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MCA: Transparent and Accountable Decision Systems

MCA：透明且负责任的决策系统

基本信息

批准号：
2218975
负责人：
Amelie Marian
金额：
$ 45.57万
依托单位：
Rutgers University New Brunswick
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-01 至 2025-08-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2218975&HistoricalAwards=false
关键词：
MCA Transparent Accountable Decision Systems

项目摘要

Automated and algorithmic decision systems are used extensively to enact public policy. Despite their use within the public domain as automated decision-making and resource distribution tools, these systems are often opaque and not publicly audited. Details that could provide a measure of reason and accountability are often hidden within proprietary contracts with third-party vendors. Without transparent and explainable processes, it is not possible to verify whether the outcomes satisfy ethical and fairness constraints. Without accountability, there can be no trust in the decisions produced by these systems. This project focuses on accountability, transparency, and explainability in the context of automated decision systems for public policy. This Mid-Career Advancement (MCA)Award supports Amelie Marian to work with a partner/mentor who brings different expertise. The PI leverages her background in designing ranking systems and decision-making algorithms to collaborate with the partner’s team of legal scholars, policy researchers, and social scientists to develop guidelines and techniques for transparency and accountability in decision systems.This project addresses the accountability of algorithmic decisions through the perspectives of computation, law, and ethics. Transparency and accountability are critical prerequisites for building trust in the results of automated decisions and guaranteeing fair and equitable outcomes. The research involves secondary analysis of data used for public policy decisions in domains such as school admissions, vaccine and organ donation lists prioritization, job applications, public housing allocations, and ranked choice voting. The PI is using the MCA award also to deepen and create new collaborations with policy-makers, as well as establish new multidisciplinary collaborations with the project's mentor partner, Helen Nissenbaum, director of the Digital Life Initiative group at Cornell Tech. By involving a wide array of stakeholders and scholars, this research obtains a better understanding of what constitutes a fair, transparent, and accountable decisions, thereby increasing trust in the decision processes and leveraging algorithmic decision mechanisms for social good.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.

自动化和算法决策系统被广泛用于制定公共政策。尽管它们在公共领域被用作自动决策和资源分配工具，但这些系统通常是不透明的，并且没有公开审计。可以提供理由和责任衡量标准的细节通常隐藏在与第三方供应商签订的专有合同中。如果没有透明和可解释的过程，就不可能验证结果是否满足道德和公平约束。没有问责制，这些系统产生的决策就不可能得到信任。该项目侧重于公共政策自动化决策系统中的问责制、透明度和可解释性。这个职业中期发展（MCA）奖支持艾米丽·玛丽安与一位带来不同专业知识的合作伙伴/导师一起工作。首席检察官利用她在设计排名系统和决策算法方面的背景，与合作伙伴的法律学者、政策研究人员和社会科学家团队合作，制定决策系统透明度和问责制的指导方针和技术。本项目从计算、法律和伦理的角度探讨算法决策的责任。透明度和问责制是建立对自动化决策结果的信任和保证公平公正结果的关键先决条件。这项研究涉及对用于公共政策决策的数据进行二次分析，这些决策涉及的领域包括学校招生、疫苗和器官捐赠名单的优先排序、工作申请、公共住房分配和排序选择投票。PI还利用MCA奖加深和创建与政策制定者的新合作，并与项目的导师伙伴、康奈尔理工大学数字生活倡议小组主任海伦·尼森鲍姆（Helen Nissenbaum）建立新的多学科合作。通过涉及广泛的利益相关者和学者，这项研究对公平、透明和负责任的决策的构成有了更好的理解。从而增加对决策过程的信任，并利用算法决策机制为社会造福。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。