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IMPLICIT BIAS IN HIRING: LEVERAGING AVATARS TO FOSTER INCLUSIVE HIRING PRACTICES
Trifilo, Alexa S.
Trifilo, Alexa S.
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2025-05
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Business Administration/Interdisciplinary
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https://doi.org/10.34944/rw6e-7e87
Abstract
Imagine a world where the brilliance of a mind is the only criterion for a job – no judgment, no prejudice. Such a world could be closer than we think. This research examines the critical issue of hiring discrimination by focusing on the challenge of implicit racial in-group bias in organizational settings. The study proposes an innovative approach using extended reality (XR) technology, specifically through the deployment of avatars, to mitigate these biases during the interview phase. This paper extends the concept of "blind" hiring into the domain of XR, where physical characteristics like race are obscured, potentially reducing biases that inadvertently influence hiring decisions. A comprehensive literature review underpins this study, highlighting the pivotal role of workforce diversity and the substantiated benefits of diverse teams on organizational performance. The readiness and evolution of XR technology are examined, emphasizing its growing affordability and versatile applications in fields ranging from education to psychological therapy, which supports its potential use in human resource practices.
Central to this research is an empirical investigation exploring the effects of racial identity masking through avatars on implicit biases in hiring. The study employs a carefully designed experiment where participants interact with candidates represented by avatars of varying racial identifiability. This approach seeks to understand the extent to which such technological interventions can influence hiring recommendations and decisions.
These findings contribute to the scholarly understanding of XR's potential in reducing implicit biases, with far-reaching implications for both organizational practices and societal inclusivity. Additionally, they extend academic discourse on discrimination and implicit biases and offer practical insights for managers and human resource practitioners in leveraging technology for more equitable hiring processes.
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