Algorithmic Fairness in Ai-Mediated Institutional Communication: A Computational Framework for Multilingual Professional Interaction
暫譯: AI介入的機構溝通中的演算法公平性：多語言專業互動的計算框架
Yi, Ran, Li, Zhensheng, Zhang, Wei
- 出版商: Springer
- 出版日期: 2026-08-15
- 售價: $2,530
- 貴賓價: 9.5 折 $2,403
- 語言: 英文
- 頁數: 63
- 裝訂: Quality Paper - also called trade paper
- ISBN: 3032286573
- ISBN-13: 9783032286574
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相關分類:
Natural Language Processing
海外代購書籍(需單獨結帳)
商品描述
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 in NLP fairness, computational sociolinguistics, multilingual AI systems, and applied machine learning in institutional domains.
商品描述(中文翻譯)
隨著大型語言模型越來越多地影響專業話語——法律程序、跨境文件和專業教育——語言公平性和算法問責的問題變得迫在眉睫。本書發展了一個計算框架，用於評估 AI 媒介的機構溝通中的公平性。
本書介紹了一種基於變壓器的基準架構，旨在測量多語言機構環境中的溝通能力和公平性。利用來自跨境專業環境的特定領域語料庫，它將社會語言學指標轉化為可測量的計算指標。
通過模型驗證、偏見分析和跨語言穩健性測試，作者展示了如何在專業溝通中評估公平性，超越一般的自然語言處理基準，並提出了一個可複製的框架，以將語言正義原則整合到 AI 系統評估中。本書將吸引對自然語言處理公平性、計算社會語言學、多語言 AI 系統以及機構領域應用機器學習的研究者的興趣。
作者簡介
Ran Yi is an Associate Professor at the National University of Defense Technology, China. Her research integrates computational linguistics, legal discourse analysis, and multilingual NLP. She studies algorithmic fairness and institutional communication, developing discourse-aware evaluation frameworks for AI-mediated professional language technologies in global settings.
Zhensheng Li is a researcher at Shanghai AI Laboratory working on large language models, multilingual representation learning, and trustworthy AI systems. His work focuses on cross-lingual modeling, efficient training architectures, and fairness evaluation for language technologies deployed in complex real-world
institutional environments today globally.
Wei Zhang is an Associate Professor at the National University of Defense Technology, China. His research focuses on institutional discourse, policy communication, and professional language in regulated contexts. He studies institutional discourse norms, authority, and interpretability.
作者簡介(中文翻譯)
冉怡是中國國防科技大學的副教授。她的研究整合了計算語言學、法律話語分析和多語言自然語言處理。她研究算法公平性和機構溝通，為全球環境中的人工智慧媒介專業語言技術開發了以話語為中心的評估框架。
李振生是上海人工智慧實驗室的研究員，專注於大型語言模型、多語言表示學習和可信的人工智慧系統。他的工作重點是跨語言建模、高效訓練架構以及對當今全球複雜現實機構環境中部署的語言技術進行公平性評估。
張偉是中國國防科技大學的副教授。他的研究專注於機構話語、政策溝通和受規範環境中的專業語言。他研究機構話語規範、權威性和可解釋性。
