Filling holes in science draws collective attention, but most higher-order holes remain unexplored
Computers and SocietyDigital LibrariesSocial and Information Networks
Summary
The authors study how scientific progress often comes from connecting separate ideas, which they represent as points in a high-dimensional space. They use a math tool called persistent homology to find gaps or "holes" in knowledge, from simple disconnected ideas to complex gaps involving many concepts. They discover that when researchers fill expected gaps, they tend to get a lot of attention, especially in empirical sciences. However, as science advances, the number of complex gaps grows faster than the number that get filled, leaving many unexplored. The authors suggest that AI could help fill these complex gaps in knowledge.
Authors
Jiajie Luo, James A. Evans
Abstract
Much scientific discovery involves filling holes between ideas and arguments that unleash techno-scientific advance. Representing knowledge as high-dimensional concept embeddings, we use persistent homology to detect holes of increasing order, from gaps between disconnected ideas to higher-order cavities, and identify the research works that fill them. We find two empirical asymmetries. Researchers who fill anticipated holes are poised to draw collective attention by staging outsized novelty and foresight, indicating that bridging holes anticipates where science will converge, most strongly in empirical fields and least in formal and design fields. Yet as knowledge grows, higher-order holes explode while the fraction science fills collapses, leaving most higher-order combinations unexplored. These results call for a richer science of holes, and mark a frontier where contemporary AI might help fill the high-dimensional gaps human science opens.