Detalhes bibliográficos
Ano de defesa: |
2024 |
Autor(a) principal: |
Silva, Aline Alves da |
Orientador(a): |
Marcelo Graglia
,
Silva, Catarina |
Banca de defesa: |
Não Informado pela instituição |
Tipo de documento: |
Tese
|
Tipo de acesso: |
Acesso aberto |
Idioma: |
por |
Instituição de defesa: |
Pontifícia Universidade Católica de São Paulo
|
Programa de Pós-Graduação: |
Programa de Pós-Graduação em Tecnologias da Inteligência e Design Digital
|
Departamento: |
Faculdade de Ciências Exatas e Tecnologia
|
País: |
Brasil
|
Palavras-chave em Português: |
|
Palavras-chave em Inglês: |
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Área do conhecimento CNPq: |
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Link de acesso: |
https://repositorio.pucsp.br/jspui/handle/handle/41478
|
Resumo: |
We are experiencing a disruptive moment in which technologies such as Artificial Intelligence (AI) are becoming increasingly powerful and widespread. With the potential for automation of tasks that were once solely performed by humans, AI proves to be an unstoppable force across various sectors, including the financial industry. This research focuses on the issue of biases in neural networks in AI systems within the financial sector of Brazil and Portugal, as it examines several implications of this problem. Additionally, possible solutions to mitigate biases are investigated, including system development techniques, regulation, and accountability. These biases can lead to unfair and/or discriminatory decisions that negatively impact society on a massive scale. By addressing the issue of biases in AI models from two distinct geographical perspectives, the study allows for comparison between the approaches and solutions utilized in both countries within financial applications |