From insight to innovation: Harnessing artificial intelligence for dynamic literature reviews

IF 2.5 3区 管理学 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE
Stephen Buetow , Joshua Lovatt
{"title":"From insight to innovation: Harnessing artificial intelligence for dynamic literature reviews","authors":"Stephen Buetow ,&nbsp;Joshua Lovatt","doi":"10.1016/j.acalib.2024.102901","DOIUrl":null,"url":null,"abstract":"<div><p>The factors contributing to different levels of artificial intelligence (AI) adoption by librarians and their patrons need clarifying in the context of literature reviews. This paper addresses this need by exploring the transformative impact of AI on literature reviews, particularly within academic librarianship in the health sciences. Drawing on literature and professional experience, it examines how AI is reshaping reviews, potentially extending their meaning beyond text-based sources to accommodate multimedia content and predictive insights. While highlighting AI's promise in enhancing research efficiency and comprehensiveness, the paper also notes the lack of documentation of AI's uptake for literature reviews, perhaps reflecting concerns over reliability and biases. Proposed strategies for moving forward include matching different literature reviews with the most appropriate AI systems. This alignment guides librarians and researchers in navigating the complexities of AI adoption, using human oversight to ensure the integrity and quality of AI content. The paper underscores the importance of education, training, and continuous consultation to promote trustworthy and responsible AI utilization. This pathway foresees more robust outcomes from literature reviews in domains like health care in the digital age.</p></div>","PeriodicalId":47762,"journal":{"name":"Journal of Academic Librarianship","volume":"50 4","pages":"Article 102901"},"PeriodicalIF":2.5000,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0099133324000624/pdfft?md5=0d7901072dae22d9ff6cb26bad9c26b4&pid=1-s2.0-S0099133324000624-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Academic Librarianship","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0099133324000624","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0

Abstract

The factors contributing to different levels of artificial intelligence (AI) adoption by librarians and their patrons need clarifying in the context of literature reviews. This paper addresses this need by exploring the transformative impact of AI on literature reviews, particularly within academic librarianship in the health sciences. Drawing on literature and professional experience, it examines how AI is reshaping reviews, potentially extending their meaning beyond text-based sources to accommodate multimedia content and predictive insights. While highlighting AI's promise in enhancing research efficiency and comprehensiveness, the paper also notes the lack of documentation of AI's uptake for literature reviews, perhaps reflecting concerns over reliability and biases. Proposed strategies for moving forward include matching different literature reviews with the most appropriate AI systems. This alignment guides librarians and researchers in navigating the complexities of AI adoption, using human oversight to ensure the integrity and quality of AI content. The paper underscores the importance of education, training, and continuous consultation to promote trustworthy and responsible AI utilization. This pathway foresees more robust outcomes from literature reviews in domains like health care in the digital age.

从洞察到创新:利用人工智能进行动态文献审查
导致图书馆员及其读者采用人工智能(AI)的不同程度的因素需要在文献评论的背景下加以澄清。本文针对这一需求,探讨了人工智能对文献评论的变革性影响,特别是在健康科学领域的学术图书馆中。本文以文献和专业经验为基础,探讨了人工智能如何重塑文献综述,将其意义扩展到基于文本的来源之外,以容纳多媒体内容和预测性见解。论文强调了人工智能在提高研究效率和全面性方面的前景,同时也注意到人工智能在文献综述中的应用缺乏文献记录,这或许反映了人们对可靠性和偏见的担忧。建议的前进战略包括将不同的文献综述与最合适的人工智能系统相匹配。这种匹配可以指导图书馆员和研究人员驾驭人工智能应用的复杂性,利用人工监督确保人工智能内容的完整性和质量。本文强调了教育、培训和持续咨询对于促进可信和负责任地使用人工智能的重要性。这一途径可以预见,在数字时代的医疗保健等领域,文献综述将产生更有力的成果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of Academic Librarianship
Journal of Academic Librarianship INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
5.30
自引率
15.40%
发文量
120
审稿时长
29 days
期刊介绍: The Journal of Academic Librarianship, an international and refereed journal, publishes articles that focus on problems and issues germane to college and university libraries. JAL provides a forum for authors to present research findings and, where applicable, their practical applications and significance; analyze policies, practices, issues, and trends; speculate about the future of academic librarianship; present analytical bibliographic essays and philosophical treatises. JAL also brings to the attention of its readers information about hundreds of new and recently published books in library and information science, management, scholarly communication, and higher education. JAL, in addition, covers management and discipline-based software and information policy developments.
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信