Vieses algorítmicos de raça e gênero nos processos e sistemas de organização do conhecimento
In recent years, several studies have shown ethical deviations, as well as racism and sexism in the processes and systems of knowledge organization that contribute to perpetuating prejudices and discrimination against historically marginalized populations such as blacks, indigenous peoples, wo...
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| Formato: | bachelorThesis |
| Idioma: | pt_BR |
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Universidade Federal do Rio Grande do Norte
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| Endereço do item: | https://repositorio.ufrn.br/handle/123456789/50741 |
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| Resumo: | In recent years, several studies have shown ethical deviations, as well as racism and
sexism in the processes and systems of knowledge organization that contribute to
perpetuating prejudices and discrimination against historically marginalized
populations such as blacks, indigenous peoples, women, LGBTQIA+, among others.
These issues are present both in physical and digital environments, including those
marked by the intensive use of artificial intelligence algorithms such as search
engines, image banks and library discovery systems. This raises questions about the
reproduction of discrimination and prejudice in the digital environment. In this sense,
the present work aims to analyze manifestations of algorithmic biases in knowledge
organization processes and systems that perpetuate race and gender discrimination.
For this, bibliographical research is used in order to identify cases of racism and
algorithmic sexism according to the environment of occurrence or system of
organization of the knowledge involved. From the retrieved literature, three cases were
selected, reflected in three published works, which address algorithmic biases in
search engines, image banks and library discovery systems. The results were
obtained through a critical analysis of the three works observed. During this process,
it was possible to verify manifestations of racism and sexism both in the Google search
engine, as well as in the Shuttersstock, Stockphotos and Getty Images image banks
and in library discovery systems, fundamentally related to processes of indexing and
categorization of subjects and images. These biases mostly affect the representation
of black populations and women, also making it difficult to access correct and truthful
information about these social groups. The analyzes also reveal the lack of
transparency and regulation in the use of artificial intelligence algorithms. It concludes
by highlighting the importance of information professionals who know and dominate
these discussions, as well as further research in this area to ensure that the processes
and systems of knowledge organization do not contribute to the perpetuation of
discrimination and inequalities of race and gender. |
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