Análise da abordagem antirracista como pilar fundamental no design de intervenções de inteligência artificial na área de saúde
Guardado en:
| Autor principal: | |
|---|---|
| Fecha de Publicación: | 2024 |
| Formato: | Master thesis |
| Lenguaje: | por |
| Fuente: | Repositório Comum do Brasil - Deposita |
| Download full: | https://deposita.ibict.br/handle/deposita/826 https://isni.org/isni/0000000527830351 https://www.cesar.school/ https://ror.org/02t7xfd51 |
Sumario: | The increasing use of artificial intelligence (AI) in the healthcare sector in Brazil faces the critical challenge of racial biases, which have the potential to amplify existing inequalities and compromise the quality of care in a country marked by its significant racial diversity. This research aims to investigate how the inclusion of anti-racist practices in the design of AI solutions can contribute to equity in artificial intelligence solutions in healthcare. It also seeks to understand the mechanisms by which racial biases affect AI solutions, as well as proposing strategies to effectively mitigate these biases. Using an exploratory, inductive, and constructivist methodological approach, based on the analysis of interviews with healthcare professionals, designers, and developers, the study highlights the scarcity of anti-racist initiatives in the AI solutions development cycle, showing the need to reformulate current practices. In conclusion, it reveals the need for a holistic approach to achieve equity in AI solutions in healthcare, emphasizing the adoption of anti-racist practices, the promotion of diversity in development teams, and the importance of multidisciplinary collaborations. These strategies aim to ensure that AI solutions meet the varied needs of the population, with ethics, racial equity, and explicitly anti-racist practices becoming central elements of innovation in healthcare AI. |