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Скачать или смотреть A Feminist Framework for Urban AI Governance I Data for Policy 2024

  • Data for Policy
  • 2024-07-19
  • 57
A Feminist Framework for Urban AI Governance I Data for Policy 2024
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Описание к видео A Feminist Framework for Urban AI Governance I Data for Policy 2024

"A Feminist Framework for Urban AI Governance: Addressing Challenges for Public-Private Partnerships"
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OVERVIEW:
📋This analysis provides a critical account of AI governance in the modern “smart city” through a feminist lens. Evaluating the case of Sidewalk Labs’ Quayside Project - a smart city development that was to be implemented in Toronto, Canada - it is argued that public-private partnerships can create harmful impacts when corporate actors seek to establish new ‘rules of the game’ regarding data regulation.
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Submission: DAP-2023-0175
AUTHOR:
Laine McCrory
Department of Communication and Culture, Toronto Metropolitan University, Toronto, Canada ; Department of Communication and Media Studies, York University, Toronto, Canada
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#smartcity #aigovernance #dataregulation
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ABSTRACT:
This analysis provides a critical account of AI governance in the modern “smart city” through a feminist lens. Evaluating the case of Sidewalk Labs’ Quayside Project - a smart city development that was to be implemented in Toronto, Canada - it is argued that public-private partnerships can create harmful impacts when corporate actors seek to establish new ‘rules of the game’ regarding data regulation. While the Quayside project was eventually abandoned in 2020, it demonstrates key observations for the state of urban algorithmic governance both within Canada and internationally. Articulating the need for a revitalized and participatory smart city governance program prioritzes meaningful engagement in the forms of transparency and accountability measures. Taking a feminist lens, it argues for a two-pronged approach to : integrating collective engagement from the outset in the design process, and ensuring the civilian data protection through a robust, rights-based privacy regulation strategy. Engaging with feminist theories of intersectionality in relation to technology and data collection, this framework articulates the need to understand the broader histories of social marginalisation when implementing governance strategies regarding artificial intelligence in cities.

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