ARTIFICIAL INTELLIGENCE APPLIED TO LEGAL TRIAGE: EFFICIENCY, ETHICS, AND REGULATORY IMPACTS
DOI:
https://doi.org/10.56238/levv15n43-159Palavras-chave:
Legal Triage, Artificial Intelligence, Algorithmic Governance, Judicial Efficiency, AI EthicsResumo
Artificial intelligence (AI) has increasingly been incorporated into judicial systems, particularly in procedural stages preceding substantive adjudication. Legal triage refers to the preliminary classification, prioritization, and procedural routing of cases using computational systems, distinct from algorithmic decision-making in final judgments. This article examines AI-based legal triage across three interdependent dimensions: operational efficiency, ethical implications, and regulatory consequences. Drawing from contemporary scholarship on predictive analytics, algorithmic decision-support systems, and AI governance in judicial contexts, the study analyzes how supervised learning models and natural language processing architectures contribute to administrative optimization while simultaneously introducing concerns regarding bias, discretionary authority, transparency, and institutional accountability. The article argues that AI-driven legal triage can enhance procedural consistency and reduce systemic backlog, but its normative legitimacy depends on embedded transparency mechanisms, explainability protocols, and structured human oversight. The regulatory landscape remains fragmented, requiring harmonized governance frameworks to ensure that efficiency gains do not undermine constitutional safeguards or due process principles.
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