<b>Who should adress inequlity? External attributions increase support for algorithmic solutions</b>

As governments increasingly incorporate algorithmic decision-making into healthcare, education, employment, and other public services, whether these technologies can effectively mitigate inequality may depend not only on algorithmic capability but also on how the public understands the causes of inequality.

Drawing on attribution theory and system justification theory, five studies comprising seven experiments (<i>N</i> = 961) showed that externally attributing inequality consistently increased individuals’ willingness to rely on algorithmic rather than human decision-makers in addressing inequality across healthcare, recruitment, and education. This effect was driven by reduced system-justifying beliefs. Moreover, algorithmic interventions could even undermine perceived fairness when inequality was internally attributed.