Algoritmos racistas: a representação das crianças negras da educação infantil nos bancos de imagens digitais

Abstract

This study investigated racial presence and representativeness in images related to early childhood education available on digital image banks such as Unsplash, Freepik, Pexels, and Pixabay. The primary objective was to determine whether search algorithms, potentially imbued with racial bias, influence the representation of Black children in early childhood education and contribute to the perpetuation of racism. The methodology involved mapping and analyzing images obtained from searches using terms such as "Early Childhood Education," "Daycare," "Young Child," "Child," "Black Child," and "Preschool." The research addressed concepts of algorithmic oppression and algorithmic racism, discussing the importance of an anti-racist early childhood education. The results revealed a predominance of images of white children, with limited representation of Black children. Searches for terms like "Daycare" and "Early Childhood Education" yielded a significant number of images featuring white children. In contrast, images of Black children, when found, often depicted them in a negative light or with serious expressions. This qualitative and documentary-focused research raises the following question: What are the social and pedagogical implications of stereotypical or negative representations of Black children in the context of early childhood education linked to digital image banks? The study aims to promote reflection on how the absence or under-representation of Black children can impact their self-esteem and identity, sustaining prejudices and creating an unequal educational environment. This study suggests that search algorithms in digital image banks may reinforce a Eurocentric view of early childhood education, preserving and reproducing racial exclusion in various contexts where these images may be shared and/or commercialized.