Representational Aspects of Artificial Intelligence Generated Images: Semiosis, Self-Referentiality, and Meta-Synthesis

Authors

DOI:

https://doi.org/10.17231/comsoc.47(2025).6197

Keywords:

self-referentiality, technical images, artificial intelligence, meta-synthetic, semiosis

Abstract

This article aims to explore the relationships between the theoretical and conceptual operators of semiosis and self-referentiality, investigating aspects related to the representational dynamics of images generated by artificial intelligence (AI). The work begins with the ambivalent relationship between the image as a criterion of truth and the recognition of its possibilities for manipulation to problematise how emerging aspects of contemporary media logic strain the supposed objectivity of technical images. In this sense, through its own conceptual vocabulary, it aims to characterise synthetic images (generated by AI) as metastases. This proposal is based on an analysis of the representational processes involved in the creation and circulation of AI-generated images, examining the dimensions of prediction, self-referentiality, and meta-synthesis. Thus, the article discusses the specificities of representation and records of reality in technical images, deals with AI-generated images through prediction and their representational status, and characterises them based on the notions of “self-referentiality” and “meta-synthesis” in semiotic networks. In conclusion, the work considers that the imagistic metastases of AI-generated images strain the logical place of representation of the real, which is thus distanced, extended, and traversed by radical mediations and profound mediatisations. Likewise, AI-generated images create self-referential semiosis plots that are statistically predictable and probable, like other previous technical images.

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Author Biographies

Tiago Salgado, Programa de Pós-Graduação em Comunicação Digital, Instituto Brasileiro de Ensino, Desenvolvimento e Pesquisa, Brasília, Brazil

Tiago Barcelos Pereira Salgado is a permanent professor in the Postgraduate Programme in Digital Communication at the Instituto Brasileiro de Ensino, Desenvolvimento e Pesquisa. He holds a PhD in Communication from the Federal University of Minas Gerais, Brazil. He is the leader of the research group Field of Communication and Its Interfaces (National Council for Scientific and Technological Development) and a member of the Research Network on Semiotics, Interactions and Media Materialities.

Natália Cortez, Programa de Pós-Graduação em Comunicação, Universidade Federal de Ouro Preto, Mariana, Brazil

Natália Moura Pacheco Cortez is an assistant professor in the Department of Journalism at the Federal University of Ouro Preto, Brazil. She holds a PhD in Social Communication from the Federal University of Minas Gerais, Brazil. She is the deputy leader of the Convergence and Journalism Research Group/Federal University of Ouro Preto and a member of the Research Group on Media, Semiotics, and Pragmatism/Federal University of Minas Gerais. She is also affiliated with the Research Network on Semiotics, Interactions and Media Materialities.

Daniel Ribeiro, Departamento de Comunicação, Faculdade de Comunicação e Artes, Universidade Federal de Mato Grosso, Cuiabá, Brazil

Daniel Melo Ribeiro is an adjunct professor in the Department of Communication at the Federal University of Mato Grosso, Brazil. He holds a PhD in Communication and Semiotics from the Pontifical Catholic University of São Paulo, Brazil. He is the co-leader of the Research Group on Media, Semiotics, and Pragmatism/Federal University of Minas Gerais and a member of the International Association of Centres for Peirce Studies/Pontifical Catholic University of São Paulo. He is also a member of the Research Network on Semiotics, Interactions and Media Materialities.

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Published

2025-06-25

How to Cite

Salgado, T., Cortez, N., & Ribeiro, D. (2025). Representational Aspects of Artificial Intelligence Generated Images: Semiosis, Self-Referentiality, and Meta-Synthesis. Comunicação E Sociedade, 47, e025009. https://doi.org/10.17231/comsoc.47(2025).6197