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Research at the intersection of human-computer interaction (HCI) and health is increasingly done by collaborative cross-disciplinary teams. The need for cross-disciplinary teams arises from the interdisciplinary nature of the work itself—with the need for expertise in a health discipline, experimental design, statistics, and computer science, in addition to HCI. This work can also increase innovation, transfer of knowledge across fields, and have a higher impact on communities. To succeed at a collaborative project, researchers must effectively form and maintain a team that has the right expertise, integrate research perspectives and work practices, align individual and team goals, and secure funding to support the research. However, successfully operating as a team has been challenging for HCI researchers, and can be limited due to a lack of training, shared vocabularies, lack of institutional incentives, support from funding agencies, and more; which significantly inhibits their impact. This workshop aims to draw on the wealth of individual experiences in health project team collaboration across the CHI community and beyond. By bringing together different stakeholders involved in HCI health research, together, we will identify needs experienced during interdisciplinary HCI and health collaborations. We will identify existing practices and success stories for supporting team collaboration and increasing HCI capacity in health research. We aim for participants to leave our workshop with a toolbox of methods to tackle future team challenges, a community of peers who can strive for more effective teamwork, and feeling positioned to make the health impact they wish to see through their work.
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Interrogating Human-centered Data Science: Taking Stock of Opportunities and Limitations
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.
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- Award ID(s):
- 1850517
- PAR ID:
- 10502566
- Publisher / Repository:
- ACM
- Date Published:
- Journal Name:
- In Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems
- ISBN:
- 9781450391566
- Page Range / eLocation ID:
- 1 to 6
- Format(s):
- Medium: X
- Location:
- New Orleans LA USA
- Sponsoring Org:
- National Science Foundation
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