Why That Robot? A Qualitative Analysis of Justification Strategies for Robot Color Selection Across Occupational Contexts
Jiangen He, Wanqi Zhang, Jessica K. Barfield

TL;DR
This study explores how users justify robot color choices across occupations, revealing biases, stereotype influences, and the impact of robot appearance on reasoning strategies, with implications for reducing societal biases.
Contribution
It introduces a comprehensive qualitative analysis of human justification strategies for robot color selection, highlighting bias mechanisms and design considerations in HRI.
Findings
Functionalism is the dominant justification strategy (52%)
Racial stereotypes influence color choices even when not consciously recognized
Robot anthropomorphism shifts reasoning from functional to de-racialized explanations
Abstract
As robots increasingly enter the workforce, human-robot interaction (HRI) must address how implicit social biases influence user preferences. This paper investigates how users rationalize their selections of robots varying in skin tone and anthropomorphic features across different occupations. By qualitatively analyzing 4,146 open-ended justifications from 1,038 participants, we map the reasoning frameworks driving robot color selection across four professional contexts. We developed and validated a comprehensive, multidimensional coding scheme via human--AI consensus (). Our results demonstrate that while utilitarian \textit{Functionalism} is the dominant justification strategy (52\%), participants systematically adapted these practical rationales to align with established racial and occupational stereotypes. Furthermore, we reveal that bias frequently operates beneath…
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