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Pandemic and the City pp 279–305Cite as

Social Justice, Digitalization, and Health and Well-Being in the Pandemic City

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Part of the book series: Footprints of Regional Science ((VRS))

Abstract

Technological developments have been linked to the distribution of disease over time and relative to this vision—especially given today’s increasingly “smart” cities—disparities in health point to broader social and digital asymmetries and inequities. Accordingly, framing health as a social justice issue and addressing structural inequality as a critical determinant of disease incidence, this research attends to the consequences of pandemic crises in urban contexts, examining how digitalization and automation relate to health and differentiating dynamics and relations in the face of such crises. With particular attention to artificial intelligence (AI) and algorithmic performance and embracing a multi-faceted perspective on socio-technological antecedents and consequences, an integrated and in-depth exploration of pandemics and social justice is offered as a contribution to a larger cross-cutting literature. Moreover, in response to increasing calls for measures that look beyond technical aspects of AI and algorithmic performance to consider broader societal impacts, imperatives for metrics development are specified for assessing social justice implications of AI for urban pandemic management.

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Notes

  1. 1.

    https://www.city-journal.org/cities-and-pandemics-have-long-history.

  2. 2.

    https://health.gov/healthypeople/objectives-and-data/social-determinants-health.

  3. 3.

    https://www.rwjf.org/en/cultureofhealth/taking-action.html.

  4. 4.

    Although this term was introduced by Berwick (2020), it is used in in a different way here.

  5. 5.

    https://iapp.org/about/what-is-privacy/.

  6. 6.

    http://livewithai.org/ai-surveillance-human-rights-privacy/.

  7. 7.

    https://www.publichealthscotland.scot/our-organisation/about-public-health-scotland/supporting-whole-system-approaches/applying-a-whole-system-approach/.

  8. 8.

    https://www.ncsl.org/research/labor-and-employment/covid-19-essential-workers-in-the-states.aspx.

  9. 9.

    https://observer.com/2020/06/amazon-artificial-intelligence-monitor-warehouse-worker-social-distancing-coronavirus.

  10. 10.

    https://www.ncsl.org/research/labor-and-employment/covid-19-essential-workers-in-the-states.aspx.

  11. 11.

    MAU and MTU generally refers to the propensity for different outcomes at varying levels of spatial and temporal aggregation, respectively.

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Author information

Authors and Affiliations

  1. George Mason University, Arlington, VA, USA

    Laurie A. Schintler & Connie L. McNeely

Authors
  1. Laurie A. Schintler
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  2. Connie L. McNeely
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Correspondence to Laurie A. Schintler .

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Editors and Affiliations

  1. Department of Economics, Yeditepe University, Istanbul, Turkey

    Mehmet Güney Celbiş

  2. Programme Smart Cities and Data Analytics, Open University, Heerlen, The Netherlands

    Karima Kourtit

  3. Programme Smart Cities and Data Analytics, Open University, Heerlen, The Netherlands

    Peter Nijkamp

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Schintler, L.A., McNeely, C.L. (2023). Social Justice, Digitalization, and Health and Well-Being in the Pandemic City. In: Celbiş, M.G., Kourtit, K., Nijkamp, P. (eds) Pandemic and the City. Footprints of Regional Science(). Springer, Cham. https://doi.org/10.1007/978-3-031-21983-2_15

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