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The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
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Reproducibility in Human-Robot Interaction: Furthering the Science of HRI.

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Area of Science:

  • Human-Robot Interaction (HRI)
  • Robotics
  • Artificial Intelligence
  • Psychology

Background:

  • Reproducibility is vital for scientific progress in Human-Robot Interaction (HRI), mirroring advancements in AI, robotics, and psychology.
  • The HRI community has prioritized reproducibility, evidenced by the 2020 ACM/IEEE International Conference on Human-Robot Interaction's dedicated theme.

Purpose of the Study:

  • To review the current status of research reproducibility in Human-Robot Interaction (HRI).
  • To identify challenges unique to ensuring reproducibility in the interdisciplinary field of HRI.
  • To propose actionable recommendations for enhancing reproducibility within the HRI community.

Main Methods:

  • Literature review focusing on the state of reproducibility in HRI.
  • Analysis of challenges stemming from the interdisciplinary nature of HRI and technological artifacts.
  • Examination of biases in research evaluation and practices affecting reproducibility.

Main Results:

  • The field of HRI faces unique reproducibility challenges due to its interdisciplinary nature and reliance on physical artifacts.
  • Existing biases in research evaluation and practices hinder efforts to support reproducibility.
  • Current researcher training may not adequately foster the practice of research reproduction.

Conclusions:

  • Addressing biases and adapting researcher training are essential steps to improve HRI reproducibility.
  • Implementing proposed solutions can provide valuable guidelines for the HRI community and related scientific fields.
  • Enhancing reproducibility will accelerate the maturation of scientific knowledge in Human-Robot Interaction.