TECNOLOGIAS DE PERFILAMENTO E DADOS AGREGADOS DE GEOLOCALIZAÇÃO NO COMBATE À COVID-19 NO BRASIL
UMA ANÁLISE DOS RISCOS INDIVIDUAIS E COLETIVOS À LUZ DA LGPD
DOI:
https://doi.org/10.30899/dfj.v0i0.1020Palavras-chave:
Perfilamento, Dados de geolocalização, COVID-19, Riscos individuais e coletivos, Privacidade de grupoResumo
O presente trabalho visa analisar os riscos à privacidade e à proteção de dados pessoais – nas suas dimensões individual e coletiva – gerados pelo perfilamento baseado no uso de dados agregados de geolocalização de dispositivos móveis, buscando investigar a existência de parâmetros normativos encontrados na Lei Geral de Proteção de Dados (LGPD) aplicáveis aos riscos identificados. Para tanto, o artigo propõe as seguintes questões de pesquisa: (i) quais riscos aos direitos fundamentais à privacidade e à proteção de dados pessoais tecnologias de perfilamento baseadas no uso de dados agregados de geolocalização de dispositivos móveis geram nos níveis individual e coletivo na luta contra a pandemia de COVID-19 no Brasil? (ii) a LGPD prevê parâmetros normativos aplicáveis a fim de lidar com esses riscos, em especial a grupos criados a partir de sistemas algorítmicos? Na sociedade orientada por dados, o perfilamento automatizado tem importante função na infraestrutura da informação e da comunicação preponderante da computação preemptiva (preemptive computing). Neste contexto, dá-se a afirmação da dimensão coletiva dos direitos à privacidade e à proteção de dados pessoais. Os riscos detectados a ambos direitos, inclusive no âmbito coletivo ou de grupo, são o de reidentificação dos usuários de dispositivos móveis por ataques inferenciais (membership inference attacks) e de desvirtuamento de função e finalidade originária do tratamento dos dados. A fim de lidar com tais riscos, sugere-se uma interpretação sistemática de parâmetros normativos da LGPD, que tratam de perfilamento automatizado e de relatório de impacto à proteção de dados pessoais.
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