“DEVELOPING EFFECTIVE, ACCOUNTABLE, AND TRANSPARENT INSTITUTIONS AT ALL LEVELS”

A CRITICAL PERSPECTIVE ON THE FULFILLMENT OF SUSTAINABLE DEVELOPMENT GOALS TARGET 16.6 BY THE BRAZILIAN JUDICIARY – ACHIEVEMENTS AND SHORTCOMINGS

Abstract

Through this article, the objective is to analyze the fulfillment of Target 16.6 of the Sustainable Development Goals (SDGs) of the 2030 Agenda of the UN by the Brazilian Judiciary, particularly about the requirement of effectiveness, from a critical perspective concerning its achievements and shortcomings. The hypothesis is that the Brazilian Judiciary has exercised its role in a responsible, transparent, and effective manner, notwithstanding the need for continuous improvement: (i) of mechanisms and tools for expenditure control; (ii) of the resolution of bottlenecks that hinder the prompt delivery of judicial services and the enhancement of quality control methods. Regarding the methodology, the quantitative data were drawn from the “Justiça em Números” (Justice in Numbers) publication issued by the National Council of Justice, because it constitutes the most comprehensive database, presenting figures from all bodies within the national judiciary, compiled and balanced using specific metrics and indicators. Additionally, the study involved consulting bibliographic sources, legal texts, and official websites. The findings were derived using inductive logic. As a result, it is highlighted that the Brazilian Judiciary has made consistent efforts to improve the delivery of justice, aiming to satisfactorily meet SDG Target 16.6. The main challenge in the coming years will be to maintain the reduction in the number of pending cases and in their processing times, as well as to improve the quality of judicial services. In this regard, the rational and ethical use of artificial intelligence and the indexing of the judiciary’s databases to the SDGs may serve as effective support measures. Accordingly, it is suggested that future research should continue analyzing performance indicators, particularly the effects of artificial intelligence use and its implications, as well as the improvement of quality control metrics.