The ethical dimensions of Google autocomplete

IF 6.5 1区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY Big Data & Society Pub Date : 2023-01-01 DOI:10.1177/20539517231156518
Rosie Graham
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引用次数: 2

Abstract

What questions should we ask of Google’s Autocomplete suggestions? This article highlights some of the key ethical issues raised by Google’s automated suggestion tool that provides potential queries below a user’s search box. Much of the discourse surrounding Google’s suggestions has been framed through legal cases in which complex issues can become distilled into black-and-white questions of the law. For example, do Google have to remove a particular suggestion and do they have to pay a settlement for damages? This commentary argues that shaping this discourse along primarily legal lines obscures many of these other moral dimensions raised by Google Autocomplete. Building from existing typologies, this commentary first outlines the legal discourse before exploring five additional ethical challenges, each framed around a particular moral question in which all users have a stake. Written in the form of a commentary, the purpose of this article is not to conclusively answer the ethical questions raised, but rather to give an account of why these particular questions are worth debating. Autocomplete’s suggestions are not simply a mirror of what users are typing into Google’s search bar. Google’s official statement is that “Autocomplete is a time-saving but complex feature. It doesn’t simply display the most common queries on a given topic” but “also predict[s] individual words and phrases that are based on both real searches as well as word patterns found across the web” (Google, 2022). Both its underlying methods and associated terminology have changed throughout time, shifting between providing completions, suggestions, and predictions. In doing so, the grounds for potential critique are ever-changing, which means that Google’s approach to Autocomplete deserves significant scrutiny.
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谷歌自动完成的伦理维度
对于b谷歌的自动补全建议,我们应该问哪些问题?这篇文章重点介绍了b谷歌的自动建议工具提出的一些关键的道德问题,该工具在用户的搜索框下面提供潜在的查询。围绕b谷歌建议的许多讨论都是通过法律案例来框定的,在这些案例中,复杂的问题可以被提炼成非黑即白的法律问题。例如,b谷歌是否必须删除一个特定的建议,他们是否必须支付损害赔偿?这篇评论认为,按照主要的法律路线来塑造这一话语,模糊了谷歌自动完成提出的许多其他道德维度。基于现有的类型学,本评论首先概述了法律话语,然后探索了五个额外的道德挑战,每个挑战都围绕着一个特定的道德问题,所有用户都有利害关系。这篇文章以评论的形式写成,目的并不是要结论性地回答所提出的伦理问题,而是要说明为什么这些特定的问题值得讨论。自动补全的建议并不仅仅是用户在b谷歌搜索栏中输入内容的镜像。谷歌的官方声明是“自动补全是一个节省时间但复杂的功能。它不仅显示给定主题上最常见的查询”,而且“还预测基于真实搜索以及在网络上发现的单词模式的单个单词和短语”(b谷歌,2022)。它的基本方法和相关术语随着时间的推移而变化,在提供完井、建议和预测之间转换。在这样做的过程中,潜在的批评理由是不断变化的,这意味着谷歌对自动完成的方法值得仔细审查。
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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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