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Geographies of Algorithmic Violence: Redlining the Smart City

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  • Sara Safransky

Abstract

City governments are embracing data‐driven and algorithmic planning to tackle urban problems. Data‐driven analytics have an unprecedented capacity to call urban futures into being. At the same time, they can depoliticize planning decisions. I argue that this shift calls urban studies scholars to investigate geographies of algorithmic violence—a repetitive and standardized form of violence that contributes to the racialization of space and spatialization of poverty. This article examines this broader phenomenon through the case of a proprietary market value assessment that is being used to guide development in cities across the United States. The assessment employs an algorithm that helps city officials make critical decisions about which neighborhoods to target for investment, disinvestment and public service upgrades or disconnections. I argue that the racial, infrastructural, and epistemological violence associated with this evaluation can potentially lead to a new kind of municipal redlining. The article brings insights from critical race theory into conversation with critical scholarship on algorithms by analyzing how algorithmic violence works through data‐driven planning technologies to depoliticize and leverage power while further entrenching racism and inequality.

Suggested Citation

  • Sara Safransky, 2020. "Geographies of Algorithmic Violence: Redlining the Smart City," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 44(2), pages 200-218, March.
  • Handle: RePEc:bla:ijurrs:v:44:y:2020:i:2:p:200-218
    DOI: 10.1111/1468-2427.12833
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    References listed on IDEAS

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    3. Kevin Fox Gotham, 2000. "Urban Space, Restrictive Covenants and the Origins of Racial Residential Segregation in a US City, 1900–50," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 24(3), pages 616-633, September.
    4. Matthew Tenney & Renee Sieber, 2016. "Data-Driven Participation: Algorithms, Cities, Citizens, and Corporate Control," Urban Planning, Cogitatio Press, vol. 1(2), pages 101-113.
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    Cited by:

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    2. Federico Cugurullo & Federico Caprotti & Matthew Cook & Andrew Karvonen & Pauline MᶜGuirk & Simon Marvin, 2024. "The rise of AI urbanism in post-smart cities: A critical commentary on urban artificial intelligence," Urban Studies, Urban Studies Journal Limited, vol. 61(6), pages 1168-1182, May.
    3. Frick, Karen Trappenburg PhD & Kumar, Tanu PhD & Mendonça Abreu, Giselle Kristina & Post, Alison PhD, 2021. "Benchmarking “Smart City” Technology Adoption in California: Developing and Piloting a Data Collection Approach," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt3797p0ws, Institute of Transportation Studies, UC Berkeley.
    4. Erin McElroy, 2023. "DIS/POSSESSORY DATA POLITICS: From Tenant Screening to Anti‐Eviction Organizing," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 47(1), pages 54-70, January.
    5. The Re‐Arrangements Collective & Fabien Cante & Ajmal Hussain & Timo Makori & Surer Qassim Mohamed & Alana Osbourne & Francesca Pilo' & Kavita Ramakrishnan & AbdouMaliq Simone & Rike Sitas & Adeem Suh, 2023. "Movement 3. Navigating Urban Arrangements," International Journal of Urban and Regional Research, Wiley Blackwell, vol. 47(3), pages 483-495, May.
    6. Ferreri, Mara & Sanyal, Romola, 2022. "Digital informalisation: rental housing, platforms, and the management of risk," LSE Research Online Documents on Economics 112794, London School of Economics and Political Science, LSE Library.

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