Toward Fair Artificial Intelligence: Algorithmic Equity and Decolonial Reparation in Social Resource Allocation
Abstract
This study examines the impact of artificial intelligence (AI) on the equity of social resource allocation in contexts of structural inequality in Latin America and Europe. To this end, a comparative analysis of three flagship programs (SISBEN in Colombia, Progresa in Mexico, and the Minimum Living Income in Spain) was conducted using a modified Delphi method with the participation of 15 experts. The study identified significant systemic biases, such as geographic exclusion, ethnic discrimination, the gender gap, and age bias. In addition, there was a total absence of ex ante ethical audits in the algorithms evaluated. Participatory approaches were found to be more effective in mitigating biases than technical interventions. This article proposes the DELPHI Ethical Protocol, based on community co-participation, binding audits, multilingual transparency, and a remediation fund financed by a tax on AI developers. It concludes that regulatory frameworks must include decolonial clauses to ensure social justice in algorithmic governance.
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