RAPID: Countering Language Biases in COVID-19 Search Auto-Completes

新型冠状病毒(新冠肺炎)导致关于这种疾病、其传播和补救措施的在线搜索活动急剧增加。因此，搜索引擎可以显著影响公众对疾病的看法和公众采取的行动。如果搜索结果中存在语言偏见，那么在认知和采取的行动上也可能存在偏见。该项目将系统分析提供给英语和西班牙语用户的新冠肺炎相关搜索自动补全功能的差异。这一结果将产生关于算法偏差出现的新知识，并有助于确保在大规模卫生紧急情况下大规模传播卫生信息的公平性。这些研究结果将在紧急情况下以多种语言以通俗易懂的方式分享，以帮助确保在新冠肺炎大流行期间平等获得卫生信息。这些反馈可能有助于改善众多面临新冠肺炎疫情的个人的健康结果。该项目旨在通过日志分析和采访，得出在搜索引擎传播新冠肺炎相关健康信息时，消除基于语言的偏见的方法。该项目的第一步是审核西班牙语和英语的搜索自动完成结果，并测试在生成这两种语言的结果的方式上是否存在系统差异。下一步是利用有多个用户的焦点小组来了解自动补全查询如何影响说英语和说西班牙语的人理解新冠肺炎疾病的方式，并采取必要的预防措施。这两个阶段的发现将被结合起来，以生成设计搜索体验的指导方针，以在公共健康危机中支持健康公平。这一研究主题可能会吸引不同的学生研究人员，这可能有助于扩大对STEM研究职业管道的参与。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The novel coronavirus (COVID-19) has resulted in sharp increases in online search activity about the disease, its spread, and remedial actions. Hence, search engines can significantly influence public perceptions of the disease and the actions undertaken by the public. If there are language biases in the results of searches, there may also be biases in perceptions and actions taken. This project will systematically analyze the differences in COVID-19 related search auto-completes that are provided to English and Spanish speakers. The results will generate new knowledge on the emergence of algorithmic bias and help ensure equity in health information dissemination at scale amid large-scale health emergencies. The findings will be shared in easy-to-understand terms on an urgent basis in multiple languages to help ensure equal access to health information in the COVID-19 pandemic. This feedback could help improve the health outcomes for numerous individuals facing the COVID-19 pandemic.The project is designed to yield approaches for countering language-based bias in COVID-19 related health information dissemination by search engines using log analysis and interviews. The first step in this project is to audit the search auto-complete results in Spanish and English, and test if there are systematic differences in the way results are generated across the two languages. The next step is to this utilize focus groups with multiple users to understand how auto-complete queries affect the way English versus Spanish speakers understand COVID-19 disease and take necessary precautions. The findings from the two phases are to be combined to generate guidelines on designing search experiences that support health equity amid a public health crisis. This research topic is likely to attract a diverse range of student researchers, which could help broaden participation in STEM research career pipelines.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.