Corpus-based Critical Discourse Analysis on AI Policy: A Comparison Between North America and Developing Countries in East Asia

Feng Gu
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Abstract

Artificial Intelligence (AI) has undergone a global transformative impact on people’s lives. However, the realm of empirical research focused on AI within applied linguistics remains limited, predominantly dwelling on qualitative rhetoric and narrative analysis. This research aims to fill this gap by shedding light on the discursive constructions of AI policies between North America and developing countries in East Asia based on corpus data. Two corpora are constructed for quantitative study, utilizing keywords, collocates, and concordance analysis, and two dimensions of dialectical-relational approach are adopted to delve into the results. The findings reveals that both EA and NA prioritize AI-related efforts, but EA emphasizes more on economic and societal applications, while NA highlights governmental sectors’ efforts, cooperation with allies, and national security in AI deployment. The results are closely associated with their social context. This nuanced understanding of AI policy research holds significant implications for policymakers, stakeholders, and scholars actively involved in shaping responsible AI regulations and governance practices on an international scale.
基于语料库的人工智能政策批评话语分析:北美与东亚发展中国家的比较
人工智能(AI)对人们的生活产生了全球性的变革性影响。然而,应用语言学中人工智能的实证研究领域仍然有限,主要集中在定性修辞和叙事分析上。本研究旨在通过揭示基于语料库数据的北美和东亚发展中国家之间人工智能政策的话语构建来填补这一空白。构建两个语料库进行定量研究,运用关键词分析、搭配分析和一致性分析,并采用辩证关系法的两个维度对结果进行深入研究。调查结果显示,EA和NA都优先考虑人工智能相关工作,但EA更强调经济和社会应用,而NA则强调政府部门在人工智能部署方面的努力、与盟友的合作以及国家安全。结果与他们的社会环境密切相关。这种对人工智能政策研究的细致理解,对积极参与制定负责任的人工智能法规和国际范围内治理实践的政策制定者、利益相关者和学者具有重要意义。
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