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Research into recidivism risk prediction in the criminal legal system has garnered significant attention from HCI, critical algorithm studies, and the emerging field of human-AI decision-making.
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Predictive crime mapping: Arbitrary grids or street networks?
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Who Is Included in Human Perceptions of AI?: Trust and Perceived Fairness around Healthcare AI and Cultural Mistrust. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems . 1–14
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Comparing Generic and Community-Situated Crowdsourcing for Data Validation in the Context of Recovery from Substance Use Disorders. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems . 1–17
Sabirat Rubya, Joseph Numainville, and Svetlana Yarosh. 2021 · 2021
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A framework of high-stakes algorithmic decision-making for the public sector developed through a case study of child-welfare
Devansh Saxena, Karla Badillo-Urquiola, Pamela J Wisniewski, and Shion Guha. 2021 · 2021
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Automating inequality: How high-tech tools profile, police, and punish the poor
Virginia Eubanks. 2018 · 2018
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Human perceptions of fairness in algorithmic decision making: A case study of criminal risk prediction. In Proceedings of the 2018 World Wide Web Conference . 903–912
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Kernel density estimation (KDE) vs. hot-spot analysis–detecting criminal hot spots in the City of San Francisco. In Proceeding of the 21 Conference on Geo-Information Science
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Fairness and accountability design needs for algorithmic support in high-stakes public sector decision-making. In Proceedings of the 2018 chi conference on human factors in computing systems . 1–14
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Space and time efficient kernel density estimation in high dimensions
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Technical flaws of pretrial risk assessments raise grave concerns
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Toward algorithmic accountability in public services: A qualitative study of affected community perspectives on algorithmic decision-making in child welfare services. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems . 1–12
Anna Brown, Alexandra Chouldechova, Emily Putnam-Hornstein, Andrew Tobin, and Rhema Vaithianathan. 2019 · 2019
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Niels Van Berkel, Jorge Goncalves, Daniel Russo, Simo Hosio, and Mikael B Skov. 2021 · 2021
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Algorithms and housing discrimination: Rethinking HUD’s new disparate impact rule
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Human-centered data science: an introduction
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How child welfare workers reduce racial disparities in algorithmic decisions. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems . 1–22
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Reconciling data-driven crime analysis with human-centered algorithms
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Improving human-AI partnerships in child welfare: understanding worker practices, challenges, and desires for algorithmic decision support. In Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems . 1–18
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Algorithms Allegedly Penalized Black Renters. The US Government Is Watching
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Dipto Das, Shion Guha, Jed Brubaker, and Bryan Semaan. 2024 · 2024
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A Human-Centered Review of Algorithms in Homelessness Research
Erina Seh-Young Moon and Shion Guha. 2024 · 2024
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