The Linguistic Landscape of AI Communication: Challenges in Human-Machine Interactions
DOI:
https://doi.org/10.64137/XXXXXXXX/IJLLH-V1I1P105Keywords:
Artificial Intelligence, Human-Machine Interaction, Natural Language Processing, Linguistic Landscape, Semantic Ambiguity, Context Awareness, Machine LearningAbstract
The quick advancement of Artificial Intelligence (AI) innovations has expanded the mediums of human-machine correspondence to a number of new linguistic communications. In this sense, this paper will delve into a better understanding of the linguistic landscape of AI communication, paying close attention to the challenges of Human–Machine Interactions (HMI). We examine how remaining semantic ambiguities, contextual misunderstanding, syntactic complexity, and pragmatic limitations within AI language processing limit what they can do. This research examines the factors hidden behind the scenes that hinder smooth communication, utilising a multidisciplinary approach that combines computational linguistics, cognitive science, and AI system analysis. The findings reveal gaps in Natural Language Understanding (NLU) for maintaining, highlighting the importance of cultural and linguistic diversity; they also showcase the inadequacies of current machine learning models in perceiving nuanced human expressions. We propose possible paths for adaptive language models and context-aware algorithms to enhance AI communicative competence, which would help build better HMI systems. The results are informative for AI design, linguistic theory and user experience optimization
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