Not All Robots are Evaluated Equally: The Impact of Morphological Features on Robots’ Assessment through Capability Attributions

Author:

Kunold Laura1ORCID,Bock Nikolai2ORCID,Rosenthal-von der Pütten Astrid2ORCID

Affiliation:

1. Ruhr University Bochum, Bochum, Germany

2. RWTH Aachen University, Aachen, Germany

Abstract

Favorable assessments of social robots are addressed in several research and development attempts because positive attitudes and intentions towards technology are regarded as a necessary prerequisite for usage. To predict a favorable evaluation, it is inevitable to understand the appraisal process and determine crucial variables that affect the evaluative and behavioral consequences of HRI. Robotic morphology has been identified as one of these variables. In the present work, we expand previous work by demonstrating that capability attributions associated with robots’ morphological features explain variations in evaluations. Based on two large picture-based online studies (Study 1, n = 673; Study 2, n = 586) we show that robots with similar morphological features (e.g., robots with arms and grippers) can be clustered along their assigned capabilities, and that these capabilities (e.g., to manipulate objects) explain evaluations of the robots in terms of acceptance and social attributes (i.e., warmth, competence, and discomfort). We discuss whether these initial assessments are relevant to live interactions and how our results can inform robot design.

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Human-Computer Interaction

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1. A Survey on Dialogue Management in Human-robot Interaction;ACM Transactions on Human-Robot Interaction;2024-06-14

2. RoSI: A Model for Predicting Robot Social Influence;ACM Transactions on Human-Robot Interaction;2024-06-14

3. A Pilot Investigation of Human Preference for Robot Arm Visual Form;Companion of the 2024 ACM/IEEE International Conference on Human-Robot Interaction;2024-03-11

4. “Ick bin een Berlina”: dialect proficiency impacts a robot’s trustworthiness and competence evaluation;Frontiers in Robotics and AI;2024-01-29

5. A Framework to Study and Design Communication with Social Robots;Robotics;2022-11-15

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