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Data-driven Humanitarian Mapping: Harnessing Human-Machine Intelligence for High-Stake Public Policy and Resilience Planning

Published: 14 August 2021 Publication History
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    Humanitarian challenges, including natural disasters, food insecurity, climate change, racial and gender violence, environmental crises, the COVID-19 coronavirus pandemic, human rights violations, and forced displacements, disproportionately impact vulnerable communities worldwide. Despite these growing perils, there remains a notable paucity of data science research to scientifically inform equitable public policy decisions for improving the livelihood of at-risk populations. Scattered data science efforts exist to address these challenges, but they remain isolated from practice and prone to algorithmic harms. Consequently, proclaimed benefits of data-driven innovations remain inaccessible to policymakers, practitioners, and marginalized communities at the core of humanitarian actions and global development. To help address this gap, we propose the Data-driven Humanitarian Mapping Research Program, which focuses on developing novel data science methodologies that harness human-machine intelligence for high-stakes public policy and resilience planning. As a part of the initiative, we host the second KDD workshop to continue fostering a global community of researchers, policymakers, and practitioners to advance a commonly shared data science research agenda for just humanitarian actions, resilience planning, and sustainable development. We envision the Data-driven Humanitarian Mapping will bring in new paradigms for equitable data science and policy decision-making while helping create a sustainable world.

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    cover image ACM Conferences
    KDD '21: Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining
    August 2021
    4259 pages
    ISBN:9781450383325
    DOI:10.1145/3447548
    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 2021

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    Author Tags

    1. algorithmic decision making and ethics
    2. computational social science
    3. data-driven humanitarian actions
    4. fair and interpretable machine learning
    5. human-centered data science
    6. public policy
    7. remote sensing
    8. social computing
    9. sustainable development

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