A Human-Centered Approach to Algorithmic Services: Considerations for Fair and Motivating Smart Community Service Management that Allocates Donations to Non-Profit Organizations

A Human-Centered Approach to Algorithmic Services: Considerations for Fair and Motivating Smart Community Service Management that Allocates Donations to Non-Profit Organizations
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以人为本的算法服务:向非营利组织分配捐款的公平和激励智能社区服务管理的考虑

DOI:
10.1145/3025453.3025884
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发表时间:
2017
期刊:
Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems
影响因子:
--
通讯作者:
Lizarondo, Leah
Lizarondo, Leah
中科院分区:
--
文献类型:
--
作者:
Lee, Min Kyung;Kim, Ji Tae;Lizarondo, Leah

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算法越来越多地被纳入各种服务中,以协调多个利益相关者的需求和兴趣。我们如何设计这些算法服务,使其做出的决策不仅高效,而且公平且具有激励性?我们采用以人为本的方法来识别和解决构建以人为本的算法服务的挑战。我们正在为 412 Food Rescue 构建分配算法,该组织将食品捐赠与非营利组织相匹配。作为这个正在进行的项目的一部分,我们对服务组织工作人员、捐助者、志愿者、受援非营利组织及其客户以及普通公民中的多个利益相关者进行了访谈,以了解分配算法、界面和周围工作实践的设计方式。研究结果表明,我们需要理解并解释利益相关者持有的不同公平观念;考虑算法在现实世界中公平运行的人员、环境和界面;并保持自动化的意义和社交互动,以建立公平和激励性的算法服务。
Algorithms are increasingly being incorporated into diverse services that orchestrate multiple stakeholders' needs and interests. How can we design these algorithmic services to make decisions that are not only efficient, but also fair and motivating? We take a human-centered approach to identify and address challenges in building human-centered algorithmic services. We are in the process of building an allocation algorithm for 412 Food Rescue, an organization that matches food donations with non-profit organizations. As part of this ongoing project, we conducted interviews with multiple stakeholders in the service-organization staff, donors, volunteers, recipient non-profits and their clients, and everyday citizens-in order to understand how the allocation algorithm, interfaces, and surrounding work practices should be designed. The findings suggest that we need to understand and account for varying fairness notions held by stakeholders; consider people, contexts, and interfaces for algorithms to work fairly in the real world; and preserve meaningfulness and social interaction in automation in order to build fair and motivating algorithmic services.
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