Interrogating Human-centered Data Science: Taking Stock of Opportunities and Limitations. In CHI Conference on Human Factors in Computing Systems Extended Abstracts
Abstract
CHI EA '22: Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems
https://doi.org/10.1145/3491101.3503740
Data science has become an important topic for the CHI conference and community, as shown by many papers and a series of workshops. Previous workshops have taken a critical view of data science from an HCI perspective, working toward a more human–centered treatment of the work of data science and the people who perform the many activities of data science. However, those approaches have not thoroughly examined their own grounds of criticism. In this workshop, we deepen that critical view by turning a reflective lens on the HCI work itself that addresses data science. We invite new perspectives from the diverse research and practice traditions in the broader CHI community, and we hope to co-create a new research agenda that addresses both data science and human-centered approaches to data science.
Document Type
Conference Proceeding
Publication Date
4-28-2022
Recommended Citation
Tanweer, Anissa; Aragon, Cecilia R.; Muller, Michael; Guha, Shion MS, PhD; Neff, Gina; and Kogan, Marina, "Interrogating Human-centered Data Science: Taking Stock of Opportunities and Limitations. In CHI Conference on Human Factors in Computing Systems Extended Abstracts" (2022). Health Services and Informatics Research. 77.
https://researchrepository.parkviewhealth.org/informatics/77