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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Can Law Ever Be Code? Beyond Google’s Algorithmic Black Box and Towards a Right to Explanation

Costa Dos Anjos, Lucas 23 November 2021 (has links) (PDF)
This thesis aims to analyze the legal relevance and forms of instrumentalization of the right to explanation of automated decisions in the context of European Union Law. Under the prisms of trade secret protection, privacy and data protection, competition and consumer law, the investigation identifies legal provisions of primary and secondary European law, as well as complementary sources, which support the existence of a right to explanation. Additionally, the proportionality in the weighing of fundamental rights can corroborate the legal and technical implementation of this right, for which this thesis proposes practical suggestions that are consistent with the Google Search platform, chosen as the object of study through which the analyzes would be carried out. Revisiting Lawrence Lessig's idea that (computational) code would shape society's behavior, accommodated by Shoshana Zuboff's recent contributions on surveillance capitalism, I propose that law (norms) can also be translated into (programming) code. Many steps in this direction have already been taken and continue to be in recently proposed legislation. Robust laws in the areas of data protection, trade secrets protection, competition and consumer law currently subsidize claims for explanation that can be filed with different administrative bodies and be examined by European courts. Competition authorities have already proven that there can be real consequences in the reformulation of some of these practices in the private sector, as seen in previous cases of Google within the scope of the European Commission. Since there is a large asymmetry of information between automated decision-making platforms and its users, by disclosing a portion of an algorithm’s inner functioning (purposes, reasoning, inputs and deciding parameters taken into consideration etc.), in an appropriate fashion to the average user for whom the explanation is aimed, it is possible to better enforce consumer welfare and safeguard competition standards. The substance of this study recognizes the importance of a right to explanation as a stepping stone for algorithmic governance, especially with regard to Google’s search engine and its applications. / Doctorat en Sciences juridiques / info:eu-repo/semantics/nonPublished
2

[pt] DIREITO À EXPLICAÇÃO E PROTEÇÃO DE DADOS PESSOAIS NAS DECISÕES POR ALGORITMOS DE INTELIGÊNCIA ARTIFICIAL / [en] RIGHT TO AN EXPLANATION AND DATA PROTECTION IN DECISIONS BY ARTIFICIAL INTELLIGENCE ALGORITHMS

ISABELLA ZALCBERG FRAJHOF 26 October 2022 (has links)
[pt] Em um mundo mediado por algoritmos, em que espaços de tomada de decisão antes destinados a humanos passam a ser dominados por estes artefatos, surge uma demanda para que estas decisões algorítmicas sejam explicáveis. Este desafio ganha uma camada de complexidade quando há o uso de técnicas de inteligência artificial, em especial, a aplicação de modelos de aprendizado de máquina, diante da opacidade e inescrutabilidade do modo de funcionamento e dos resultados gerados de alguns tipos destes algoritmos. Neste sentido, esta tese tem início com a apresentação do conceito e dos desafios da inteligência artificial e do aprendizado de máquina para o Direito, particularmente para direitos fundamentais (i.e. proteção de dados pessoais, privacidade, liberdade, autonomia e igualdade). Em seguida, é compartilhada a discussão envolvendo o direito à explicação quando do seu surgimento, e como a sua previsão na LGPD poderá ser interpretada à luz dos aprendizados e interpretações já colhidos no âmbito do GDPR. Ainda, serão analisados como os principais desafios para os direitos fundamentais que são colocados por tais algoritmos de tomada de decisão podem ser resumidos sob os princípios de transparência, prestação de contas e responsabilização e justiça/igualdade. É proposta uma abordagem multifacetada e multidisciplinar, a ser aplicada em diferentes momentos, para assegurar a observância de tais princípios no desenvolvimento e uso de algoritmos de tomada de decisão de aprendizado de máquina. Por fim, propõe-se que a garantia de um direito à explicação, atualmente inserido em uma discussão mais ampla de prestação de contas e responsabilização, deve atender a uma perspectiva de mérito e de procedimento. São identificados os diferentes tipos de conteúdos que têm sido mapeados como passíveis de serem exigidos a título de explicação, e os valores e direitos que um direito à explicação visa proteger, demonstrado, ao final, a importância de que este conteúdo possa estar sujeito a algum tipo de escrutínio público. / [en] In a world mediated by algorithms, in which decision-making spaces previously destined for humans are now dominated by these artifacts, urges a demand for these algorithmic decisions to be explainable. This challenge gains a layer of complexity when artificial intelligence techniques are used, in particular, the application of machine learning models, given the opacity and inscrutability of the operating mode and the results generated by some types of these algorithms. In this sense, this thesis begins with the presentation of the concept and challenges of artificial intelligence and machine learning for the area of Law, particularly for fundamental rights (i.e. data protection, privacy, freedom, autonomy and equality). Then, the discussion involving the arise of a right to explanation is presented, and how its provision in the LGPD can be interpreted in the light of the lessons learned and interpretations already gathered under the GDPR. Furthermore, it will be analyzed how the main challenges for fundamental rights that are posed by such decision-making algorithms can be summarized under the principles of transparency, accountability and justice/equality. A multifaceted and multidisciplinary approach is proposed, to be applied at different moments in time, to ensure that such principles are incorporated during the development and use of machine learning decision-making algorithms. Finally, this thesis proposed that guaranteeing a right to explanation, which is currently allocated in a broader discussion involving accountability, must take into account a perspective of merit and procedure. The different types of content that have been mapped as likely to be required as an explanation are identified, as well as the values and rights that a right to explanation aims to protect, demonstrating, finally, the importance that such content be subject to public scrutiny.

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