Título: | RIGHT TO AN EXPLANATION AND DATA PROTECTION IN DECISIONS BY ARTIFICIAL INTELLIGENCE ALGORITHMS | ||||||||||||
Autor: |
ISABELLA ZALCBERG FRAJHOF |
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Colaborador(es): |
CAITLIN SAMPAIO MULHOLLAND - Orientador |
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Catalogação: | 26/OUT/2022 | Língua(s): | PORTUGUESE - BRAZIL |
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Tipo: | TEXT | Subtipo: | THESIS | ||||||||||
Notas: |
[pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio. [en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio. |
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Referência(s): |
[pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=60965&idi=1 [en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=60965&idi=2 |
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DOI: | https://doi.org/10.17771/PUCRio.acad.60965 | ||||||||||||
Resumo: | |||||||||||||
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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