Community Responsive Algorithms for Social Accountability (CRASA)

社会责任社区响应算法 (CRASA)

基本信息

批准号：
2131504
负责人：
Ryan Kennedy
金额：
$ 74.99万
依托单位：
University of Houston
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-10-01 至 2024-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2131504&HistoricalAwards=false
关键词：
Community Responsive Algorithms Social Accountability

项目摘要

The Community Responsive Algorithms for Social Accountability (CRASA) project will establish a model for accountability that can be applied across a comprehensive range of algorithms being used in public policy in various contexts. The project’s goals will be achieved through a three-year community-based participatory research program focusing on Harris County, Texas, incorporating input from stakeholders in local government, the legal community, and industry. Relying on input from community stakeholders, this project will develop an algorithm-accountability benchmark (AAB) that will be applied to a variety of public policy algorithms used by governments, advocacy groups, and corporations for design and evaluation. In co-operation with community partners, CRASA will promote broad application of this benchmark approach in the public policy sphere. The development and explication of specific standards through the AAB will provide a clear and reproducible touchstone for development, evaluation, and implementation of algorithms in public policy. CRASA will also contribute to education and workforce development by producing a set of educational materials on the use of algorithms that can be easily accessed by legal professionals and the general public; by developing a multidisciplinary undergraduate/graduate course for students on the ethics of artificial intelligence; and, by training the next generation of scholars interested in responsive and transparent algorithms for use in public policy.The use of algorithms in public policy has expanded dramatically in recent decades. They currently play an active part in informing policymakers in their decisions related to criminal justice, public education, the allocation of public resources, and even national defense strategy. However, standards of accountability reflecting current legal obligations and societal concerns have lagged far behind their extensive use and influence. CRASA’s community-based research strategy will answer questions about how to make the use of algorithms more accountable, and, specifically, how benchmarks of accountability can be established for these algorithms that will engender legitimacy and public trust. The project’s overall research strategy involves five objectives: Objective 1 – collect needed information through interviews with stakeholders representing a wide variety of interests in the application of public policy algorithms and establish a community advisory board that meets regularly to guide and evaluate the research; Objective 2 – conduct a comprehensive review of the quickly evolving legal precedents and academic proposals being set forth for algorithm regulation; Objective 3 – design an algorithm-accountability benchmark (AAB) that can be applied across policy areas to evaluate and compare algorithms in terms of their accountability standards; Objective 4 – conduct behavioral experiments, both within the legal community and the general public, to evaluate public trust and understanding of the AAB; and Objective 5 – develop a software scoring toolkit that will provide the AAB score for any software and demonstrate its use in two application domains: criminal risk estimation and facial recognition.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.

社区响应式社会问责制（CRASA）项目将建立一个责任模型，可以在各种情况下在公共政策中使用的全面算法应用。该项目的目标将通过针对德克萨斯州哈里斯县的三年基于社区的参与研究计划实现，并编码地方政府，法律界和行业的利益相关者的意见。依靠社区利益相关者的意见，该项目将开发算法 - 账目基准（AAB），该基准将应用于政府，倡导组织和公司设计和评估公司使用的各种公共政策算法。在与社区合作伙伴的合作中，CRASA将在公共政策领域促进这种基准方法的广泛应用。通过AAB来开发和阐明特定标准将为开发，评估和实施公共政策中的开发，评估和实施提供清晰且可再现的试金石。 Crasa还将通过生产有关使用算法的一套教育材料来为教育和劳动力发展做出贡献，这些材料可以由法律专业人员和公众轻松访问这些算法；通过为学生的人工智能道德规范开发多学科的本科/研究生课程；而且，通过培训对公共政策中响应式和透明算法感兴趣的下一代学者。在近几十年来，公共政策中使用算法的使用已大大扩展。他们目前在向决策者提供与刑事司法，公共教育，公共资源分配甚至国防战略有关的决策方面发挥积极作用。但是，反映当前法律义务和社会问题的问责制标准远远落后于其广泛使用和影响力。 CRASA的基于社区的研究策略将回答有关如何更责任使用算法的问题，具体来说，如何为这些算法建立问责制的基准，这些算法将导致合法性和公众信任。该项目的整体研究策略涉及五个目标：目标1 - 通过与代表公共政策算法的各种利益的利益相关者的访谈收集所需信息，并建立一个社区顾问委员会，该委员会定期开会以指导和评估研究；目标2 - 对正在不断发展的法律先例和算法规定的学术建议进行全面审查；目标3 - 设计算法 - 估算基准（AAB），可以在政策领域应用，以根据其问责制标准评估和比较算法；目标4 - 在法律界和公众内进行行为实验，以评估公众对AAB的信任和理解；和目标5 - 开发一个软件评分工具包，该工具包将为任何软件提供AAB分数，并证明其在两个应用程序领域中的用途：犯罪风险估算和面部识别。该奖项反映了NSF的法定任务，并被认为是通过基金会的知识功绩和更广泛的影响审查标准来通过评估来评估的。