Remaking the landscape of scientific expertise: the emergent research program of total automation in science

• In Event: Expertise in the Age of AI

Abstract

This article examines an emergent research program aimed at the complete automation of science, analyzing how various automation projects funded by DARPA and others are working to replicate traditionally human scientific competencies. Rather than directly attempting to create fully autonomous robot scientists, these projects break down complex scientific work into discrete, automatable "tasks." While individual projects often preserve some role for human scientists, collectively they reveal a comprehensive blueprint for scientific automation. Through interviews with 26 DARPA contractors, program managers, and others involved in scientific automation, the authors demonstrate how automation efforts target three key domains of human scientific expertise: insight (hypothesis generation and pattern recognition), embodied knowledge (experimental procedures and techniques), and judgment (evaluation of scientific claims). Instead of simply trying to replicate human capabilities, these initiatives are actively reshaping scientific practice to be more amenable to machine intervention, through initiatives like standardized ontologies and machine-readable data formats. Although full automation faces significant technical and institutional challenges, this emergent program portends major changes in scientific practice and careers while raising important questions about the future role of human knowledge in scientific discovery. The article contributes to ongoing debates about artificial intelligence in science while challenging existing sociological accounts of scientific practice.

Authors

• David Peterson, Purdue University

• Bernard Joseph Koch, University of Chicago

• Aaron Panofsky, University of California-Los Angeles