Integrating Equity in Public Sector Data-Driven Decision Making: Exploring the Desired Futures of Underserved Stakeholders

Public sector agencies aim to innovate not just for efficiency but also to enhance equity. Despite the growing adoption of data-driven decision-making systems in the public sector, efforts to integrate equity as a primary goal often fall short. This typically arises from inadequate early-stage involvement of underserved stakeholders and prevalent misunderstandings concerning the authentic meaning of equity from these stakeholders' perspectives. Our research seeks to address this gap by actively involving undersevered stakeholders in the process of envisioning the integration of equity within public sector data-driven decisions, particularly in the context of a building department in a Northeastern mid-sized U.S. city. Applying a speed dating method with storyboards, we explore diverse equity-centric futures within the realm of local business development, a domain where small businesses, particularly women-and minority-owned businesses, historically confront inequitable distribution of public services. We explored three essential aspects of equity: monitoring equity, resource allocation prioritization, as well as information and equity. Our findings illuminate the complexities of integrating equity into data-driven decisions, offering nuanced insights about the needs of stakeholders. We found that attempts to monitor and incorporate equity goals into public sector decision-making can unexpectedly backfire, inadvertently sparking community apprehension and potentially exacerbating existing inequities. Small business owners, including those identifying as women-and minority-owned, advocated against the use of demographic-based data in equity-focused data-driven decision-making in the public sector, instead emphasizing factors such as community needs, application complexity, and uncertainties inherent in small businesses. Drawing from these insights, we propose design implications to assist designers of public sector data-driven decision-making systems to better accommodate equity considerations.

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Publication Details

Journal
Proceedings of the ACM on Human-Computer Interaction
Published
2024-11-07
DOI
https://doi.org/10.1145/3686905
Citations
4
Primary Topic
Smart Cities and Technologies
Type
article
Field-Weighted Citation Impact
1.28
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article

Integrating Equity in Public Sector Data-Driven Decision Making: Exploring the Desired Futures of Underserved Stakeholders

Bonnie Fan, Sarah Fox, Willa Yunqi Yang, Haiyi Zhu et al.
4 citations
Proceedings of the ACM on Human-Computer Interaction
Smart Cities and Technologies
1.28
article

Integrating Equity in Public Sector Data-Driven Decision Making: Exploring the Desired Futures of Underserved Stakeholders

Bonnie Fan, Sarah Fox, Willa Yunqi Yang, Haiyi Zhu, Motahhare Eslami, Yinan Li, Seyun Kim, John Zimmerman, Jennifer Ho, Jessie Ramey
article en
4 citations

Abstract

Public sector agencies aim to innovate not just for efficiency but also to enhance equity. Despite the growing adoption of data-driven decision-making systems in the public sector, efforts to integrate equity as a primary goal often fall short. This typically arises from inadequate early-stage involvement of underserved stakeholders and prevalent misunderstandings concerning the authentic meaning of equity from these stakeholders' perspectives. Our research seeks to address this gap by actively involving undersevered stakeholders in the process of envisioning the integration of equity within public sector data-driven decisions, particularly in the context of a building department in a Northeastern mid-sized U.S. city. Applying a speed dating method with storyboards, we explore diverse equity-centric futures within the realm of local business development, a domain where small businesses, particularly women-and minority-owned businesses, historically confront inequitable distribution of public services. We explored three essential aspects of equity: monitoring equity, resource allocation prioritization, as well as information and equity. Our findings illuminate the complexities of integrating equity into data-driven decisions, offering nuanced insights about the needs of stakeholders. We found that attempts to monitor and incorporate equity goals into public sector decision-making can unexpectedly backfire, inadvertently sparking community apprehension and potentially exacerbating existing inequities. Small business owners, including those identifying as women-and minority-owned, advocated against the use of demographic-based data in equity-focused data-driven decision-making in the public sector, instead emphasizing factors such as community needs, application complexity, and uncertainties inherent in small businesses. Drawing from these insights, we propose design implications to assist designers of public sector data-driven decision-making systems to better accommodate equity considerations.

Proceedings of the ACM on Human-Computer InteractionVol. 8(CSCW2)
University of Chicago (US), Chatham University (US), Arizona State University (US), Carnegie Mellon University (US)
Gender equality
Openalex Percentile: Top 17%
Smart Cities and Technologies
1.28
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