Generative AI and Meaning-Making: A Semiotic Approach from the Global South

Abstract

The widespread adoption of Artificial Intelligence (AI) models—particularly Generative AI (GenAI)—since the 2010s, along with the algorithmic circulation of data, has reshaped multiple dimensions of social life. This article examines the processes of construction of meaning in generative AI through the lens of discursive semiotics, focusing on how Big Data and datafication operate as semiotic regimes. Drawing upon the concepts of semiotic practices and forms of life (Fontanille 2008; 2015), the analysis describes how the intangible and dynamic process of datafication configures practical scenes that, once stabilized within Big Data, privilege particular forms of life. Given the concentration of technological control in the Global North, as well as the operative interactions among Big Data, datafication, algorithms, and AI, one can account, for instance, for the intensification of prejudices and stereotypes—the so-called bias. To expand the semiotic debate on AI from a Global South perspective—especially in light of the structural underrepresentation of data—the study compares texts generated by Sabiá, a Brazilian AI model, with those produced by the globally disseminated model ChatGPT. The findings demonstrate how variations in dataset constitution reverberate in processes of construction of meaning. The study argues that semiotics must be implicated in both the comprehension and the construction of more ethical and culturally plural AIs, in order to reduce structural asymmetries between North and South.