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Content moderation, AI, and the question of scale

Big data & society, 2020-07, Vol.7 (2), p.205395172094323 [Peer Reviewed Journal]

The Author(s) 2020 ;The Author(s) 2020. This work is licensed under the Creative Commons Attribution – Non-Commercial License https://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;ISSN: 2053-9517 ;EISSN: 2053-9517 ;DOI: 10.1177/2053951720943234

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  • Title:
    Content moderation, AI, and the question of scale
  • Author: Gillespie, Tarleton
  • Subjects: Automation ; Content management ; Digital media ; Social media ; Social networks
  • Is Part Of: Big data & society, 2020-07, Vol.7 (2), p.205395172094323
  • Description: AI seems like the perfect response to the growing challenges of content moderation on social media platforms: the immense scale of the data, the relentlessness of the violations, and the need for human judgments without wanting humans to have to make them. The push toward automated content moderation is often justified as a necessary response to the scale: the enormity of social media platforms like Facebook and YouTube stands as the reason why AI approaches are desirable, even inevitable. But even if we could effectively automate content moderation, it is not clear that we should.
  • Publisher: London, England: SAGE Publications
  • Language: English
  • Identifier: ISSN: 2053-9517
    EISSN: 2053-9517
    DOI: 10.1177/2053951720943234
  • Source: DOAJ : Directory of Open Access Journals
    SAGE Open Access Journals
    AUTh Library subscriptions: ProQuest Central
    ROAD

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