Artificial intelligence-assisted tools for redefining the communication landscape of the scholarly world

被引:19
作者
Razack, Habeeb Ibrahim Abdul [1 ,2 ]
Mathew, Sam T.
Saad, Fathinul Fikri Ahmad [1 ,3 ]
Alqahtani, Saleh A. [4 ,5 ,6 ]
机构
[1] Univ Pulra Malaysia, Fac Med & Hlth Sci, Serdang, Selangor, Malaysia
[2] King Saud Univ, Coll Med, Dept Cardiac Sci, Riyadh, Saudi Arabia
[3] Univ Pulra Malaysia, Hosp Pengajar, Nucl Imaging Unit, Serdang, Selangor, Malaysia
[4] Johns Hopkins Univ, Div Gastroenterol & Hepatol, Baltimore, MD USA
[5] King Faisal Specialist Hosp & Res Ctr, Liver Transplant Ctr, Riyadh, Saudi Arabia
[6] King Faisal Specialist Hosp & Res Ctr, Dept Biostatisl Epidemiol & Sci Comp, Riyadh, Saudi Arabia
来源
SCIENCE EDITING | 2021年 / 8卷 / 02期
关键词
Artificial intelligence; Machine learning; Peer review; Scholarly publishing; Science writing; AI;
D O I
10.6087/kcse.244
中图分类号
G2 [信息与知识传播];
学科分类号
05 ; 0503 ;
摘要
The flood of research output and increasing demands for peer reviewers have necessitated the intervention of artificial intelligence (AI) in scholarly publishing. Although human input is seen as essential for writing publications, the contribution of AI slowly and steadily moves ahead. AI may redefine the role of science communication experts in the future and transform the scholarly publishing industry into a technology-driven one. It can prospectively improve the quality of publishable content and identify errors in published content. In this article, we review various AI and other associated tools currently in use or development for a range of publishing obligations and functions that have brought about or can soon leverage much-demanded advances in scholarly communications. Several AI-assisted tools, with diverse scope and scale, have emerged in the scholarly market. AI algorithms develop summaries of scientific publications and convert them into plain-language texts, press statements, and news stories. Retrieval of accurate and sufficient information is prominent in evidence-based science publications. Semantic tools may empower transparent and proficient data extraction tactics. From detecting simple plagiarism errors to predicting the projected citation impact of an unpublished article, AI's role in scholarly publishing is expected to be multidimensional. AI, natural language processing, and machine learning in scholarly publishing have arrived for writers, editors, authors, and publishers. They should leverage these technologies to enable the fast and accurate dissemination of scientific information to contribute to the betterment of humankind.
引用
收藏
页码:134 / 144
页数:11
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