Algorithmic Fairness in AI-Mediated Institutional Communication: A Computational Framework for Multilingual Professional Interaction (SpringerBriefs in Computer Science)

As Large Language Models increasingly shape professional discourse-legal proceedings, cross-border documentation, and professional education-questions of linguistic equity and algorithmic accountability become urgent.The book develops a computational framework for evaluating fairness in AI-mediated institutional communication.The book introduces a transformer-based benchmarking architecture designed to measure communicative competence and fairness across multilingual institutional settings.Using domain-specific corpora from cross-border professional environments, it operationalises sociolinguistic indicators into measurable computational metrics. Through model validation, bias analysis, and cross-lingual robustness testing, the authors demonstrate how fairness in professional communication can be evaluated beyond generic NLP benchmarks, and propose a replicable framework for integrating linguistic justice principles into AI system assessment.This book will be of interest to researchers