The Case for Voter-Centered Audits of Search Engines During Political Elections
The Case for Voter-Centered Audits of Search Engines During Political Elections
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政治选举期间以选民为中心的搜索引擎审计案例
DOI：
10.1145/3351095.3372835
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发表时间：
2020
期刊：
影响因子：
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通讯作者：
Devine, Claire
中科院分区：
文献类型：
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作者：
Mustafaraj, Eni;Lurie, Emma;Devine, Claire
搜索引擎根据不透明的规则将几个链接排在数百万个链接之前，这让自己面临偏见的批评。之前的研究集中在衡量搜索引擎算法的政治偏见，以检测搜索引擎操纵对选民的可能影响，或搜索结果中不平衡的意识形态表现。鉴于这些关切与公平原则有关，这种公平的概念可以被视为明确地面向选举候选人或政治进程，而只是含蓄地面向广大公众。因此，我们提出以下研究问题：一个明确以确保和最大限度地公平对待公众(即选民)的原则为中心的审计框架应该如何运作？为了回答这个问题，我们定性地探索了四个关于美国选举和政治的数据集：1)在2018年美国大选之前对合格的美国选民进行的关于他们信息需求的调查，2)在2018年美国大选前谷歌大规模审计中使用的有偏见的政治短语的数据集，3)谷歌对2018年美国大选中两组政治候选人的“相关搜索”短语(其中一组完全由女性组成)。以及4)在2019年美国弗吉尼亚州全州选举当天自动完成一系列搜索的建议和结果页面。我们发现，选民的信息需求比过去搜索引擎审计文献所描述的要广泛得多，依赖于选民建模的政治学理论为设计以选民为中心的审计提供了一个很好的起点。
Search engines, by ranking a few links ahead of million others based on opaque rules, open themselves up to criticism of bias. Previous research has focused on measuring political bias of search engine algorithms to detect possible search engine manipulation effects on voters or unbalanced ideological representation in search results. Insofar that these concerns are related to the principle of fairness, this notion of fairness can be seen as explicitly oriented toward election candidates or political processes and only implicitly oriented toward the public at large. Thus, we ask the following research question: how should an auditing framework that is explicitly centered on the principle of ensuring and maximizing fairness for the public (i.e., voters) operate? To answer this question, we qualitatively explore four datasets about elections and politics in the United States: 1) a survey of eligible U.S. voters about their information needs ahead of the 2018 U.S. elections, 2) a dataset of biased political phrases used in a large-scale Google audit ahead of the 2018 U.S. election, 3) Google's "related searches" phrases for two groups of political candidates in the 2018 U.S. election (one group is composed entirely of women), and 4) autocomplete suggestions and result pages for a set of searches on the day of a statewide election in the U.S. state of Virginia in 2019. We find that voters have much broader information needs than the search engine audit literature has accounted for in the past, and that relying on political science theories of voter modeling provides a good starting point for informing the design of voter-centered audits.