读写能力
计算机科学
相关性(法律)
工作流程
人工智能
背景(考古学)
机器翻译
语言工业
社会学
自然语言
理解法
教育学
政治学
法学
古生物学
生物
数据库
出处
期刊:Lebende Sprachen
[De Gruyter]
日期:2023-09-03
卷期号:68 (2): 283-330
被引量:11
标识
DOI:10.1515/les-2023-0024
摘要
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.
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