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搜索引擎性别偏见。

Search Engine Gender Bias.

作者信息

Wijnhoven Fons, van Haren Jeanna

机构信息

Department of Industrial Engineering and Business Information Systems, University of Twente, Enschede, Netherlands.

出版信息

Front Big Data. 2021 May 26;4:622106. doi: 10.3389/fdata.2021.622106. eCollection 2021.

DOI:10.3389/fdata.2021.622106
PMID:34124651
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8187950/
Abstract

This article discusses possible search engine page rank biases as a consequence of search engine profile information. After describing search engine biases, their causes, and their ethical implications, we present data about the Google search engine (GSE) and DuckDuckGo (DDG) for which only the first uses profile data for the production of page ranks. We analyze 408 search engine screen prints of 102 volunteers (53 male and 49 female) on queries for job search and political participation. For job searches GSE, we find a bias toward stereotypically "female" jobs for women but also for men, although the bias is significantly stronger for women. For political participation, the bias of GSE is toward more powerful positions. Contrary to our hypothesis, this bias is even stronger for women than for men. Our analysis of DDG does not give statistically significant page rank differences for male and female users. We, therefore, conclude that GSE's personal profiling is not reinforcing a gender stereotype. Although no gender differences in page ranks was found for DDG, DDG usage in general gave a bias toward "male-dominant" vacancies for both men and women. We, therefore, believe that search engine page ranks are not biased by profile ranking algorithms, but that page rank biases may be caused by many other factors in the search engine's value chain. We propose ten search engine bias factors with virtue ethical implications for further research.

摘要

本文探讨了搜索引擎页面排名偏差可能是搜索引擎个人资料信息导致的结果。在描述了搜索引擎偏差、其成因及其伦理影响之后,我们展示了关于谷歌搜索引擎(GSE)和 DuckDuckGo(DDG)的数据,其中只有前者在生成页面排名时使用个人资料数据。我们分析了102名志愿者(53名男性和49名女性)在求职和政治参与查询方面的408张搜索引擎屏幕截图。对于GSE的求职搜索,我们发现女性和男性都存在偏向典型“女性”工作的偏差,不过女性的偏差更为显著。对于政治参与,GSE的偏差是偏向更有权力的职位。与我们的假设相反,这种偏差在女性中比在男性中更为强烈。我们对DDG的分析没有得出男性和女性用户在页面排名上有统计学显著差异的结果。因此,我们得出结论,GSE的个人资料分析并没有强化性别刻板印象。虽然在DDG中未发现页面排名上的性别差异,但总体而言,使用DDG对男性和女性都存在偏向“男性主导”职位空缺的偏差。因此,我们认为搜索引擎页面排名并非由个人资料排名算法导致偏差,而是页面排名偏差可能由搜索引擎价值链中的许多其他因素引起。我们提出了十个具有美德伦理意义的搜索引擎偏差因素以供进一步研究。

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Applying XAI to an AI-based system for candidate management to mitigate bias and discrimination in hiring.将可解释人工智能应用于基于人工智能的候选人管理系统,以减轻招聘过程中的偏见和歧视。
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本文引用的文献

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The science of fake news.假新闻的科学。
Science. 2018 Mar 9;359(6380):1094-1096. doi: 10.1126/science.aao2998. Epub 2018 Mar 8.
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The search engine manipulation effect (SEME) and its possible impact on the outcomes of elections.搜索引擎操纵效应(SEME)及其对选举结果可能产生的影响。
Proc Natl Acad Sci U S A. 2015 Aug 18;112(33):E4512-21. doi: 10.1073/pnas.1419828112. Epub 2015 Aug 4.
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Perspect Psychol Sci. 2012 May;7(3):203-20. doi: 10.1177/1745691612442904.
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Proc Natl Acad Sci U S A. 2013 Apr 9;110(15):5802-5. doi: 10.1073/pnas.1218772110. Epub 2013 Mar 11.
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