Supporting Serendipity
نویسندگان
چکیده
Qualitative inductive methods are widely used in CSCW and HCI research for their ability to generatively discover deep contextualized insights, but these inherently manual human-resource-intensive processes often infeasible analyzing large corpora. Researchers have been increasingly interested ways apply qualitative "big" data problems, hoping achieve more generalizable results from larger amounts of while preserving the depth richness methods. In this paper, we describe a study researchers' work practices challenges, with an eye towards whether is appropriate domain human-AI collaboration what successful collaborations might entail. Our findings characterize participants' diverse methodological nuanced dynamics, identify areas where they benefit AI-based tools. While participants highlight messiness uncertainty analysis, still want full agency over process believe that AI should not interfere. provides investigation task delegability context offers directions design assistance honor serendipity, human agency, ambiguity.
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ژورنال
عنوان ژورنال: Proceedings of the ACM on human-computer interaction
سال: 2021
ISSN: ['2573-0142']
DOI: https://doi.org/10.1145/3449168