{"title":"Wikipedia and large language models: perfect pairing or perfect storm?","authors":"P. Thomas","doi":"10.1108/lhtn-03-2023-0056","DOIUrl":null,"url":null,"abstract":"\nPurpose\nThe purpose of this paper is to explore the potential benefits and challenges of using large language models (LLMs) like ChatGPT to edit Wikipedia.\n\n\nDesign/methodology/approach\nThe first portion of this paper provides background about Wikipedia and LLMs, explicating briefly how each works. The paper's second section then explores both the ways that LLMs can be used to make Wikipedia a stronger site and the challenges that these technologies pose to Wikipedia editors. The paper's final section explores the implications for information professionals.\n\n\nFindings\nThis paper argues that LLMs can be used to proofread Wikipedia articles, outline potential articles and generate usable Wikitext. The pitfalls include the technology's potential to generate text that is plagiarized or violates copyright, its tendency to produce “original research” and its tendency to generate incorrect or biased information.\n\n\nOriginality/value\nWhile there has been limited discussion among Wikipedia editors about the use of LLMs when editing the site, hardly any scholarship has been given to how these models can impact Wikipedia's development and quality. This paper thus aims to fill this gap in knowledge by examining both the potential benefits and pitfalls of using LLMs on Wikipedia.\n","PeriodicalId":39748,"journal":{"name":"Library Hi Tech News","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Library Hi Tech News","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1108/lhtn-03-2023-0056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose
The purpose of this paper is to explore the potential benefits and challenges of using large language models (LLMs) like ChatGPT to edit Wikipedia.
Design/methodology/approach
The first portion of this paper provides background about Wikipedia and LLMs, explicating briefly how each works. The paper's second section then explores both the ways that LLMs can be used to make Wikipedia a stronger site and the challenges that these technologies pose to Wikipedia editors. The paper's final section explores the implications for information professionals.
Findings
This paper argues that LLMs can be used to proofread Wikipedia articles, outline potential articles and generate usable Wikitext. The pitfalls include the technology's potential to generate text that is plagiarized or violates copyright, its tendency to produce “original research” and its tendency to generate incorrect or biased information.
Originality/value
While there has been limited discussion among Wikipedia editors about the use of LLMs when editing the site, hardly any scholarship has been given to how these models can impact Wikipedia's development and quality. This paper thus aims to fill this gap in knowledge by examining both the potential benefits and pitfalls of using LLMs on Wikipedia.
期刊介绍:
Library Hi Tech News (LHTN) helps busy professionals stay abreast of current events and developments in the library and information industry. LHTN publishes articles of varying lengths, reports from relevant conferences, and case studies of how technology is used in the library. The Editors work closely with authors who are new to publishing, and those who are seeking outlets for reporting on practical uses of IT in libraries. Publishing your article in LHTN can be "a place to start," analogous to a "poster session in print", and does not preclude publishing a more fulsome piece in a peer-reviewed journal at a later date. Readers consider LHTN as the source from which to hear what’s coming next in terms of technology development for academic and public libraries.