重要的数据:关于困惑的隐喻,将“数字”视为物质以及与人工智能的后人类合作

IF 0.2 4区 文学 0 LITERATURE
PARAGRAPH Pub Date : 2023-07-01 DOI:10.3366/para.2023.0428
Annie Ring
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引用次数: 0

摘要

本文认为,“数字”和“大数据”是混淆的隐喻,用于屏蔽技术对生活体验和地球的真实影响。现在,科技消费者全天候与互联网(或“网络”)相连,他们的数据可以被大规模收集和货币化。由此产生的新数据经济和人工智能技术需要仔细评估它们对人体、环境和新知识形式的影响。因此,在这篇文章中,我列出了所谓的数字现象的实质性影响:数据,它们在“云”中的大规模存储,以及它们在训练算法和人工智能(AI)的紧急形式中的应用。基于技术文化理论家(包括Donna Haraway, N. Katherine Hayles, Wendy Hui Kyong Chun和Elena Esposito)的学术研究,以及弗里德里希·尼采(Friedrich Nietzsche),卡尔·马克思(Karl Marx)和汉娜·阿伦特(Hannah Arendt)关于隐喻和暴力的长期哲学,我认为思考新媒体和技术在较少隐喻的地方更具伦理性,因此更能意识到技术与人类和后人类生活(包括人工智能)的纠缠本质。由此提出的数据重要的概念是为了在未来更公正地使用数据和机器认知。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Data that Matter: On Metaphors of Obfuscation, Thinking ‘the Digital’ as Material and Posthuman Cooperation with AI
This article argues that ‘the digital’ and ‘big data’ are metaphors of obfuscation, which are used to screen the real effects of technologies on lived experiences and the planet. Now that technology consumers are connected 24/7 to the Internet (or ‘Web’), their data can be gathered and monetized on a vast scale. The new data economies and AI technologies that have emerged as a result require careful evaluation regarding their effects on bodies, environments and new forms of knowledge. In this piece, I therefore lay out the material impacts of so-called digital phenomena: of data, their large-scale storage in the ‘Cloud’, and their use in training algorithms and emergent forms of artificial intelligence (AI). Building on scholarship by cultural theorists of technology including Donna Haraway, N. Katherine Hayles, Wendy Hui Kyong Chun and Elena Esposito, as well as long-standing philosophies of metaphor and violence by Friedrich Nietzsche, Karl Marx and Hannah Arendt, I make the case that thinking about new media and technology is more ethical where it is less metaphorical, and so more conscious of the entangled nature of technology with human and posthuman life, including AI. The resulting concept of data that matter is proposed with a view to more justice-oriented uses of data and machine cognition in the future.
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来源期刊
PARAGRAPH
PARAGRAPH LITERATURE-
CiteScore
0.30
自引率
0.00%
发文量
22
期刊介绍: Founded in 1983, Paragraph is a leading journal in modern critical theory. It publishes essays and review articles in English which explore critical theory in general and its application to literature, other arts and society. Regular special issues by guest editors highlight important themes and figures in modern critical theory.
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