Effective Access to Justice and Algorithmic Discrimination: The use of Artificial Intelligence by the Judiciary

Abstract

Objective: To analyze how the absence of an intersectional perspective in artificial intelligence (AI) systems employed by the Judiciary affects the realization of the fundamental right to effective access to justice, with particular attention to the risks of algorithmic discrimination.

 Methodology: The research adopts textual content analysis as its methodological approach, supported by the theoretical frameworks of intersectionality and effective access to justice. The examination focuses on the interplay between structural inequalities and AI-based decision-making within judicial systems.

 Findings: The study highlights that algorithmic discrimination, resulting from the uncritical adoption of AI tools in adjudication, reproduces social inequalities based on race, gender, class, and other markers of difference. The lack of intersectional awareness in these systems compromises the quality and legitimacy of judicial decisions, undermining the principle of equal treatment before the law.

 Conclusion: Algorithmic discrimination is incompatible with the guarantee of effective access to justice. Its mitigation requires the incorporation of an intersectional perspective into AI-assisted judicial practices, ensuring that technological innovations strengthen, rather than weaken, democratic access to fair adjudication.