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Diretrizes de auditabilidade e conformidade no desenvolvimento e testes de soluções de IA no âmbito do LIAA3R – 2ª Edição

Authors: Lima, Caio Moysés de; Lozada, Claudia de Oliveira; D'Eva, Maíra Zau Serpa Spina; Carvalho, Matheus Henrique de Paiva; Mariano Junior, Raul; Monteiro, Renato Arruda Rocha;

Diretrizes de auditabilidade e conformidade no desenvolvimento e testes de soluções de IA no âmbito do LIAA3R – 2ª Edição

Abstract

O Laboratório de Inteligência Artificial Aplicada da Justiça Federal da 3ª Região - LIAA-3R foi criado para “incentivar a pesquisa e o desenvolvimento de modelos de inteligência artificial que contribuam para o aprimoramento dos serviços judiciais e administrativos no âmbito da 3ª Região”. Do ponto de vista organizacional, o LIAA-3R não é um novo órgão, mas uma “parceria permanente” entre os dois laboratórios de inovação já existentes: o iLabTRF3 e o iJuspLab[1]. Assim, o LIAA-3R se vale, no desempenho de suas atividades, de todos os recursos materiais e humanos pertencentes aos dois laboratórios de inovação da Justiça Federal da 3ª Região. Este documento consolida as diretrizes e orientações definidas pelo GVEJ até o momento e contém, ainda, instruções destinadas ao próprio GVEJ sobre o modo de conduzir os seus procedimentos de validação. A primeira edição, elaborada no primeiro semestre de 2021, ainda estava moldada pelos preceitos da Portaria SINAPSES. A presente edição já contempla as inovações normativas, além de agregar a experiência e o conhecimento adquiridos pelos membros do GVEJ no procedimento de validação dos projetos SINARA/SIGMA, concluído no final de 2021.

2ª Edição

Keywords

Validação, Algoritmo, Conformidade, Inteligência artificial, Lei Geral de Proteção de Dados, Auditabilidade

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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