Automating the practice of science: Opportunities, challenges, and implications
Sebastian Musslick, Laura K Bartlett, Suyog H Chandramouli, Marina Dubova, Fernand Gobet, Thomas L Griffiths, Jessica Hullman, Ross D King, J Nathan Kutz, Christopher G Lucas, Suhas Mahesh, Franco Pestilli, Sabina J Sloman, William R Holmes
Proceedings of the National Academy of Science
Diagram of AI-assisted empirical behavioral research including automated model discovery, experimental design, and experimentation.
Abstract
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 conse- quences 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 stakehold- ers to navigate the rapidly evolving frontier of automated scientific practice.