AUTHOR=Manzi Federico , Peretti Giulia , Di Dio Cinzia , Cangelosi Angelo , Itakura Shoji , Kanda Takayuki , Ishiguro Hiroshi , Massaro Davide , Marchetti Antonella TITLE=A Robot Is Not Worth Another: Exploring Children’s Mental State Attribution to Different Humanoid Robots JOURNAL=Frontiers in Psychology VOLUME=11 YEAR=2020 URL=https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2020.02011 DOI=10.3389/fpsyg.2020.02011 ISSN=1664-1078 ABSTRACT=

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.