Automating the practice of science: Opportunities, challenges, and implications
Journal article, 2025

Automation transformed various aspects of our human civilization, revolutionizing industries and streamlining processes. In the domain of scientific inquiry, automated approaches emerged as powerful tools, holding promise for accelerating discovery, enhancing reproducibility, and overcoming the traditional impediments to scientific progress. This article evaluates the scope of automation within scientific practice and assesses recent approaches. Furthermore, it discusses different perspectives to the following questions: where do the greatest opportunities lie for automation in scientific practice?; What are the current bottlenecks of automating scientific practice?; and What are significant ethical and practical consequences of automating scientific practice? By discussing the motivations behind automated science, analyzing the hurdles encountered, and examining its implications, this article invites researchers, policymakers, and stakeholders to navigate the rapidly evolving frontier of automated scientific practice.

metascience

computational scientific discovery

automation

AI for science

Author

Sebastian Musslick

Osnabrück University

Brown University

Laura K. Bartlett

London School of Economics and Political Science

Suyog H. Chandramouli

University of Alberta

Princeton University

Aalto University

Marina Dubova

Indiana University

Fernand Gobet

University of Roehampton

London School of Economics and Political Science

Thomas L. Griffiths

Princeton University

Jessica Hullman

Robert R. McCormick School of Engineering and Applied Science

Ross King

Chalmers, Computer Science and Engineering (Chalmers), Data Science and AI

University of Cambridge

J. Nathan Kutz

University of Washington

Christopher G. Lucas

University of Edinburgh

Suhas Mahesh

University of Toronto

Franco Pestilli

The University of Texas at Austin

Sabina J. Sloman

University of Manchester

William R. Holmes

Indiana University

Proceedings of the National Academy of Sciences of the United States of America

0027-8424 (ISSN) 1091-6490 (eISSN)

Vol. 122 5 e2401238121

Subject Categories (SSIF 2025)

Computer Sciences

DOI

10.1073/pnas.2401238121

PubMed

39869810

More information

Latest update

2/19/2025