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To explore this question, we constructed a dataset of 22.1 million words from unscripted spoken language drawn from conversational science and technology podcasts.
Simplified Text
For their study on AI-associated language, researchers constructed a dataset of 22.1 million words from unscripted spoken language from science and technology podcasts.
Confidence Score
1.000
Claim Maker
Bryce Anderson, Riley Galpin, Tom S. Juzek
Context Type
Scientific Paper Abstract
Context Details
{
    "statistic": "22.1 million words",
    "paper_title": "Model Misalignment and Language Change: Traces of AI-Associated Language in Unscripted Spoken English",
    "source_type": "conversational science and technology podcasts"
}
Subject Tags
Artificial Intelligence Research Linguistics Computer Science
UUID
05e52a4a-19f2-4365-b2cc-d5c7327cd573
Vector Index
✗ No vector
Created
September 25, 2026 at 1:10 AM (2 weeks ago)
Last Updated
September 25, 2026 at 1:10 AM (2 weeks ago)

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Screenshot of https://arxiv.org/abs/2508.00238
Model Misalignment and Language Change: Traces of AI-Associated Language in Unscripted Spoken English
Completed Research
3 claims
2 weeks ago
https://arxiv.org/abs/2508.00238

This paper investigates the influence of Large Language Models (LLMs) on human language, specifically in unscripted spoken English. Analyzing 22.1 million words from podcasts, the study found a significant increase in LLM-associated words post-2022, suggesting a convergence between human and AI language patterns.

Large Language Models Language Change AI Influence Computational Linguistics Spoken English Lexical Analysis

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