CHS:Small: Incorporating and Balancing Stakeholder Values in Algorithm Design

CHS:Small：在算法设计中纳入并平衡利益相关者价值观

基本信息

批准号：
1908688
负责人：
Haiyi Zhu
金额：
$ 50万
依托单位：
University of Minnesota-Twin Cities
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-08-01 至 2019-11-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1908688&HistoricalAwards=false
关键词：
CHS Small Incorporating Balancing Stakeholder

项目摘要

This project will create a general method for value-sensitive algorithm design and develop tools and techniques to help incorporate the tacit values of stakeholders, balance multiple stakeholders' values, and achieve collective goals in the development of an algorithm. The research community has paid increasing attention to the role of human values in algorithm design and development. For example, fairness-aware machine learning research attempts to translate fairness notions into formal algorithmic constraints and develop algorithms subject to such constraints. Despite the mathematical rigor of these approaches, prior research suggests a disconnect between the current discrimination-aware machine learning research and stakeholders' realities, context, and constraints; this disconnect is likely to undermine practical initiatives. Furthermore, studies have suggested that there are often tensions among a diverse set of values relevant to the design of the algorithm. A new general method will be developed in the context of Redesigning Wikipedia's Objective Revision Evaluation Service (ORES), a machine learning-based service designed to generate real-time predictions on edit quality and article quality, which will benefit vast numbers of people who consume the Wikipedia content either directly or indirectly through other applications.There are four major goals of this research. The first is to articulate and demonstrate a general method for creating algorithmic systems that respect and balance stakeholders' values. The second goal is to create techniques for generating an algorithmic system's value report and explaining the value trade-offs. The third goal to create, deploy, and evaluate social and technical innovations to address fundamental trade-offs between different values. The final goal is to design and implement improvements to ORES, which will improve a wide variety of applications that rely on ORES, and Wikipedia's content and community as a whole. For an example of the kinds of problems that must be solved, quality control algorithms that prioritize efficiency in deleting low quality content incur the risk of undermining the motivation of contributors in peer production communities, particularly new contributors who are still learning how to contribute. To date, however, little work has been conducted to create solutions to address tensions and trade-offs between different values in algorithm design. The research will be performed through multiple studies by stepping through the process for a diverse set of tasks, each of which will allow interaction with multiple stakeholders, who have different (and perhaps conflicting) values.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.

该项目将为价值敏感算法设计和开发工具和技术创建一种通用方法，以帮助纳入利益相关者的默契价值，平衡多个利益相关者的价值观，并实现算法开发的集体目标。研究界已越来越关注人类价值在算法设计和开发中的作用。例如，公平感知的机器学习研究试图将公平概念转化为正式的算法约束，并开发受此类约束的算法。尽管这些方法严格严格，但先前的研究表明，当前的歧视感知机器学习研究与利益相关者的现实，背景和约束之间存在脱节。这种断开连接可能会破坏实际举措。此外，研究表明，与算法的设计相关的一组价值集中通常存在紧张局势。将在重新设计Wikipedia的客观修订评估服务（ORES）的背景下开发一种新的通用方法，这是一种基于机器学习的服务，旨在生成有关编辑质量和文章质量的实时预测，这将使大量消耗Wikipedia内容的人直接或间接地通过其他应用程序来实现。这是这项研究的四个主要目标。首先是阐明并展示一种创建尊重和平衡利益相关者价值观的算法系统的一般方法。第二个目标是创建用于生成算法系统的价值报告并解释价值权衡的技术。创建，部署和评估社会和技术创新的第三个目标是解决不同价值观之间的基本权衡。最终目标是设计和实施对矿石的改进，这将改善依赖矿石的各种应用程序，以及Wikipedia的内容和整个社区。对于必须解决的各种问题的示例，质量控制算法优先考虑效率在删除低质量内容的效率上会导致破坏同伴生产社区的贡献者的动机，尤其是仍在学习如何贡献的新贡献者。然而，迄今为止，几乎没有开展工作来创建解决方案，以解决算法设计中不同值之间的紧张局势和权衡。这项研究将通过多项研究通过逐步完成各种任务的过程来进行，每项任务都将允许与多个利益相关者进行互动，这些利益相关者具有不同的（也许是矛盾的）价值观。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的智力和更广泛影响的评估来进行评估的支持，这是值得的。