Between images and algorithms: what do we see, what looks at us, and what do we encounter in countervisualities with education?

Abstract

Emerging from a postdoctoral research project, this article explores the intersections between images, algorithms, and teaching practices, offering a critical and sensitive reflection on the uses, advances, and limitations of Artificial Intelligence (AI) within the realms of visual culture and teacher education. Drawing on authors such as Nicholas Mirzoeff, Gillian Rose, and Georges Didi-Huberman, who challenge the algorithmic capture of subjectivity, the study investigates how digital images affect us ethically, aesthetically, technically, and politically in contemporary contexts. Through the methodology of conversing with images, experienced in schools, universities, and educational events, the research reveals hybrid practices involving AI and digital platforms that expand perception and provoke meaningful shifts. A notable example includes the creation of narrative memories of women from a local community in Rio de Janeiro, retold to preschool children in a public early childhood education center using the ChatGPT application. The article invites resistance and the emergence of alternative visualities through interactive teaching approaches that confront normative models and broaden the horizons of teacher education and self-formation.