Racial mismatch between applicant and AI avatar increased perceived ethnic bias, while sharing only one identity trait lowered fairness ratings compared to full or no match.
International Journal of Human- Computer Studies 170: 102954
2 Pith papers cite this work. Polarity classification is still indexing.
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Participatory AI approaches in forced displacement settings risk 'participation washing' due to entrenched power dynamics between aid recipients, providers, donors, and host nations, requiring independent governance structures.
citing papers explorer
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Skin-Deep Bias: How Avatar Appearances Shape Perceptions of AI Hiring
Racial mismatch between applicant and AI avatar increased perceived ethnic bias, while sharing only one identity trait lowered fairness ratings compared to full or no match.
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From experimentation to engagement: on the paradox of participatory AI and power in contexts of forced displacement and humanitarian crises
Participatory AI approaches in forced displacement settings risk 'participation washing' due to entrenched power dynamics between aid recipients, providers, donors, and host nations, requiring independent governance structures.