How Science Thinks: Collective Cognition and the Selection of Scientific Ideas

Wednesdays@NICO Seminar, Noon, February 26, 2014, Chambers Hall 

Professor James Allen Evans, University of Chicago

How Science Thinks:  Collective Cognition and the Selection of Scientific Ideas

Science can be viewed as a complex system. It is apparently complicated; shaped by strong interactions between diverse components; and displays emergent, often unexpected collective outcomes. Here, I explore how the complex network of science provides a substrate on which a scientist–-and indeed science as a whole-–thinks. Put another way: Does the structure of past research allow us to predict the future? Because experiments do not represent singular connections, our first approach models science as a dynamic hypergraph. Using millions of scientific articles from MEDLINE, we validate this approach and show how science moves from problems posed and questions answered in one year to those examined in the next. Along the way, we discover how science “changes its mind”—how science has become more risk-averse and less efficient at discovery as measured by the sources of discovery that lead to high citations and awards. We also examine how the network of scientist authors used to be a stronger path through which scientific things of all types combined and that the sources of serendipity are changing. We also uncover the special role that methods play in integrating science. Much more efficient strategies for mature fields involve more individual risk-taking than the structure of modern scientific careers supports and I show how publication of experimental failures and investment in alternative paths of discovery could substantially improve the speed of discovery. I explore the implications of these findings for machine science--the expanded use of computation from analysis to hypothesis generation and scientific imagination.

James Evans is Associate Professor of Sociology at the University of Chicago, member of the Committee on the Conceptual and Historical Studies of Science, Senior Fellow at the Computation Institute and Director of Knowledge Lab ( His work explores the sources, structure, dynamics and consequences of modern knowledge. Evans is particularly interested in the relation of markets to science and knowledge more broadly, and how evolutionary and generative models can inform our understanding of collective representations, experiences and certainty. He has studied how industry collaboration shapes the ethos, secrecy and organization of academic science; the web of individuals and institutions that produce innovations; and markets for ideas and their creators. Evans has also examined the impact of the Internet on knowledge in society.  His work uses natural language processing, the analysis of social and semantic networks, statistical modeling, and field-based observation and interviews. Evans’ research is funded by the National Science Foundation, the National Institutes of Health, the Mellon and Templeton Foundations and has been published in Science, PLOS, American Journal of Sociology, Social Studies of Science, Administrative Science Quarterly and other journals. His work has been featured in Nature, the Economist, Atlantic Monthly, Wired, NPR, BBC, El Pais, CNN and many other outlets.