Bias Cues and the Turn to AI: Perspectives from Minority and Marginalized Groups

AI is often criticized for perpetuating social inequality, yet the people most vulnerable to human prejudice may embrace AI as a fairer referee. We tested this paradox across four vignette pre-registered experiments conducted in two social contexts (gender and race), manipulating bias cues (equal vs. unequal) and psychological perspective in the scenario (self vs. third person). When bias was made salient, participants consistently preferred AI to humans. In the gender context, female participants increased AI preference when they imagined themselves as the victim of discrimination, whereas participants with higher perceived marginalization did so when the threat was described in the third person. Such differences between self- and third-person perspectives were not found in the race context. These findings suggest a complex, strategic calculus among vulnerable populations, yet highlight an ethical tension: relying on an ‘impartial’ AI risks masking systemic inequities individuals are attempting to bypass.