Algorithmic Transparency and Accountability through Crowdsourcing: A Study of the NYC School Admission Lottery
Algorithmic Transparency and Accountability through Crowdsourcing: A Study of the NYC School Admission Lottery
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通过众包实现算法透明度和问责制：纽约市学校入学抽签研究
DOI：
10.1145/3593013.3594009
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Marian, Amelie
中科院分区：
文献类型：
--
作者：
Marian, Amelie
算法用于帮助制定广泛的公共政策决策。然而，算法过程的细节以及如何与系统交互的细节往往没有充分传达给利益相关者，使他们感到沮丧并对决策结果产生不信任。透明度和问责制是建立对决策结果的信任并保证结果公平公正的关键先决条件。不幸的是，组织和机构没有强烈的动机来解释和澄清他们的决策过程；然而，利益相关者并非无能为力，可以战略性地联合起来，推动提高透明度。在本文中，我讨论了这一努力的结果和经验教训：家长主导的众包活动，以提高纽约市学校招生过程的透明度。众所周知，纽约市使用延迟录取匹配算法将学生分配到学校，但家庭获得的关于他们必须参与的系统机制的信息很少，而且往往是错误的。此外，匹配到特定学校的几率取决于一套复杂的优先规则和打破平局的随机（抽签）号码，学生及其家人并不清楚这些规则对结果的影响，导致学生排名名单上出现许多“浪费选择”和很高的未匹配学生比例。利用学校申请结果的众包调查结果，我能够解释随机的决胜因素如何影响录取，从而增加了过程的清晰度和透明度。结果凸显了比赛中的几个问题和低效率，并证明系统中需要更多的问责和验证。
Algorithms are used to aid decision-making for a wide range of public policy decisions. Yet, the details of the algorithmic processes and how to interact with their systems are often inadequately communicated to stakeholders, leaving them frustrated and distrusting of the outcomes of the decisions. Transparency and accountability are critical prerequisites for building trust in the results of decisions and guaranteeing fair and equitable outcomes. Unfortunately, organizations and agencies do not have strong incentives to explain and clarify their decision processes; however, stakeholders are not powerless and can strategically combine their efforts to push for more transparency.In this paper, I discuss the results and lessons learned from such an effort: a parent-led crowdsourcing campaign to increase transparency in the New York City school admission process. NYC famously uses a deferred-acceptance matching algorithm to assign students to schools, but families are given very little, and often wrong, information on the mechanisms of the system in which they have to participate. Furthermore, the odds of matching to specific schools depend on a complex set of priority rules and tie-breaking random (lottery) numbers, whose impact on the outcome is not made clear to students and their families, resulting in many “wasted choices” on students’ ranked lists and a high rate of unmatched students. Using the results of a crowdsourced survey of school application results, I was able to explain how random tie-breakers factored in the admission, adding clarity and transparency to the process. The results highlighted several issues and inefficiencies in the match and made the case for the need for more accountability and verification in the system.
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DOI：
10.1145/3411764.3445748
发表时间：
2021-01
期刊：
Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems
影响因子：
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作者：
Samantha Robertson;Tonya Nguyen;Niloufar Salehi
通讯作者：
Samantha Robertson;Tonya Nguyen;Niloufar Salehi
DOI：
10.2139/ssrn.2860738
发表时间：
2018-04
期刊：
AARN: Schools (Topic)
影响因子：
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作者：
Inácio Bó;R. Hakimov
通讯作者：
Inácio Bó;R. Hakimov
DOI：
10.2139/ssrn.4016109
发表时间：
2022
期刊：
SSRN Electronic Journal
影响因子：
--
作者：
Sarah R. Cohodes;S. Corcoran;J. Jennings;Carolyn Sattin
通讯作者：
Carolyn Sattin
DOI：
10.1257/aer.p20171131
发表时间：
2017
期刊：
The American Economic Review
影响因子：
--
作者：
Kehinde F. Ajayi;Willa Friedman;Adrienne M. Lucas
通讯作者：
Adrienne M. Lucas
择校动态匹配：延迟取消后的高效座位重新分配（特邀演讲）
DOI：
10.2139/ssrn.2993375
发表时间：
2017
期刊：
Proceedings of the 50th Annual ACM SIGACT Symposium on Theory of Computing
影响因子：
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作者：
Irene Lo
通讯作者：
Irene Lo