Oil & Water? Diffusion of AI Within and Across Scientific Fields

Fuente: arXiv
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Main Authors: Duede, Eamon, Dolan, William, Bauer, André, Foster, Ian, Lakhani, Karim
Format: Preprint
Published: 2024
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author Duede, Eamon
Dolan, William
Bauer, André
Foster, Ian
Lakhani, Karim
author_facet Duede, Eamon
Dolan, William
Bauer, André
Foster, Ian
Lakhani, Karim
contents This study empirically investigates claims of the increasing ubiquity of artificial intelligence (AI) within roughly 80 million research publications across 20 diverse scientific fields, by examining the change in scholarly engagement with AI from 1985 through 2022. We observe exponential growth, with AI-engaged publications increasing approximately thirteenfold (13x) across all fields, suggesting a dramatic shift from niche to mainstream. Moreover, we provide the first empirical examination of the distribution of AI-engaged publications across publication venues within individual fields, with results that reveal a broadening of AI engagement within disciplines. While this broadening engagement suggests a move toward greater disciplinary integration in every field, increased ubiquity is associated with a semantic tension between AI-engaged research and more traditional disciplinary research. Through an analysis of tens of millions of document embeddings, we observe a complex interplay between AI-engaged and non-AI-engaged research within and across fields, suggesting that increasing ubiquity is something of an oil-and-water phenomenon -- AI-engaged work is spreading out over fields, but not mixing well with non-AI-engaged work.
format Preprint
id arxiv_https___arxiv_org_abs_2405_15828
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Oil & Water? Diffusion of AI Within and Across Scientific Fields
Duede, Eamon
Dolan, William
Bauer, André
Foster, Ian
Lakhani, Karim
Digital Libraries
Artificial Intelligence
This study empirically investigates claims of the increasing ubiquity of artificial intelligence (AI) within roughly 80 million research publications across 20 diverse scientific fields, by examining the change in scholarly engagement with AI from 1985 through 2022. We observe exponential growth, with AI-engaged publications increasing approximately thirteenfold (13x) across all fields, suggesting a dramatic shift from niche to mainstream. Moreover, we provide the first empirical examination of the distribution of AI-engaged publications across publication venues within individual fields, with results that reveal a broadening of AI engagement within disciplines. While this broadening engagement suggests a move toward greater disciplinary integration in every field, increased ubiquity is associated with a semantic tension between AI-engaged research and more traditional disciplinary research. Through an analysis of tens of millions of document embeddings, we observe a complex interplay between AI-engaged and non-AI-engaged research within and across fields, suggesting that increasing ubiquity is something of an oil-and-water phenomenon -- AI-engaged work is spreading out over fields, but not mixing well with non-AI-engaged work.
title Oil & Water? Diffusion of AI Within and Across Scientific Fields
topic Digital Libraries
Artificial Intelligence
url https://arxiv.org/abs/2405.15828