Abertura não faz mal : promovendo transparência qualificada de sistemas de aprendizagem de máquina para proteção de dados por meio da regulação responsiva

Dissertação (mestrado) — Universidade de Brasília, Faculdade de Direito, Programa de Pós-Graduação em Direito, 2022.Sistemas de aprendizagem de máquina (machine learning, ML) têm sido cada vez mais utilizados em processos de tomada de decisões que afetam aspectos-chave das vidas de pessoas. Entretanto, usuários e reguladores pouco sabem sobre como esses modelos funcionam, já que apenas informações escassas são divulgadas por seus desenvolvedores e operadores. A transparência dessas tecnologias surge assim como uma exigência feita por diferentes grupos de especialistas para que os usuários tenham controle sobre o quanto suas vidas devem depender dos julgamentos realizados por sistemas de machine learning, mas também para que reguladores responsabilizem os responsáveis por eles pelos danos que vierem a incorrer. Esta dissertação traça assim uma análise comparativa sobre como as leis brasileira e europeia de proteção de dados abordam a transparência de machine learning e avalia a adequação das estratégias participativas da teoria da regulação responsiva e de sua estrutura de incentivos para promover sistemas mais inteligíveis.Machine-learning (ML) models have been increasingly applied to make decisions that affect key aspects of people’s lives. However, users and regulators are barely aware of how these models work, as only scarce information is disclosed by developers and operators on this matter. ML transparency emerges thus as a recurrent demand made by stakeholders for users to gain control over how much their lives should rely on judgements carried out by machines, for regulators to render those responsible for them accountable for incurred damages and for scholars to understand algorithms' impacts in society. This dissertation thus traces a comparative analysis on how the Brazilian and European data protection legal frameworks address ML transparency and assesses the adequateness of the responsive regulation theory’s participatory strategies and incentives framework for promoting more intelligible systems

Transparência pela cooperação: Como a regulação responsiva pode auxiliar na promoção de sistemas de machine-learning inteligíveis

[Purpose] To analyze the applicability of the theory of responsive regulation to promote the intelligibility of machine learning systems under the focus of the Brazilian General Data Protection Law (LGPD). [Methodology/approach/design] This article has the theory of responsive regulation as a theoretical framework and will initially be based on a comparative analysis of the LGPD and the GDPR to identify how this theory can assist Brazilian regulators, more specifically the National Data Protection Authority, to address intelligibility of artificial intelligence systems. [Findings] From a comparative analysis between how LGPD and GDPR deal with the issue of automated decision systems (including machine-learning) explainability, this article identified that the rationale for cooperation between regulator and regulated, a network governance system and the existence of a regulatory pyramid allows for the application of the theory of responsive regulation to promote the intelligibility of these systems. [Practical implications] AI systems have often been accused of discriminatory bias, something which may increase the racial and gender gaps in Brazil. Ensuring that the technology is understandable for humans to better identify how to address these shortcomings is paramount to promoting the use of fairer systems. This study intends, by identifying the most appropriate regulatory strategies to deal with algorithmic opacity, to assist regulators in addressing the discrimination promoted by these systems.[Purpose] To analyze the applicability of the theory of responsive regulation to promote the intelligibility of machine learning systems under the focus of the Brazilian General Data Protection Law (LGPD). [Methodology/approach/design] This article has the theory of responsive regulation as a theoretical framework and will initially be based on a comparative analysis of the LGPD and the GDPR to identify how this theory can assist Brazilian regulators, more specifically the National Data Protection Authority, to address intelligibility of artificial intelligence systems. [Findings] From a comparative analysis between how LGPD and GDPR deal with the issue of automated decision systems (including machine-learning) explainability, this article identified that the rationale for cooperation between regulator and regulated, a network governance system and the existence of a regulatory pyramid allows for the application of the theory of responsive regulation to promote the intelligibility of these systems. [Practical implications] AI systems have often been accused of discriminatory bias, something which may increase the racial and gender gaps in Brazil. Ensuring that the technology is understandable for humans to better identify how to address these shortcomings is paramount to promoting the use of fairer systems. This study intends, by identifying the most appropriate regulatory strategies to deal with algorithmic opacity, to assist regulators in addressing the discrimination promoted by these systems.[Propósito] Analisar a aplicabilidade da teoria da regulação responsiva para promoção da inteligibilidade de sistemas de machinelearning sob o enfoque da Lei Geral de Proteção de Dados. [Metodologia/abordagem/design] Este artigo tem a teoria da regulação responsiva como marco teórico e se baseará, inicialmente, em uma análise comparada da LGPD e do RGPD para identificar como essa teoria pode auxiliar reguladores brasileiros, mais especificamente a Autoridade Nacional de Proteção de Dados, a abordar a inteligibilidade de sistemas de inteligência artificial. [Resultados] A partir de uma análise comparativa prévia entre como LGPD e RGPD lidam com o tema da explicabilidade de sistemas de decisão automatizada (incluso machine-learning), identificou-se que o racional de cooperação entre regulador e regulado, um sistema de governança em rede e a existência de uma pirâmide regulatória permitem a aplicação da teoria da regulação responsiva para a promoção da inteligibilidade desses sistemas. [Implicações práticas] Sistemas de IA têm sido frequentemente acusados de possuírem vieses discriminatórios. Isso faz com que pessoas negras sejam mais frequentemente identificadas do que brancas por tecnologias de reconhecimento facial ou que afrodescendentes tenham menor chance de conseguir crédito, potencializando o abismo racial no Brasil. Garantir que a tecnologia seja compreensível para humanos identificarem melhor como endereçar essas falhas é primordial para promover o uso de sistemas mais justos. O presente estudo pretende, por meio da identificação das estratégias regulatórias mais adequadas a lidar com a opacidade algorítmica, auxiliar reguladores a endereçar a discriminação promovida por esses sistemas

O acordo entre União Europeia e Turquia para readmissão de refugiados e os conceitos de primeiro país de asilo e país terceiro seguro

Trabalho de Conclusão de Curso (graduação)—Universidade de Brasília, Faculdade de Direito, 2017.A Guerra Civil Síria levou à maior crise de refugiados desde a Segunda Guerra Mundial. Os países mais afetados pela migração em massa são os que fazem fronteira com a Síria, como Líbano, Jordânia e Turquia, bem como os Estados europeus, em especial a Grécia e os países dos Balcãs. Nesse contexto, a União Europeia celebrou um acordo com a Turquia para devolver ao país requerentes irregulares de asilo que, antes de chegarem às fronteiras europeias, passaram por território turco. O objetivo desta monografia é analisar se o acordo respeita o princípio de direito internacional do non-refoulement e as noções de primeiro país de asilo e terceiro país seguro, previstos no direito europeu, de modo a conferir se os sírios que vivem na Turquia têm acesso aos direitos previstos na Convenção Relativa ao Estatuto dos Refugiados.The Syrian Civil War led to the greatest refugee crisis since World War II. The most affected countries are the ones bordering Syria, such as Lebanon, Jordan and Turkey, as well as the European States, especially Greece and the Balkan States. In this context, European Union signed an agreement with Turkey in order to return to the latter irregular asylum seekers whom, before arriving in Europe, crossed the Turkish territory. The aim of this undergraduate thesis is to analyze whether the agreement respects the non-refoulement international law principle and the notions of first country of asylum and safe third country, as described by the European law, so as to ascertain whether Syrians in Turkey are having access to the rights established under UN’s Convention Relating to the Status of Refugees

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved