Eamon Duede, William Dolan, André Bauer, Ian Foster, Karim Lakhani
{"title":"油和水?人工智能在科学领域内和科学领域间的扩散","authors":"Eamon Duede, William Dolan, André Bauer, Ian Foster, Karim Lakhani","doi":"arxiv-2405.15828","DOIUrl":null,"url":null,"abstract":"This study empirically investigates claims of the increasing ubiquity of\nartificial intelligence (AI) within roughly 80 million research publications\nacross 20 diverse scientific fields, by examining the change in scholarly\nengagement with AI from 1985 through 2022. We observe exponential growth, with\nAI-engaged publications increasing approximately thirteenfold (13x) across all\nfields, suggesting a dramatic shift from niche to mainstream. Moreover, we\nprovide the first empirical examination of the distribution of AI-engaged\npublications across publication venues within individual fields, with results\nthat reveal a broadening of AI engagement within disciplines. While this\nbroadening engagement suggests a move toward greater disciplinary integration\nin every field, increased ubiquity is associated with a semantic tension\nbetween AI-engaged research and more traditional disciplinary research. Through\nan analysis of tens of millions of document embeddings, we observe a complex\ninterplay between AI-engaged and non-AI-engaged research within and across\nfields, suggesting that increasing ubiquity is something of an oil-and-water\nphenomenon -- AI-engaged work is spreading out over fields, but not mixing well\nwith non-AI-engaged work.","PeriodicalId":501285,"journal":{"name":"arXiv - CS - Digital Libraries","volume":"56 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Oil & Water? Diffusion of AI Within and Across Scientific Fields\",\"authors\":\"Eamon Duede, William Dolan, André Bauer, Ian Foster, Karim Lakhani\",\"doi\":\"arxiv-2405.15828\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study empirically investigates claims of the increasing ubiquity of\\nartificial intelligence (AI) within roughly 80 million research publications\\nacross 20 diverse scientific fields, by examining the change in scholarly\\nengagement with AI from 1985 through 2022. We observe exponential growth, with\\nAI-engaged publications increasing approximately thirteenfold (13x) across all\\nfields, suggesting a dramatic shift from niche to mainstream. Moreover, we\\nprovide the first empirical examination of the distribution of AI-engaged\\npublications across publication venues within individual fields, with results\\nthat reveal a broadening of AI engagement within disciplines. While this\\nbroadening engagement suggests a move toward greater disciplinary integration\\nin every field, increased ubiquity is associated with a semantic tension\\nbetween AI-engaged research and more traditional disciplinary research. Through\\nan analysis of tens of millions of document embeddings, we observe a complex\\ninterplay between AI-engaged and non-AI-engaged research within and across\\nfields, suggesting that increasing ubiquity is something of an oil-and-water\\nphenomenon -- AI-engaged work is spreading out over fields, but not mixing well\\nwith non-AI-engaged work.\",\"PeriodicalId\":501285,\"journal\":{\"name\":\"arXiv - CS - Digital Libraries\",\"volume\":\"56 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Digital Libraries\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2405.15828\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Digital Libraries","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2405.15828","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Oil & Water? Diffusion of AI Within and Across Scientific Fields
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.