A groundbreaking study led by researchers at McGill University is poised to upend long-held beliefs about how language evolves over time. Contrary to the widely accepted theory that semantic change principally requires the replacement of older generations by younger speakers, the new research reveals a far more nuanced picture. Utilizing advanced artificial intelligence (AI) techniques to dissect language patterns, the study demonstrates that adults across all age groups actively participate in adopting and propagating new word meanings, with older speakers sometimes even spearheading the introduction of novel semantic shifts.
For decades, linguists have theorized that language change is primarily a generational phenomenon, necessitating the gradual phasing out of older speakers in favor of new cohorts who shape contemporary vocabulary and meanings. This study, however, challenges this dogma by showing that semantic evolution does not solely hinge on generational turnover. Instead, semantic innovations percolate through a complex social matrix involving active engagement from speakers of all ages — a revelation with profound implications for our understanding of language dynamics.
The research team, headed by Gaurav Kamath, a doctoral candidate in McGill’s Department of Linguistics, applied sophisticated AI models to an unprecedentedly rich corpus: over 7.9 million speeches delivered by thousands of U.S. Congress members spanning nearly a century and a half, from 1873 to 2010. This massive dataset enabled the researchers to trace linguistic trajectories over time with remarkable granularity, uncovering subtle semantic shifts that had previously eluded detection through traditional linguistic methodologies.
One of the primary methodological challenges faced by the team was the pinpointing of emergent meanings of words in real time. While identifying the precise moment a new semantic value arises is inherently difficult due to the gradual and often sporadic nature of adoption, the researchers circumvented this obstacle by focusing on meanings once firmly established. Through a retrospective approach, they mapped how and when these newer interpretations first materialized and subsequently diffused across speaker demographics.
A quintessential example cited in the study is the term “article.” Between 1873 and 2010, “article” retained a stable meaning in legislative contexts—specifically as a constituent part of bills or laws. However, the word exhibited a semantic evolution in other domains: its usage to denote physical objects was prevalent well into the 1940s but began to wane by the mid-20th century. By the 1970s, “article” had largely come to signify a journalistic piece, highlighting how meanings can diverge and resettle within cultural milieus over extended temporal frames.
Beyond linguistic intricacies, the findings hold significant sociolinguistic import. The study reveals that older speakers, traditionally viewed as resistant to linguistic innovation, often adopt new semantic uses within only two or three years after younger speakers, narrowing the generational lag previously assumed to be far larger. In some noteworthy cases, older individuals even initiate semantic shifts, challenging stereotypes about age and language adaptability.
The implications of these discoveries extend well beyond the legislative setting in which the data was gathered. Since congresspeople constitute a relatively homogenous and socially elite group, the researchers emphasize the necessity of applying similar analytical frameworks to more demographically and culturally diverse populations. Such expanded research would test whether the patterns observed in the halls of Congress translate to everyday language use in broader social contexts, encompassing varied ethnicities, socioeconomic statuses, and age brackets.
The methodological innovation in this study lies primarily in the deployment of cutting-edge AI tools capable of semantic content analysis on an enormous scale. This approach surpasses traditional qualitative assessments, facilitating the identification of subtle patterns across millions of data points and the visualization of how these shifts propagate through individual speaker histories. The integration of AI thus provides a powerful new lens for studying language change, bridging computational linguistics with social science inquiry.
Moreover, the researchers query whether these techniques could eventually forecast the uptake of contemporary slang and emergent lexical trends among today’s youth. Predicting such phenomena would not only enrich linguistic theory but could have practical applications in fields ranging from marketing to education and technology development, where understanding the pulse of language innovation is crucial.
Speaking on the study’s broader significance, Morgan Sonderegger, an associate professor at McGill and co-author on the paper, remarked on the complexity of language evolution as a social process. He underscored that while their findings defy simplified generational paradigms, much remains to be explored about the diverse ways communities engage with language innovation. Continued research, leveraging data from multifaceted social networks and communication platforms, promises to deepen insights into how humans negotiate meaning over time.
The study, titled “Semantic Change in Adults is Not Primarily a Generational Phenomenon,” was published in the esteemed journal Proceedings of the National Academy of Sciences (PNAS) on July 28, 2025. The work received partial funding from the Fonds de Recherche du Québec – Société et Culture, underscoring the importance of supporting interdisciplinary research at the intersection of linguistics, social science, and technology.
As language constantly morphs in response to societal shifts, digital communication, and cultural trends, understanding the mechanisms of semantic change is crucial. This research not only challenges existing theoretical frameworks but also exemplifies the potential for AI to unlock new vistas in the study of language. In doing so, it broadens our grasp of human communication, emphasizing that language is a living, collective enterprise shaped by speakers of all ages working together to define and redefine meaning.
This paradigm-shifting study thus invites linguists, social scientists, and technologists alike to reconsider the interplay between age, innovation, and language evolution, opening the door to future explorations that may redefine how we think about the words we use and the meanings we share.
Subject of Research: People
Article Title: Semantic change in adults is not primarily a generational phenomenon
News Publication Date: 28-Jul-2025
Web References:
References:
Kamath, G., et al. (2025). Semantic Change in Adults is Not Primarily a Generational Phenomenon. Proceedings of the National Academy of Sciences of America.
Keywords: Linguistics, Semantic Change, Language Evolution, Social Sciences, Computational Linguistics, AI, Language Adoption
