Multiple Disciplinary Data Work Practices in Artificial Intelligence Research: a Healthcare Case Study in the UK
CoRR(2023)
摘要
Developing artificial intelligence (AI) tools for healthcare is a multiple
disciplinary effort, bringing data scientists, clinicians, patients and other
disciplines together. In this paper, we explore the AI development workflow and
how participants navigate the challenges and tensions of sharing and generating
knowledge across disciplines. Through an inductive thematic analysis of 13
semi-structured interviews with participants in a large research consortia, our
findings suggest that multiple disciplinarity heavily impacts work practices.
Participants faced challenges to learn the languages of other disciplines and
needed to adapt the tools used for sharing and communicating with their
audience, particularly those from a clinical or patient perspective. Large
health datasets also posed certain restrictions on work practices. We
identified meetings as a key platform for facilitating exchanges between
disciplines and allowing for the blending and creation of knowledge. Finally,
we discuss design implications for data science and collaborative tools, and
recommendations for future research.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要