与人工智能竞争——记录和信息管理行业能否经受住挑战?

IF 0.8 Q3 INFORMATION SCIENCE & LIBRARY SCIENCE Records Management Journal Pub Date : 2022-03-29 DOI:10.1108/rmj-08-2021-0033
S. Xie, Li Siyi, Ruohua Han
{"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}
引用次数: 0

摘要

本研究的目的是报告一项关于记录和信息管理(RIM)行业在人工智能发展方面的能力的研究。设计/方法/方法:本研究采用演绎法设计,从牛津大学的研究中提炼出人工智能(AI)不敏感性指标、创造性智能和社会智能,并将其应用于ARMA International开发的当前RIM核心竞争力。手工编码和语义分析是主要的查询方法,给出了统计和定性结果。研究结果:目前,整个RIM行业都在抵制人工智能,但它并不是完全防人工智能的。为了证明人工智能,现有的胜任力模型需要重新设计,因为人工智能的抵抗部分和人工智能的倾向部分混合在一起,一些RIM理论和原则的处方不适合人工智能的判断或调整。它还需要为所有利益相关者之间的合作制定战略,以便我们能够在未来不利的组织决策之前抢先一步。如果说我们的专业性质让我们现在能够抵抗人工智能,那么我们的专业团结将确保我们在未来能够抵御人工智能。原创性/价值据作者所知,这篇论文在国际RIM社区中是第一篇。它提供了详细的AI不敏感性评估数据和针对整个RIM社区的针对性建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Records Management Journal
Records Management Journal INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
3.50
自引率
7.10%
发文量
11
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
期刊最新文献
Records management compliance: a case study of Kuwait’s College of Basic Education Strategy for auditing investigation records and information: a case study of records and information management in the Royal Malaysian Police Electronic records management amidst the seismic shift in the dynamic infosphere Insights into the current state of electronic health records adoption and utilisation in Tanzanian public primary healthcare facilities: a survey study Conceptual framework to explore artificial intelligence technology (AIT) readiness and adoption intention in records and information management (RIM) practices: a proposal
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1