How categories come to matter

Lucian Leahu, Marisa Cohn, Wendy March

    Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

    Abstract

    In a study of users' interactions with Siri, the iPhone personal assistant application, we noticed the emergence of overlaps and blurrings between explanatory categories such as "human" and "machine". We found that users work to purify these categories, thus resolving the tensions related to the overlaps. This "purification work" demonstrates how such categories are always in flux and are redrawn even as they are kept separate. Drawing on STS analytic techniques, we demonstrate the mechanisms of such "purification work." We also describe how such category work remained invisible to us during initial data analysis, due to our own forms of latent purification, and outline the particular analytic techniques that helped lead to this discovery. We thus provide an illustrative case of how categories come to matter in HCI research and design.
    Original languageEnglish
    Title of host publicationProceedings of the SIGCHI Conference on Human Factors in Computing Systems
    PublisherAssociation for Computing Machinery
    Publication date2013
    Pages3331-3334
    ISBN (Print)978-1-4503-1899-0
    DOIs
    Publication statusPublished - 2013

    Keywords

    • Human-Computer Interaction (HCI)
    • Siri
    • Purification Work
    • Explanatory Categories
    • Science and Technology Studies (STS)
    • Human-Machine Interaction
    • Category Work
    • Data Analysis Techniques

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