DDRIG: Automating Blackness: Race, Computing, and Politics in the Postwar United States

在战后的美国，政府官员和计算机专家试图通过计算机促进种族平等。数据库、数据库和其他计算机化系统承诺改变政府机构识别美国公民身份和向他们提供服务的方式。根据这一设想，计算机将作为无私的决策者，以一种没有主观解释或种族偏见的方式处理和处理公民的个人数据。然而，公民和种族正义活动人士警告说，设计糟糕的政府计算系统可能会混淆和具体化不平等。这项研究对这场争论进行了解读，并分析了由此产生的体系。它在更广泛的范围内反映了当代对计算和信息技术中算法偏见和不平等的担忧。通过强调过去推动计算不平等的政治力量和技术设计，论文强调了计算技术中最有害的元素可能被拆除、颠覆或重组的不同方式，并将引起立法者、计算机专业人员和致力于创建更公正的数据系统的学者的兴趣。为此，该项目将科学和技术研究的理论框架与档案研究相结合，以审查影响三种不同政府计算系统的开发和使用的种族观念：就业服务机构的就业服务匹配系统、执法部门的国家犯罪信息中心和公共卫生的流行病监测项目。该项目的问题是：美国政府的计算机系统和关于种族的社会科学思想是如何相互复杂化和相互塑造的？计算机化识别的技术实践如何成为政治和科学斗争的中心，以解释战后美国各种形式的种族不平等的原因和解决方案？民权活动家、社区研究人员、进步的政府官员和其他边缘化的技术人员如何看待种族平等和政府计算之间的关系？这一奖项反映了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。

In the postwar United States, government officials and computer experts sought to advance racial equality through computing. Data banks, databases, and other computerized systems promised to transform how government agencies identified American citizens and delivered services to them. Per this vision, computers would serve as disinterested decision-makers, processing and acting on citizens’ personal data in a manner lacking subjective interpretation or racial bias. However, citizens and racial justice activists warned that poorly designed government computing systems could obfuscate and reify inequalities. This research unpacks this debate and analyzes the systems that emerged from it. It speaks to contemporary concerns about algorithmic bias and inequities in computing and information technologies more broadly. By highlighting the political forces and technical designs that have driven computational inequalities in the past, the dissertation highlights different ways in which the most harmful elements of computing technologies might be dismantled, subverted, or retooled and will be of interest to lawmakers, computing professionals, and scholars committed to creating more just data systems.To this end, this project combines theoretical frameworks from Science and Technology Studies with archival research to examine the racial ideas that shaped the development and use of three different government computing systems: the employment service’s Job Service Matching System, law enforcement’s National Crime Information Center, and public health’s Epidemiologic Surveillance Project. The project asks: how did U.S. government computing systems and social scientific ideas about race complicate and mutually shape one another? How were the technical practices of computerized identification central sites for political and scientific struggles to explain the causes of, and solutions to, various forms of racial inequality in postwar America? How did civil rights activists, community researchers, progressive government officials, and other marginalized technologists envision the relationship between racial equality and government computing?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.