Interrogating Human-centered Data Science: Taking Stock of Opportunities and Limitations
Interrogating Human-centered Data Science: Taking Stock of Opportunities and Limitations
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DOI：
10.1145/3491101.3503740
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发表时间：
2022-04
期刊：
影响因子：
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通讯作者：
A. Tanweer;Cecilia R. Aragon;Michael J. Muller;Shion Guha;Samir Passi;Gina Neff;M. Kogan
中科院分区：
文献类型：
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作者：
A. Tanweer;Cecilia R. Aragon;Michael J. Muller;Shion Guha;Samir Passi;Gina Neff;M. Kogan
数据科学已经成为CHI会议和社区的重要主题，正如许多论文和一系列研讨会所示。以前的研讨会从HCI的角度对数据科学进行了批判性的审视，致力于以更人性化的方式对待数据科学的工作和执行数据科学许多活动的人。然而，这些方法并没有彻底审查它们自己的批评理由。在这个研讨会中，我们通过对HCI工作本身进行反思透镜来深化这一批判性观点，这些工作本身涉及数据科学。我们邀请来自更广泛的CHI社区的不同研究和实践传统的新观点，我们希望共同创建一个新的研究议程，解决数据科学和以人为本的数据科学方法。
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.