审计数字平台在经济机会广告中的歧视
Auditing Digital Platforms for Discrimination in Economic Opportunity Advertising
摘要：
包括社交网络在内的数字平台是经济信息的主要来源。有证据表明，数字平台向人口群体展示了不同的社会经济机会。我们的工作通过提出一种方法和软件来审计数字平台的偏见和歧视来解决这个问题。为了证明这一点，对Facebook平台和广告网络进行了审计。在2019年10月至2020年5月期间，我们从Facebook广告库API收集了141，063个广告。使用机器学习分类器，每个广告都被自动标记为主要营销类别（住房，就业，信贷，政治，其他）。对于每个类别，我们分析了广告内容按年龄组和性别的分布。根据审计结果，我们考虑并提出了限制，需求，基础设施和政策，使研究人员能够在未来进行更系统的审计，并倡导为什么必须做这项工作。我们还讨论了有偏见的分布如何影响人们所拥有的社会经济机会，特别是当在数字平台上，一些人口群体被不成比例地排除在接受法律规定的内容的人群之外时。
英文摘要：
Digital platforms, including social networks, are major sources of economic information. Evidence suggests that digital platforms display different socioeconomic opportunities to demographic groups. Our work addresses this issue by presenting a methodology and software to audit digital platforms for bias and discrimination. To demonstrate, an audit of the Facebook platform and advertising network was conducted. Between October 2019 and May 2020, we collected 141,063 ads from the Facebook Ad Library API. Using machine learning classifiers, each ad was automatically labeled by the primary marketing category (housing, employment, credit, political, other). For each of the categories, we analyzed the distribution of the ad content by age group and gender. From the audit findings, we considered and present the limitations, needs, infrastructure and policies that would enable researchers to conduct more systematic audits in the future and advocate for why this work must be done. We also discuss how biased distributions impact what socioeconomic opportunities people have, especially when on digital platforms some demographic groups are disproportionately excluded from the population(s) that receive(s) content regulated by law.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
