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Data-driven Humanitarian Mapping and Policymaking: Toward Planetary-Scale Resilience, Equity, and Sustainability

Published: 14 August 2022 Publication History
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  • Abstract

    Human civilization faces existential threats in the forms of climate change, food insecurity, pandemics, international conflicts, forced displacements, and environmental injustice. These overarching humanitarian challenges disproportionately impact historically marginalized communities worldwide. UN OCHA estimates that 274 million people will need humanitarian support in 2022. Despite growing perils to human and environmental well-being, there remains a paucity of publicly-engaged computing research to inform the design of interventions. Data science efforts exist, but they remain isolated from socioeconomic, environmental, cultural, and policy contexts at local and international scales. Moreover, biases and privacy infringements in data-driven methods further amplify existing inequalities. The result is that proclaimed benefits of data-driven innovations may remain inaccessible to policymakers, practitioners, and underserved communities whose lives they intend to transform. To address gaps in knowledge and improve the livelihood of marginalized populations, we have established the Data-driven Humanitarian Mapping and Policymaking, an interdisciplinary initiative.

    References

    [1]
    S Gaikwad, S Iyer, Y Lin, and D Lunga. 2020. Proceedings of KDD 2021 Workshop on Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning. arXiv preprint arXiv:2109.00435 (2020).
    [2]
    S Gaikwad, S Iyer, D Lunga, and E Bondi. 2021. Data-driven Humanitarian Map- ping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning. In Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining. 4125--4126.
    [3]
    S Gaikwad, S Iyer, D Lunga, and E Bondi. 2021. Proceedings of KDD 2021 Workshop on Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning. arXiv preprint arXiv:2109.00100 (2021).

    Cited By

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    • (2024)A five-year milestone: reflections on advances and limitations in GeoAI researchAnnals of GIS10.1080/19475683.2024.230986630:1(1-14)Online publication date: 29-Jan-2024

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    cover image ACM Conferences
    KDD '22: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
    August 2022
    5033 pages
    ISBN:9781450393850
    DOI:10.1145/3534678
    Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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    New York, NY, United States

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    Published: 14 August 2022

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    Author Tags

    1. algorithmic decision-making and ethics
    2. climate crisis
    3. community-based design
    4. computational social science
    5. data science and public policy
    6. data-driven humanitarian action
    7. fair and interpretable machine learning
    8. human-centered data science
    9. public policy
    10. remote sensing.
    11. social computing
    12. sustainable development

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    • (2024)A five-year milestone: reflections on advances and limitations in GeoAI researchAnnals of GIS10.1080/19475683.2024.230986630:1(1-14)Online publication date: 29-Jan-2024

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