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Algorithmic Transparency and Accountability through Crowdsourcing: A Study of the NYC School Admission Lottery

Published: 12 June 2023 Publication History

Abstract

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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  • (2024)Ending Affirmative Action Harms Diversity Without Improving Academic MeritProceedings of the 4th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization10.1145/3689904.3694706(1-17)Online publication date: 29-Oct-2024
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cover image ACM Other conferences
FAccT '23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency
June 2023
1929 pages
ISBN:9798400701924
DOI:10.1145/3593013
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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New York, NY, United States

Publication History

Published: 12 June 2023

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Author Tags

  1. accountability
  2. crowdsourcing
  3. school matching
  4. transparency

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Cited By

View all
  • (2024)Ending Affirmative Action Harms Diversity Without Improving Academic MeritProceedings of the 4th ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization10.1145/3689904.3694706(1-17)Online publication date: 29-Oct-2024
  • (2024)Beyond Individual Accountability: (Re-)Asserting Democratic Control of AIProceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency10.1145/3630106.3658541(74-84)Online publication date: 3-Jun-2024
  • (2024)Trust in AI-assisted Decision Making: Perspectives from Those Behind the System and Those for Whom the Decision is MadeProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642018(1-14)Online publication date: 11-May-2024
  • (2024)Understanding Contestability on the Margins: Implications for the Design of Algorithmic Decision-making in Public ServicesProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3641898(1-16)Online publication date: 11-May-2024

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