Título: | EVALUATING APPROACHES FOR DEVELOPERS ETHICAL REASONING AND COMMUNICATION ABOUT MACHINE LEARNING MODELS | ||||||||||||
Autor: |
JOSE LUIZ NUNES |
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Colaborador(es): |
SIMONE DINIZ JUNQUEIRA BARBOSA - Orientador CLARISSE SIECKENIUS DE SOUZA - Coorientador |
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Catalogação: | 30/NOV/2021 | Língua(s): | ENGLISH - UNITED STATES |
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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=56260&idi=1 [en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=56260&idi=2 |
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DOI: | https://doi.org/10.17771/PUCRio.acad.56260 | ||||||||||||
Resumo: | |||||||||||||
Machine learning algorithms have become widespread for a wide
array of tasks. However, there is still no established way to deal with the
ethical issues involved in their development and design. Some techniques
have been proposed in the literature to support the reflection and/or
documentation of the design and development of machine learning models,
including ethical considerations, such as: (i) Model Cards and (ii) the
Extended Metacommunication Template. We conducted a qualitative study
to evaluate the use of these tools. We present our results concerning the use
of the Model Card by participants, with the objective of understanding how
these actors interacted with the relevant tool and the ethical dimension of
their reflections during our interviews. Our goal is to improve and support
techniques for developers to disclose information about their models and
reflect ethically about the systems they design. Furthermore, we aim to
contribute to the development of a more ethically informed and fairer use
of machine learning.
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