An inter-semiotic analysis of ideational meaning in text-prompted AI-generated images

Abstract

Abstract This paper explores the inter-semiotic analysis of the ideational meaning in images generated by the text-to-image AI tool, Bing Image Creator. It adopts Kress and Van Leeuwen’s Grammar of Visual Design as its theoretical framework as the original grounding of the framework in systemic functional grammar (SFG) ensures a solid theoretical basis for undertaking analyses that involve the incorporation of textual and visual components. The integration of an AI generative model within the analytical framework enables a systematic connection between language and visual representations. This incorporation offers the potential to generate well-regulated pictorial representations that are systematically grounded in controlled textual prompts. This approach introduces a novel avenue for re-examining inter-semiotic processes, leveraging the power of AI technology. The paper argues that visual representations possess unique structural devices that surpass the limitations of verbal or written communication as they readily accommodate larger amounts of information in contrast to the limitations of the linear nature of alphabetic writing. Moreover, this paper extends its contribution by critically evaluating specific aspects of the Grammar of Visual Design.