{"title":"当两个科学学科相遇:评估结合的动力学。天体物理学和人工智能的相遇","authors":"A. Marcovich, T. Shinn","doi":"10.1177/05390184211025848","DOIUrl":null,"url":null,"abstract":"This article points out some issues raised by the encounter between astrophysics (AP) and a newly emergent mathematical tool/discipline, namely artificial intelligence (AI). We suggest that this encounter has interesting consequences in terms of science evaluation. Our discussion favors an intra science perspective, both on the institutional and cognitive side. This encounter between machine learning (ML) and astrophysics points to three different consequences. (1) As a transverse tool, a same ML algorithm can be used for a diversity of very different disciplines and questions. This ambition and analytic intellectual architecture frequently identify similarities among apparently differentiated fields. (2) The perimeter of the disciplines involved in a research can lead to many and novel ways of collaboration between scientists and to new ways of evaluation of their work. And (3), the impossibility for the human mind to understand the processes involved in ML work raises the question of the reliability of results.","PeriodicalId":47697,"journal":{"name":"Social Science Information Sur Les Sciences Sociales","volume":"60 1","pages":"372 - 377"},"PeriodicalIF":1.9000,"publicationDate":"2021-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1177/05390184211025848","citationCount":"0","resultStr":"{\"title\":\"When two science disciplines meet: Evaluating dynamics of conjunction. The encounter between astrophysics and artificial intelligence\",\"authors\":\"A. Marcovich, T. Shinn\",\"doi\":\"10.1177/05390184211025848\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article points out some issues raised by the encounter between astrophysics (AP) and a newly emergent mathematical tool/discipline, namely artificial intelligence (AI). We suggest that this encounter has interesting consequences in terms of science evaluation. Our discussion favors an intra science perspective, both on the institutional and cognitive side. This encounter between machine learning (ML) and astrophysics points to three different consequences. (1) As a transverse tool, a same ML algorithm can be used for a diversity of very different disciplines and questions. This ambition and analytic intellectual architecture frequently identify similarities among apparently differentiated fields. (2) The perimeter of the disciplines involved in a research can lead to many and novel ways of collaboration between scientists and to new ways of evaluation of their work. And (3), the impossibility for the human mind to understand the processes involved in ML work raises the question of the reliability of results.\",\"PeriodicalId\":47697,\"journal\":{\"name\":\"Social Science Information Sur Les Sciences Sociales\",\"volume\":\"60 1\",\"pages\":\"372 - 377\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2021-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1177/05390184211025848\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Social Science Information Sur Les Sciences Sociales\",\"FirstCategoryId\":\"90\",\"ListUrlMain\":\"https://doi.org/10.1177/05390184211025848\",\"RegionNum\":4,\"RegionCategory\":\"社会学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Social Science Information Sur Les Sciences Sociales","FirstCategoryId":"90","ListUrlMain":"https://doi.org/10.1177/05390184211025848","RegionNum":4,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
When two science disciplines meet: Evaluating dynamics of conjunction. The encounter between astrophysics and artificial intelligence
This article points out some issues raised by the encounter between astrophysics (AP) and a newly emergent mathematical tool/discipline, namely artificial intelligence (AI). We suggest that this encounter has interesting consequences in terms of science evaluation. Our discussion favors an intra science perspective, both on the institutional and cognitive side. This encounter between machine learning (ML) and astrophysics points to three different consequences. (1) As a transverse tool, a same ML algorithm can be used for a diversity of very different disciplines and questions. This ambition and analytic intellectual architecture frequently identify similarities among apparently differentiated fields. (2) The perimeter of the disciplines involved in a research can lead to many and novel ways of collaboration between scientists and to new ways of evaluation of their work. And (3), the impossibility for the human mind to understand the processes involved in ML work raises the question of the reliability of results.
期刊介绍:
Social Science Information is an international peer reviewed journal that publishes the highest quality original research in the social sciences at large with special focus on theoretical debates, methodology and comparative and (particularly) cross-cultural research.