O paradoxo profundo
dos kernels à maquiagem social
Palabras clave:
Algoritmos, Aprendizagem profunda, Inteligência artificial, Saúde Coletiva, Sociedade da InformaçãoResumen
O objetivo deste estudo é analisar a produção científica disponível sobre modelos de Deep Learning para diagnóstico de doenças de pele, com foco na diversidade étnico-racial, em coleções de imagens. Metodologicamente, o estudo caracteriza-se como uma revisão narrativa da literatura, de natureza exploratória. Excluíram-se artigos que não utilizavam algoritmos de aprendizagem profunda ou que não abordavam o diagnóstico de doenças de pele. Foram analisados 37 artigos e 7 coleções de imagens de lesões cutâneas. Os resultados mostram que três artigos mencionavam a origem populacional das imagens utilizadas no treinamento dos modelos de Deep Learning. Apenas uma coleção indicou a predominância populacional das imagens representadas, mas nenhum desses repositórios forneciam estatísticas detalhadas sobre a população participante. Conclui-se que a eficácia dos algoritmos em contextos de diversidade racial carece de evidências, e as pesquisas analisadas não apresentavam soluções para essa lacuna. Nesse contexto, este estudo destaca o paradoxo profundo entre o avanço tecnológico e a perpetuação de desigualdades sociais, enfatizando a necessidade de ajustes sociais em sistemas de inteligência artificial para promover equidade no acesso à saúde e evitar o viés algorítmico em tecnologias de diagnóstico.
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