{"title":"The power of generative AI for CRIS systems: a new paradigm for scientific information management","authors":"Anna Guillaumet","doi":"10.1016/j.procs.2024.11.057","DOIUrl":null,"url":null,"abstract":"<div><div>The paper analyses the implications of the emergence of artificial intelligence (AI), especially generative AI, on current research information systems (CRIS). It reviews the recent European regulations for high-risk AI systems, the Spanish AI strategy, and the IntelComp project as use cases. The study found that the maturity of CRIS systems, coupled with the increasing complexity due to data aggregation, sets the stage for innovative AI applications. The paper proposes key domains where AI can impact and be applied in CRIS, including data management, research assessment, and advanced analytics. It also provides examples of how generative AI can be leveraged to enhance scientific information management within CRIS. The findings highlight the need to ensure the responsible and ethical development of AI technologies in the research domain.</div></div>","PeriodicalId":20465,"journal":{"name":"Procedia Computer Science","volume":"249 ","pages":"Pages 131-149"},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Procedia Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S187705092403268X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The paper analyses the implications of the emergence of artificial intelligence (AI), especially generative AI, on current research information systems (CRIS). It reviews the recent European regulations for high-risk AI systems, the Spanish AI strategy, and the IntelComp project as use cases. The study found that the maturity of CRIS systems, coupled with the increasing complexity due to data aggregation, sets the stage for innovative AI applications. The paper proposes key domains where AI can impact and be applied in CRIS, including data management, research assessment, and advanced analytics. It also provides examples of how generative AI can be leveraged to enhance scientific information management within CRIS. The findings highlight the need to ensure the responsible and ethical development of AI technologies in the research domain.