{"title":"Theoretical Considerations on AI-based Business Models for Lexicography","authors":"Henrik Køhler Simonsen","doi":"10.1515/lex-2023-0013","DOIUrl":null,"url":null,"abstract":"Abstract AI-generated text production is on the rise Zandan (2020), and AI writers seem to be playing an increasingly important role in marketing, L2 text production, lexicography and language teaching, cf. Simonsen (2020b; 2021a; 2022a; 2022b; Sharples/Pérez Y Pérez 2022; ChatGPT 2023; RYTR 2023; Writewithlaika 2023). In addition to that large national language datasets are being developed in many countries, cf. for example Kirchmeier et al. (2020), and these national word registers are expected to become an important backbone in AI-based lexicographic services. On this background, there seems to be a need for AI-based business models for lexicography. This article draws on a literature review focussing on business models and business-related considerations of relevance for lexicography. The insights from the literature review led to the development of a number of theoretical considerations on AI-based business models for lexicography. The article suggests three AI-based business models for different types of lexicography and demonstrates how these business models could be implemented in three concrete projects.","PeriodicalId":29876,"journal":{"name":"LEXICOGRAPHICA","volume":null,"pages":null},"PeriodicalIF":0.3000,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"LEXICOGRAPHICA","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/lex-2023-0013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"LANGUAGE & LINGUISTICS","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract AI-generated text production is on the rise Zandan (2020), and AI writers seem to be playing an increasingly important role in marketing, L2 text production, lexicography and language teaching, cf. Simonsen (2020b; 2021a; 2022a; 2022b; Sharples/Pérez Y Pérez 2022; ChatGPT 2023; RYTR 2023; Writewithlaika 2023). In addition to that large national language datasets are being developed in many countries, cf. for example Kirchmeier et al. (2020), and these national word registers are expected to become an important backbone in AI-based lexicographic services. On this background, there seems to be a need for AI-based business models for lexicography. This article draws on a literature review focussing on business models and business-related considerations of relevance for lexicography. The insights from the literature review led to the development of a number of theoretical considerations on AI-based business models for lexicography. The article suggests three AI-based business models for different types of lexicography and demonstrates how these business models could be implemented in three concrete projects.
Abstract AI-generated text production is on the rise Zandan (2020), and AI writers seem to play an increasingly important role in marketing, L2 text production, lexicography and language teaching, cf. Simonsen (2020b; 2021a; 2022a; 2022b; Sharples/Pérez Y Pérez 2022; ChatGPT 2023; RYTR 2023; Writewithlaika 2023)。此外,许多国家正在开发大型国家语言数据集,例如 Kirchmeier 等人 (2020),这些国家词库有望成为基于人工智能的词典服务的重要支柱。在此背景下,似乎有必要为词典学建立基于人工智能的商业模式。本文在文献综述的基础上,重点探讨了与词典学相关的商业模式和商业相关考虑因素。从文献综述中获得的启示促使我们对基于人工智能的词典学商业模式进行了一系列理论思考。文章针对不同类型的词典学提出了三种基于人工智能的商业模式,并展示了如何在三个具体项目中实施这些商业模式。