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Blurring Human–Machine Distinctions: Anthropomorphic Appearance in Social Robots as a Threat to Human Distinctiveness


The present research aims at gaining a better insight on the psychological barriers to the introduction of social robots in society at large. Based on social psychological research on intergroup distinctiveness, we suggested that concerns toward this technology are related to how we define and defend our human identity. A threat to distinctiveness hypothesis was advanced. We predicted that too much perceived similarity between social robots and humans triggers concerns about the negative impact of this technology on humans, as a group, and their identity more generally because similarity blurs category boundaries, undermining human uniqueness. Focusing on the appearance of robots, in two studies we tested the validity of this hypothesis. In both studies, participants were presented with pictures of three types of robots that differed in their anthropomorphic appearance varying from no resemblance to humans (mechanical robots), to some body shape resemblance (biped humanoids) to a perfect copy of human body (androids). Androids raised the highest concerns for the potential damage to humans, followed by humanoids and then mechanical robots. In Study 1, we further demonstrated that robot anthropomorphic appearance (and not the attribution of mind and human nature) was responsible for the perceived damage that the robot could cause. In Study 2, we gained a clearer insight in the processes underlying this effect by showing that androids were also judged as most threatening to the human–robot distinction and that this perception was responsible for the higher perceived damage to humans. Implications of these findings for social robotics are discussed.

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  9. This factor also included an item assessing human qualities attributed to robots. This item will not be considered further as it is not relevant to assess support for the current hypotheses.

  10. Part of these data were also used in Ferrari and Paladino (2014)—a study that focused on validating the scale develoepd by Kamide and colleagues in an Italian sample.

  11. In Study 1, participants were also asked to record their highest level of education to date (\(N = 3\) ‘secondary school’, \(N = 60\) ‘high school’, \(N = 32\) ‘bachelor degree’, \(N = 68\) ‘master degree’, \(N = 16\) ‘Phd or superior degree’, and 3 missing). Exploratory analyses were conducted exploring the role of educational level on the two main dependent variables of Study 1: robot anthropomorphic appearance and damage to humans. Specifically, in the ANOVAs, participants level of education was included as a covariate or as a factor (recoded whereby 0 = high school degree or lower, \(N = 63\); 1 = university degree or higher, \(N = 116\)). No significant effects were obtained for level of education and results for anthropomorphic appearance (all \(ps > .16\)) and for damage to humans and their identity (all \(ps > .55\)) were unaffected by inclusion of education in the analysestext.

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  16. Exploratory analysis indicated that Humanity Esteem did not moderate any of the findings. For the sake of brevity, these results are therefore not presented.

  17. Initially there was a fourth item (“This type of robot highlights that there are clear differences between humans and machines”) that we excluded it to increase the reliability of undermining to human–machine distinctiveness scale.


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The research for this paper was financially supported by a doctorate grant awarded by the University of Trento to F. Ferrari. Portions of the data of Study 1 have been analyzed for a different purpose and presented in form of a proceeding at “Evaluating Social Robts”, The 13th International Conference on Intelligent Autonomous System, July 18, 2014, Padova, Italy.

Authors contribution Francesco Ferrari, Maria Paola Paladino and Jolanda Jetten developed the study concept. Francesco Ferrari and Maria Paola Paladino designed the studies. Francesco Ferrari prepared the experimental material, collected and analyzed the data. Francesco Ferrari and Maria Paola Paladino drafted the manuscript. Jolanda Jetten edited and contributed to the critical revisions of the manuscript. All the authors read and approved the final version for submission.

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Correspondence to Maria Paola Paladino.

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Ferrari, F., Paladino, M.P. & Jetten, J. Blurring Human–Machine Distinctions: Anthropomorphic Appearance in Social Robots as a Threat to Human Distinctiveness. Int J of Soc Robotics 8, 287–302 (2016).

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