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Tiago P. Pagano, Rafael B. Loureiro, Fernanda V. N. Lisboa, Gustavo O. R. Cruz, Rodrigo M. Peixoto, Guilherme A. de Sousa Guimarães, Ewerton L. S. Oliveira, Ingrid Winkler and Erick G. Sperandio Nascimento
The majority of current approaches for bias and fairness identification or mitigation in machine learning models are applications for a particular issue that fails to account for the connection between the application context and its associated sensitive...
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Tiago P. Pagano, Rafael B. Loureiro, Fernanda V. N. Lisboa, Rodrigo M. Peixoto, Guilherme A. S. Guimarães, Gustavo O. R. Cruz, Maira M. Araujo, Lucas L. Santos, Marco A. S. Cruz, Ewerton L. S. Oliveira, Ingrid Winkler and Erick G. S. Nascimento
One of the difficulties of artificial intelligence is to ensure that model decisions are fair and free of bias. In research, datasets, metrics, techniques, and tools are applied to detect and mitigate algorithmic unfairness and bias. This study examines ...
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