Artificial intelligence literacy for the language industry – with particular emphasis on recent large language models such as GPT-4

Q2 Arts and Humanities
Ralph Krüger
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引用次数: 0

Abstract

Abstract This article explores the concept of artificial intelligence (AI) literacy in the context of the language industry, placing particular emphasis on recent large language models such as GPT-4. After a brief introduction in which the relevance of AI literacy in the language industry is highlighted, the article provides a concise overview of artificial neural networks and a brief history of neural network-based artificial intelligence. This is intended to lay the conceptual groundwork for the subsequent discussion of the basic principles and capabilities of large language models. Then, the article investigates in detail the concept of AI literacy, discussing the AI Literacy Framework proposed by Long/Magerko (2020) and illustrating the interface between AI literacy and the two adjacent digital literacies of professional machine translation literacy and data literacy. The article then zooms in on the practical applicability of AI technologies by discussing areas where workflows in the language industry (with a focus on the computer-assisted translation process) could be automated or optimised through large language models. The article concludes with some general reflections on the relevance of field-specific and societal AI literacy in the presence of powerful AI technologies.
语言行业的人工智能素养——特别强调最近的大型语言模型,如GPT-4
本文探讨了语言行业背景下人工智能(AI)读写能力的概念,特别强调了最近的大型语言模型,如GPT-4。在简要介绍了语言行业中人工智能素养的相关性之后,文章提供了人工神经网络的简要概述和基于神经网络的人工智能的简史。这是为了为后续讨论大型语言模型的基本原则和功能奠定概念基础。然后,本文详细研究了人工智能素养的概念,讨论了Long/Magerko(2020)提出的人工智能素养框架,并说明了人工智能素养与专业机器翻译素养和数据素养这两个相邻的数字素养之间的接口。然后,文章通过讨论语言行业的工作流程(重点是计算机辅助翻译过程)可以通过大型语言模型自动化或优化的领域,放大了人工智能技术的实际适用性。文章最后对强大的人工智能技术存在下特定领域和社会人工智能素养的相关性进行了一些一般性思考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Lebende Sprachen
Lebende Sprachen Arts and Humanities-Language and Linguistics
CiteScore
0.70
自引率
0.00%
发文量
10
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