Emergent Communication in Artificial Intelligence Interactions: Linguistic Evolution and Societal Implications

This paper explores how artificial intelligence (AI) agents can spontaneously develop new forms of communication—known as emergent communication—when interacting in cooperative and competitive multi-agent environments. By combining theoretical analysis with a detailed multi-agent simulation framework (including reinforcement learning and optional large language model interfaces), the study examines how AI-to-AI communication evolves, how it can be evaluated for transparency, efficiency, similarity to human language, and human learnability, and what ethical and societal implications may follow. Supplementary materials include pseudocode and a full simulation process diagram to enhance reproducibility and practical application.

Affiliation
Scientific Research Association of Kavian
This independent scientific and research association supports interdisciplinary studies in artificial intelligence, computational linguistics, and emerging technologies. The present work is authored by Siavosh Kaviani, Reza Salimpour Azar, and Ali Sohrabi under the auspices of this association.