沟通文化他者:生成式人工智能和大型语言模型中的信任与偏见

IF 2.1 2区 文学 0 LANGUAGE & LINGUISTICS
Christopher J. Jenks
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引用次数: 0

摘要

本文关注生成式人工智能中的信任和偏见问题,特别是基于大型语言模型的聊天机器人(如 ChatGPT)。讨论认为,跨文化交际学者必须做更多工作,以更好地理解生成式人工智能,更具体地说是大型语言模型,因为此类技术以表面上公正的方式生产和传播话语,强化了机器是社会了解种族主义和歧视等重要跨文化问题的客观资源这一普遍假设。因此,我们迫切需要了解信任和偏见是如何影响这些技术处理跨文化交流的核心话题和主题的。同样重要的是,要仔细研究社会如何利用人工智能和大型语言模型来开展重要的社会行动和实践,如历史或政治问题的教学和学习。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Communicating the cultural other: trust and bias in generative AI and large language models
This paper is concerned with issues of trust and bias in generative AI in general, and chatbots based on large language models in particular (e.g. ChatGPT). The discussion argues that intercultural communication scholars must do more to better understand generative AI and more specifically large language models, as such technologies produce and circulate discourse in an ostensibly impartial way, reinforcing the widespread assumption that machines are objective resources for societies to learn about important intercultural issues, such as racism and discrimination. Consequently, there is an urgent need to understand how trust and bias factor into the ways in which such technologies deal with topics and themes central to intercultural communication. It is also important to scrutinize the ways in which societies make use of AI and large language models to carry out important social actions and practices, such as teaching and learning about historical or political issues.
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来源期刊
CiteScore
4.20
自引率
7.70%
发文量
81
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