The uncontroversial ‘thingness’ of AI

IF 6.5 1区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY Big Data & Society Pub Date : 2023-07-01 DOI:10.1177/20539517231206794
Lucy Suchman
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Abstract

This commentary starts with the question ‘How is it that AI has come to be figured uncontroversially as a thing, however many controversies “it” may engender?’ Addressing this question takes us to knowledge practices that philosopher of science Helen Verran has named a ‘hardening of the categories’, processes that not only characterise the onto-epistemology of AI but also are central to its constituent techniques and technologies. In a context where the stabilization of AI as a figure enables further investments in associated techniques and technologies, AI's status as controversial works to reiterate both its ontological status and its agency. It follows that interventions into the field of AI controversies that fail to trouble and destabilise the figure of AI risk contributing to its uncontroversial reproduction. This is not to deny the proliferating data and compute-intensive techniques and technologies that travel under the sign of AI but rather to call for a keener focus on their locations, politics, material-semiotic specificity, and effects, including their ongoing enactment as a singular and controversial object.
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人工智能无可争议的“物性”
这篇评论以这样一个问题开始:“不管‘它’可能引发多少争议,人工智能是如何被毫无争议地视为一种东西的?”解决这个问题将我们带到了科学哲学家海伦·维兰(Helen Verran)称之为“类别强化”的知识实践中,这些过程不仅表征了人工智能的本体认识论,而且是其组成技术和技术的核心。在人工智能作为一个数字的稳定能够进一步投资于相关技术和技术的背景下,人工智能作为有争议的地位有助于重申其本体论地位和代理地位。因此,对人工智能争议领域的干预,如果不能给人工智能的数字带来麻烦和不稳定,就有可能导致其无可争议的再现。这并不是要否认在人工智能的标志下传播的激增的数据和计算密集型技术和技术,而是呼吁人们更加关注它们的位置、政治、物质符号学的特殊性和影响,包括它们作为一个单一的和有争议的对象正在进行的制定。
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来源期刊
Big Data & Society
Big Data & Society SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
10.90
自引率
10.60%
发文量
59
审稿时长
11 weeks
期刊介绍: Big Data & Society (BD&S) is an open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities, and computing and their intersections with the arts and natural sciences. The journal focuses on the implications of Big Data for societies and aims to connect debates about Big Data practices and their effects on various sectors such as academia, social life, industry, business, and government. BD&S considers Big Data as an emerging field of practices, not solely defined by but generative of unique data qualities such as high volume, granularity, data linking, and mining. The journal pays attention to digital content generated both online and offline, encompassing social media, search engines, closed networks (e.g., commercial or government transactions), and open networks like digital archives, open government, and crowdsourced data. Rather than providing a fixed definition of Big Data, BD&S encourages interdisciplinary inquiries, debates, and studies on various topics and themes related to Big Data practices. BD&S seeks contributions that analyze Big Data practices, involve empirical engagements and experiments with innovative methods, and reflect on the consequences of these practices for the representation, realization, and governance of societies. As a digital-only journal, BD&S's platform can accommodate multimedia formats such as complex images, dynamic visualizations, videos, and audio content. The contents of the journal encompass peer-reviewed research articles, colloquia, bookcasts, think pieces, state-of-the-art methods, and work by early career researchers.
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