An Integrative Literature Review Aligning Cross-disciplinary Continua for a Computational raison d’exprimer

Abstract

The landscape of Conversational Artificial Intelligence has become extremely varied, in the last years, as the capability of using language in machines has become the main showcase for generative applications. From a language philosophy point of view, however, the reason why Generative AI produces linguistic content is not aligned with the one motivating humans. In this paper, we provide a multidisciplinary integrative literature review spanning linguistics, cognitive science and computer science to propose a systematic way of organising this knowledge around raison d’exprimer: the reason why a machine should use language. We present both a horizontal model describing how different aspects of communication blend into each other, the hypertriangle of communication, and a vertical model providing a common axis to align multiple disciplines involved in Conversational AI: the illocutionary gradient. By showing how concepts belonging to multiple disciplines align themselves in these models, we provide an extensible theoretical tool to study conceptual alignments in different fields.