Why the ‘Computer says no’: illustrating big data’s discrimination risk through complex systems science

Rhoen, Michiel; Feng, Qu

doi:10.1093/idpl/ipy005

Cited by 4 publications

(1 citation statement)

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“…Vulnerable citizens are increasingly transformed into data subjects but have little ability to interrogate how their data is being collected, stored, analyzed, and used (Redden, 2018). We call this datafied marginalization ; where the risks of datafication are borne by data subjects and the benefits enjoyed by controllers (Cinnamon, 2017; Mann & Daly, 2019; Rhoen & Feng, 2018). Data collected, stored, and analyzed by companies and used by the government brings new complexities in terms of ownership, transparency, and accountability that impact social equity.…”

Section: Discussionmentioning

confidence: 99%

Social equity in the data era: A systematic literature review of data‐driven public service research

Ruijer

Porumbescu

Porter

et al. 2022

Public Administration Review

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Governments increasingly rely on large amounts of data to deliver public services. In response, there is a robust discussion about the implications of this trend for efficiency and economy, but much less attention is paid to social equity. To address this issue, our study synthesizes cross‐disciplinary research on the relationship between data‐driven public services and social equity. Based on a systematic literature review of 190 articles covering a decade of research, we demonstrate how public sector data applications relate to social equity in terms of access to services, treatment, service quality, and outcomes. Our review identifies key mechanisms related to data collection, storage, analysis, and usage that need to be addressed to ensure more equitable data‐driven public services. This review contributes to public administration research and practice by highlighting the complexities of social equity in the data era.

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