Role of Machine Learning and Organizational Structure in Science

34 Pages Posted: 30 Mar 2022 Last revised: 2 Jun 2023

See all articles by Moe Kyaw Thu

Moe Kyaw Thu

University of Tokyo

Shotaro Beppu

University of Tokyo

Masaru Yarime

The Hong Kong University of Science and Technology - Division of Public Policy; The University of Tokyo - Graduate School of Public Policy; University College London - Department of Science, Technology, Engineering and Public Policy

Sotaro Shibayama

University of Tokyo; CIRCLE Lund University

Date Written: February 6, 2022

Abstract

The progress of science increasingly relies on machine learning (ML) and machines work alongside humans in various domains of science. This study investigates the team structure of ML-related projects and analyzes the contribution of ML to scientific knowledge production under different team structure, drawing on bibliometric analyses of 25,000 scientific publications in various disciplines. Our regression analyses suggest that (1) interdisciplinary collaboration between domain scientists and computer scientists as well as the engagement of interdisciplinary individuals who have expertise in both domain and computer sciences are common in ML-related 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 depend on the depth of ML.

Keywords: Team science, machine learning, boundary spanner, collaboration, artificial intelligence, interdisciplinary science

Suggested Citation

Kyaw Thu, Moe and Beppu, Shotaro and Yarime, Masaru and Shibayama, Sotaro, Role of Machine Learning and Organizational Structure in Science (February 6, 2022). Available at SSRN: https://ssrn.com/abstract=4027904 or http://dx.doi.org/10.2139/ssrn.4027904

Moe Kyaw Thu

University of Tokyo ( email )

7-3-1 Hongo
Bunkyo-ku
Tokyo, 113-0033
Japan

Shotaro Beppu

University of Tokyo ( email )

7-3-1 Hongo
Bunkyo-ku
Tokyo, 113-0033
Japan

Masaru Yarime

The Hong Kong University of Science and Technology - Division of Public Policy ( email )

Room 4611, PPOL, HKUST
Clear Water Bay, Kowloon
Hong Kong
Hong Kong

HOME PAGE: http://yarime.net/

The University of Tokyo - Graduate School of Public Policy ( email )

Hongo 7-3-1
Bunkyo-ku
Tokyo, 113-0033
Japan

HOME PAGE: http://yarime.net/

University College London - Department of Science, Technology, Engineering and Public Policy ( email )

Gower Street
London, WC1E 6BT
United Kingdom

HOME PAGE: http://yarime.net

Sotaro Shibayama (Contact Author)

University of Tokyo ( email )

Hongo 7-3-1
Bunkyo-ku
Tokyo, Tokyo 113-8656
Japan

HOME PAGE: http://sotaroshibayama.weebly.com/

CIRCLE Lund University ( email )

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