AI-Associated Lexical Shifts Across 34 Languages: Cross-Lingual Convergence and Diachronic Uptake in News Writing
arXiv:2605.25358v1 Announce Type: new Abstract: AI-associated lexical shifts have been documented mainly in Scientific English. We extend this work to 34 languages in the WMT News Crawl corpus, refining a split-halves continuation diagnostic that compares GPT-4.1 continuations with matched human gold-standard text. For each language, we derive ranked AI-overused lemmas using log prevalence ratios. We find substantial cross-lingual semantic convergence: semantically related concepts recur across typologically diverse languages, with 'emphasize'-type verbs appearing in 24 of 34 languages. Embedd
This research provides empirical evidence of how AI is shaping language globally, leveraging advances in large language models like GPT-4.1 for cross-lingual analysis.
Understanding AI's linguistic impact across multiple languages is crucial for global communication strategies, content creation, and detecting subtle societal shifts influenced by AI rhetoric.
We now have a quantitative measure of how AI-associated vocabulary is converging across diverse languages, indicating a shared global understanding or influence of AI discourse.
- · Multilingual NLP researchers
- · Global marketing and communications firms
- · AI ethicists and policy makers
- · Content localization services
- · Providers of non-AI-centric linguistic analysis tools
Increased awareness of pervasive AI influence on everyday language in numerous cultures.
Development of tools and strategies to track and potentially guide AI-driven linguistic shifts in public discourse.
Enhanced potential for cross-cultural misunderstanding or convergence as AI language patterns become more dominant and uniform globally.
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Read at arXiv cs.CL