Reaping the rewards with minimal toil: Evaluating the polemics of artificial intelligence in academia and the future of academic writing
Shingirai Mugambiwa ()
Edelweiss Applied Science and Technology, 2024, vol. 8, issue 6, 3535-3541
Abstract:
The use of Artificial Intelligence in academic writing swings on the edge of revolution and obliteration, where the promise of unparalleled efficiency clashes with the specter of intellectual dilution, which challenges the essence of academic rigor and originality. This paper interrogates the ways in which the two extremes of innovation and traditional writing methods in academia can be integrated. As such, the paper argues that it is essential to incorporate new technologies and modern AI tools with critical and historical aspects of academic culture rather than replacing them. In essence, AI should only augment what researchers are able to do, not replace them. As a result, it is important to set specific guidelines and standards in order to deal with issues, of authorship, data collection, controlled storage, and validation of artificial intelligence products. Lastly, the paper recommends the necessity of training and education about AI tools for academics and scientists in institutions of higher learning. The academic community should seek to implement policies and strategies that allow for the use of AI technologies in the execution of scholarly activities without compromising the quality of academic writing.
Keywords: Academic integrity, Academic writing; Artificial intelligence, Efficiency, Ethics. (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:
Downloads: (external link)
https://learning-gate.com/index.php/2576-8484/article/view/2752/1040 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ajp:edwast:v:8:y:2024:i:6:p:3535-3541:id:2752
Access Statistics for this article
More articles in Edelweiss Applied Science and Technology from Learning Gate
Bibliographic data for series maintained by Melissa Fernandes ().