sensitive to both the agent type and constraints within a given scenario.     

Seeing the mind of robots: Harm augments mind perception but benevolent intentions reduce dehumanisation of artificial entities in visual vignettes

According to moral typecasting theory, good- and evil-doers (agents) interact with the recipients of their actions (patients) in a moral dyad. When this dyad is completed, mind attribution towards intentionally harmed liminal minds is enhanced. However, from a dehumanisation view, malevolent actions may instead result in a denial of humanness. To contrast both accounts, a visual vignette experiment (N = 253) depicted either malevolent or benevolent intentions towards robotic or human avatars. Additionally, we examined the role of harm-salience by showing patients as either harmed, or still unharmed. The results revealed significantly increased mind attribution towards visibly harmed patients, mediated by perceived pain and expressed empathy. Benevolent and malevolent intentions were evaluated respectively as morally right or wrong, but their impact on the patient was diminished for the robotic avatar. Contrary to dehumanisation predictions, our manipulation of intentions failed to affect mind perception. Nonetheless, benevolent intentions reduced dehumanisation of the patients. Moreover, when pain and empathy were statistically controlled, the effect of intentions on mind perception was mediated by dehumanisation. These findings suggest that perceived intentions might only be indirectly tied to mind perception, and that their role may be better understood when additionally accounting for empathy and dehumanisation.     

Validation of the Portuguese version of the Negative Attitudes towards Robots Scale

IntroductionSocial robots are robots capable of a peer-to-peer communication with humans. Nomura, Kanda, and Suzuki (2004) developed the Negative Attitude towards Robots Scale (NARS) to measure the attitudes towards robots. NARS proved to be a useful tool to study human-robot interaction.ObjectiveTo assess the psychometric properties of the Portuguese version of the NARS (PNARS).Method and resultsFour studies were conducted. In study 1 (n = 300), a principal component analysis showed that PNARS comprised two components: the negative attitudes towards robots with human traits (NARHT) and towards interaction with robots (NATIR). In study 2 (n = 536), a confirmatory factorial analysis was conducted. Results confirmed the two-factor solution of PNARS obtained in study 1. Study 3 (n = 107) tested the nomological validity of PNARS and showed that PNARS, NARHT and NATIR correlated with attitudes towards technology. Study 4 (n = 59) tested the predictive validity of PNARS and showed that scores on NARHT and NATIR predicted the future intention to work with a social robot and its affective and cognitive antecedents.ConclusionGlobally, results indicate that PNARS is a reliable instrument to use in human-robot interaction studies.     

Remote control and children's understanding of robots

Children use goal-directed motion to classify agents as living things from early in infancy. In the current study, we asked whether preschoolers are flexible in their application of this criterion by introducing them to robots that engaged in goal-directed motion. In one case the robot appeared to move fully autonomously, and in the other case it was controlled by a remote. We found that 4- and 5-year-olds attributed fewer living thing properties to the robot after seeing it controlled by a remote, suggesting that they are flexible in their application of the goal-directed motion criterion in the face of conflicting evidence of living thing status. Children can flexibly incorporate internal causes for an agent’s behavior to enrich their understanding of novel agents.     

Making sense of social robots: A structural analysis of the layperson's social representation of robots

IntroductionGiven their novelty, social robots (i.e., robots using natural language, displaying and recognizing emotions) will generate uncertainty among users. Social representations allow making sense of the new, drawing from existing knowledge.ObjectiveA free association questionnaire was administered to 212 Portuguese adults to identify the social representation of robot.MethodData was analysed with EVOC 2000 and SIMI 2000 software.ResultsThe social representation of robot is organized around the ideas of technology, help and future. Differences in the representation according to age, gender and level of education where also identified.ConclusionThe social representation of robot is marked by the conception of it as a tool. This contrasts with the concept of social robots as social agents. Implications for social robot's acceptance are discussed.