Redliking: When Redlining Goes Online

Redliking: When Redlining Goes Online
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点赞:当红线上线时

DOI:
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发表时间:
2020
期刊:
Social Science Research Network
影响因子:
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通讯作者:
Allyson E. Gold
Allyson E. Gold
中科院分区:
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文献类型:
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作者:
Allyson E. Gold

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Airbnb 的结构、设计和算法创建了一个允许用户歧视的网站架构,以防止少数族裔房东从短期租赁平台获得与白人房东相同的经济利益,本文将这种现象称为“红色喜欢”。对于拥有额外沙发、空闲房间或闲置房屋的房东来说,Airbnb 提供了创造新收入来源和增加财富的机会。 Airbnb 鼓励潜在客人在考虑潜在住宿时查看房东照片和个人信息,从而导致交易中渗透到隐性和公开的偏见。这种偏见会产生财务后果。对房东收入率的实证研究发现,即使在控制位置、面积和便利设施的情况下,白人房东的收入也明显高于少数族裔房东。 Airbnb 的算法增强了个人用户偏见的影响和倾向,创建了一个系统,其中种族中立变量充当歧视的代理。当代的红色喜好与历史上与住房财富相关的不平等是相似的。在二十世纪初,红线地图被用来证明扣留黑人社区投资的合理性。如今,“红赞”继续将财富引导至白人社区,剥夺了少数族裔房东的重要收入来源,从而强化了系统性房地产障碍,并加剧了种族贫富差距。<br><br>本文探讨了 Airbnb 等网站对少数族裔短租房东遭受歧视的责任。最初颁布的反歧视法是为了废除红线并保护少数族裔消费者打击“红线”行为,但由于 Airbnb 等网站具有多种用途,因此其能力变得更加复杂。当客人使用该平台来识别和预订住宿时,房东则使用该网站来宣传可用的住宿。结合网络言论和平台经营者责任的司法解释,本文提出了通用功能测试和碎片功能测试两种方法来确定网站歧视短租主机的责任。本文注意到现有反歧视法律框架的局限性,认为消除“点红”需要吸收行为经济学中平台设计的经验教训,并消除网站算法放大和实施用户歧视的机会。
Airbnb’s structure, design, and algorithm create a website architecture that allows user discrimination to prevent minority hosts from realizing the same economic benefits from short-term rental platforms as white hosts, a phenomenon this Article refers to as ‘redliking.’ For hosts with an extra couch, spare room, or unused home, Airbnb provides an opportunity to create new income streams and increase wealth. Airbnb encourages prospective guests to view host photographs and personal information when considering potential accommodations, thereby inviting bias, both implicit and overt, to permeate transactions. This bias has financial consequences. Empirical research on host earning rates found that white hosts earn significantly more than their minority counterparts, even when controlling for location, size, and amenities. Airbnb’s algorithm augments the effects and propensity of individual user bias, creating a system wherein race neutral variables serve as proxies for discrimination. Contemporary redliking parallels historic inequality related to housing wealth. In the early twentieth century, redlining maps were used to justify withholding investments from Black communities. Today, redliking continues the practice of directing wealth to white communities, reinforces systemic real property barriers by depriving minority hosts of important revenue streams, and exacerbates the racial wealth gap.<br><br>This Article examines the liability of websites like Airbnb for discrimination experienced by minority short-term rental hosts. The ability of anti-discrimination laws originally enacted to abolish redlining and protect minority consumers to combat redliking is complicated by the fact that sites like Airbnb serve multiple purposes; while guests use the platform to identify and book lodging, hosts use the site to advertise available accommodations. Looking to judicial interpretation of online speech and platform operator liability, this Article proposes two approaches – a general function test and a fragmented function test – to determine website liability for discrimination against short-term rental hosts. Noting the limitations of the existing anti-discrimination legal framework, this Article argues that eradicating redliking requires incorporating lessons on platform design from behavioral economics as well as eliminating opportunities for website algorithms to amplify and operationalize user discrimination.