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  • “Excavating AI” Re-excavated: Debunking a Fallacious Account of the JAFFE Dataset

    Author(s):
    Michael Lyons (see profile)
    Date:
    2021
    Group(s):
    Archives, Digital Art History, Digital Humanists, Linked Open Data, Science and Technology Studies (STS)
    Subject(s):
    Affect (Psychology), Artificial intelligence, Critical theory, Data mining, Information technology--Moral and ethical aspects, Machine learning
    Item Type:
    Article
    Tag(s):
    facial expression, training sets, affective computing, dataset, Affect, Critical data studies, Information ethics
    Permanent URL:
    http://dx.doi.org/10.17613/bw0d-7y90
    Abstract:
    Twenty-five years ago, my colleagues Miyuki Kamachi and Jiro Gyoba and I designed and photographed JAFFE, a set of facial expression images intended for use in a study of face perception. In 2019, without seeking permission or informing us, Kate Crawford and Trevor Paglen exhibited JAFFE in two widely publicized art shows. In addition, they published a nonfactual account of the images in the essay “Excavating AI: The Politics of Images in Machine Learning Training Sets.” The present article recounts the creation of the JAFFE dataset and unravels each of Crawford and Paglen’s fallacious statements. I also discuss JAFFE more broadly in connection with research on facial expression, affective computing, and human-computer interaction.
    Metadata:
    xml
    Published as:
    Online publication     Show details
    Pub. URL:
    https://zenodo.org/record/5140557
    Publisher:
    Zenodo
    Pub. Date:
    2021/7/28
    Website:
    https://zenodo.org
    Version:
    1
    Status:
    Published
    Last Updated:
    2 years ago
    License:
    Attribution-NonCommercial-NoDerivatives

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    Item Name: pdf excavating_ai_re_excavated.pdf
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