Hello Social: Intellectual Transitions in Artificial Intelligence, Generative AI, and Society - A Bibliometric Analysis (1972–2026*)

Priyanka Puri

2026

Closed access Metadata (CSL-JSON)
DOI 10.5958/2249-7137.2026.00039.x
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

Artificial Intelligence (AI) has evolved beyond a predominantly technical field into an increasingly interdisciplinary domain with significant societal implications. This study presents a scientometric mapping of intellectual transitions in Artificial Intelligence, Generative AI and society over the period 1972–2026. Using about 29,000 bibliographic records from Scopus and OpenAlex, the study identifies AI publications demonstrating explicit societal relevance through the terms society, social, societal, and societies. The analysis combines quantitative text mining, text cleaning, normalisation, TF–IDF, topic modelling, network analysis and temporal trend analysis to examine the changing intellectual structure of AI–society scholarship. Titles, abstracts and keywords/concepts are used to identify dominant themes, conceptual relationships and patterns of societal engagement. Results indicate that societal AI research constitutes a relatively small component of the overall AI literature but has expanded substantially, particularly since the late 2010s and during the 2020s. Social concerns dominate the thematic structure, accompanied by ethics, public issues, policy, governance, trust, sustainability and inequality. The conceptual and disciplinary analyses reveal strong linkages among Computer Science, Artificial Intelligence, Psychology, Political Science, Sociology, Law, Engineering and Social Sciences. Generative AI emerges as an important recent inflection point in this intellectual transition. The study provides evidence-based insights into the evolving AI–society interface and its relevance to responsible AI, public policy and societal well-being.