Theoretical Considerations on AI-based Business Models for Lexicography

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

Economics · Lexicographical order · Lexicography · Linguistics · Natural language processing · Political science · Computer Science · Lexicography and Language Studies · linguistics and terminology studies · Mathematics · Natural Language Processing Techniques · Philosophy