SaTC: CORE: Large: Collaborative: Accountable Information Use: Privacy and Fairness in Decision-Making Systems

SaTC：核心：大型：协作：负责任的信息使用：决策系统中的隐私和公平

基本信息

批准号：
1704985
负责人：
Michael Tschantz
金额：
$ 45万
依托单位：
International Computer Science Institute
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2017
资助国家：
美国
起止时间：
2017-06-01 至 2023-05-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1704985&HistoricalAwards=false
关键词：
SaTC CORE Large Collaborative Accountable

项目摘要

Increasingly, decisions and actions affecting people's lives are determined by automated systems processing personal data. Excitement about these systems has been accompanied by serious concerns about their opacity and the threats that they pose to privacy, fairness, and other values. Recognizing these concerns, the investigators seek to make real-world automated decision-making systems accountable for privacy and fairness by enabling them to detect and explain violations of these values. The technical work is informed by, and applied to, online advertising, healthcare, and criminal justice, in collaboration with and as advised by domain experts. Addressing privacy and fairness in decision systems requires providing formal definitional frameworks and practical system designs. The investigators provide new notions of privacy and fairness that deal with both protected information itself and proxies for it, while handling context-dependent, normative definitions of violations. A fundamental tension they address pits the access given to auditors of a system against the system owners' intellectual property protections and the confidentiality of the personal data used by the system. The investigators decompose such auditing into stages, where the level of access granted to an auditor is increased when potential (but not explainable) violations of privacy or fairness are detected. Workshops and public releases of code and data amplify the investigators' interactions with policy makers and other stakeholders. Their partnerships with outreach organizations encourage diversity.

影响人们生活的决策和行动越来越多地由处理个人数据的自动化系统决定。人们对这些系统的兴奋伴随着对其不透明性以及它们对隐私、公平和其他价值观构成的威胁的严重担忧。调查人员试图通过使现实世界的自动决策系统能够检测和解释违反这些价值观的行为，使它们对隐私和公平负责。这项技术工作是由在线广告、医疗保健和刑事司法提供信息并应用于这些领域。合作解决决策系统中的隐私和公平问题需要提供正式的定义框架和实用的系统设计，以处理受保护的信息本身及其代理，同时处理上下文。他们解决的一个基本矛盾是，系统审计员的访问权限与系统所有者的知识产权保护和系统使用的个人数据的机密性相冲突。调查人员将此类审计分解为多个阶段。当发现潜在的（但无法解释的）侵犯隐私或公平的行为时，授予审计员的访问级别会增加。研讨会以及代码和数据的公开发布会增强调查人员与政策制定者和其他利益相关者的互动。鼓励多样性。