HKUST PPOL Newsletter Spring 2023

14 Research Showcase Thu, M. K., Beppu, S., Yarime, M., & Shibayama, S. (2022). Role of Machine and Organizational Structure in Science. and analyzes the contribution of ML to scientific knowledge production under different team structures, drawing on bibliometric analyses of 25,000 scientific publications in various disciplines. It is suggested by regression analyses that (1) interdisciplinary collaboration between domain scientists and computer scientists as well as the engagement his study investigates the team structure of machine learning (ML)-related projects T of interdisciplinary individuals who have expertise in both domain and computer sciences are common in MLrelated projects; (2) the engagement of interdisciplinary individuals seem more important in achieving high impact and novel discoveries, especially when a project employs computational and domain approaches interdependently; and (3) the contribution of ML and its implication to team structure depends on the depth of ML. Plos one, 17(8), e0272280. Machine learning related vs machine learning unrelated