{"title":"与人工智能竞争——记录和信息管理行业能否经受住挑战?","authors":"S. Xie, Li Siyi, Ruohua Han","doi":"10.1108/rmj-08-2021-0033","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThe purpose of this study is to report on a study that focused on the records and information management (RIM) profession’s competencies with respect to the development of AI.\n\n\nDesign/methodology/approach\nDesigned as deductive, the study distilled artificial intelligence (AI) insusceptibility indicators, creative intelligence and social intelligence, from the Oxford study and applied them to the current RIM core competencies developed by ARMA International. Manual coding and semantic analysis served as the primary inquiring methods, and both statistical and qualitative results are presented.\n\n\nFindings\nThe RIM profession as a whole is currently AI-resistant, yet it is not AI-proof. To be AI-proof, the existent competencies model needs to be redesigned as the AI-resistant parts are mingled with AI-prone ones, and the prescriptions of some RIM theories and principles are not ready for AI judgements or adjustments. It requires also strategizing collaborations among all stakeholders so that we can be one step ahead of future unfavorable organizational decisions. If our professional nature renders us AI-resistant for now, then it is our professional unity that will ensure us AI-proof in the future.\n\n\nOriginality/value\nTo the best of the authors’ knowledge, this paper is first of its kind within the international RIM community. It provides detailed assessment data on AI insusceptibility and targeted suggestions regarding the RIM community as a whole.\n","PeriodicalId":20923,"journal":{"name":"Records Management Journal","volume":" ","pages":""},"PeriodicalIF":0.8000,"publicationDate":"2022-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Competing with artificial intelligence – can the records and information management profession withstand the challenge?\",\"authors\":\"S. Xie, Li Siyi, Ruohua Han\",\"doi\":\"10.1108/rmj-08-2021-0033\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\nPurpose\\nThe purpose of this study is to report on a study that focused on the records and information management (RIM) profession’s competencies with respect to the development of AI.\\n\\n\\nDesign/methodology/approach\\nDesigned as deductive, the study distilled artificial intelligence (AI) insusceptibility indicators, creative intelligence and social intelligence, from the Oxford study and applied them to the current RIM core competencies developed by ARMA International. Manual coding and semantic analysis served as the primary inquiring methods, and both statistical and qualitative results are presented.\\n\\n\\nFindings\\nThe RIM profession as a whole is currently AI-resistant, yet it is not AI-proof. To be AI-proof, the existent competencies model needs to be redesigned as the AI-resistant parts are mingled with AI-prone ones, and the prescriptions of some RIM theories and principles are not ready for AI judgements or adjustments. It requires also strategizing collaborations among all stakeholders so that we can be one step ahead of future unfavorable organizational decisions. If our professional nature renders us AI-resistant for now, then it is our professional unity that will ensure us AI-proof in the future.\\n\\n\\nOriginality/value\\nTo the best of the authors’ knowledge, this paper is first of its kind within the international RIM community. It provides detailed assessment data on AI insusceptibility and targeted suggestions regarding the RIM community as a whole.\\n\",\"PeriodicalId\":20923,\"journal\":{\"name\":\"Records Management Journal\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2022-03-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Records Management Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1108/rmj-08-2021-0033\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Records Management Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/rmj-08-2021-0033","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
Competing with artificial intelligence – can the records and information management profession withstand the challenge?
Purpose
The purpose of this study is to report on a study that focused on the records and information management (RIM) profession’s competencies with respect to the development of AI.
Design/methodology/approach
Designed as deductive, the study distilled artificial intelligence (AI) insusceptibility indicators, creative intelligence and social intelligence, from the Oxford study and applied them to the current RIM core competencies developed by ARMA International. Manual coding and semantic analysis served as the primary inquiring methods, and both statistical and qualitative results are presented.
Findings
The RIM profession as a whole is currently AI-resistant, yet it is not AI-proof. To be AI-proof, the existent competencies model needs to be redesigned as the AI-resistant parts are mingled with AI-prone ones, and the prescriptions of some RIM theories and principles are not ready for AI judgements or adjustments. It requires also strategizing collaborations among all stakeholders so that we can be one step ahead of future unfavorable organizational decisions. If our professional nature renders us AI-resistant for now, then it is our professional unity that will ensure us AI-proof in the future.
Originality/value
To the best of the authors’ knowledge, this paper is first of its kind within the international RIM community. It provides detailed assessment data on AI insusceptibility and targeted suggestions regarding the RIM community as a whole.
期刊介绍:
■Electronic records management ■Effect of government policies on record management ■Strategic developments in both the public and private sectors ■Systems design and implementation ■Models for records management ■Best practice, standards and guidelines ■Risk management and business continuity ■Performance measurement ■Continuing professional development ■Consortia and co-operation ■Marketing ■Preservation ■Legal and ethical issues