The Scale of Language
Description
The Scale of Language confronts a defining challenge of the GenAI era: the accelerating volume of machine generated text, produced with statistical smoothness and at unprecedented speed, creates a structural risk of linguistic homogenization. The danger is not scarcity but semantic drift, conceptual opacity, the erosion of reasoning visibility, and a loss of expressive depth. Evaluating linguistic quality therefore becomes essential for preserving clarity, meaning, interpretive reliability, and ultimately the human sovereignty over language. This book develops a principled pathway for meeting that challenge by integrating cognitive adequacy with statistical coherence through a dual foundation architecture. It introduces PhilEntropy, grounded in cognitive linguistic entropy, to capture the depth, relevance, and interpretive structure of human meaning, and LogiEntropy to characterize the distributional and structural regularities that statistical systems produce. Their integration forms the Linguistic Entropy Quotient (LEQ), a three layer evaluative framework that unifies perception, interpretation, and expression into a coherent measure of linguistic quality, including an expression spectrum that differentiates levels of linguistic quality. Through this architecture, the book provides a foundation for understanding how language functions across scientific writing, education, governance, and other domains where conceptual rigor is essential. It is written for researchers, educators, scientific writers, AI practitioners, and interdisciplinary scholars seeking a rigorous and actionable framework for evaluating linguistic quality in contexts where human and generative systems increasingly operate within shared expressive environments.
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Persons
Yu-Chu Tian is a Professor of Computer Science in the School of Computer Science at the Queensland University of Technology, Brisbane QLD, Australia. He received the Ph.D. degree in computer and software engineering from the University of Sydney, Sydney NSW, Australia, in 2009, and the Ph.D. degree in industrial automation from Zhejiang University, Hangzhou, China, in 1993. Professor Tian has previously held academic positions at Zhejiang University in Hangzhou China, the Hong Kong University of Science and Technology in Hong Kong China, and Curtin University in Perth Australia. He has also served as a visiting professor at the University of Maryland at College Park, USA; the University of Navarra in San Sebastián, Spain; and KTH Royal Institute of Technology in Stockholm, Sweden. His research interests span a wide range of interdisciplinary areas, including artificial intelligence and machine learning, cloud computing, computer networks, smart grid communications and control, networked control systems, and cyber-physical security
Zhuo-Ya Yang is an interdisciplinary practitioner committed to cross-domain research and practice. He received the M.S. degree in environmental science in 1991 and the Ph.D. degree in agricultural science in 1994, both from China Agricultural University in Beijing, and later pursued an EMBA at the Peking University HSBC Business School in 2021. His career spans academia and industry, beginning with university teaching before transitioning into public and private sectors, where he has accumulated extensive cross-sector experience. Dr. Yang currently serves as the Chief Executive Officer of Anyikong Power Technology Co., Ltd., a multinational new-energy enterprise. He is the author of The Measurement of Language, recently published in traditional Chinese by Chung Hwa Book Co. The book reflects his enduring engagement with questions of language, intelligence, and the human condition. His broad professional background has shaped a perspective that integrates scientific reasoning with practical innovation
Content
The Language Singularity.- Language as Cognitive Infrastructure.- Language from Generative AI.- The Evolution of Entropy.- Architecture of Language Quality Evaluation.- Expression Layer in the Evaluation Framework.- Interpretation Layer in the Evaluation Framework.- Perception Layer in the Evaluation Framework.