Innovation is often predicated on discovering useful new combinations of existing knowledge in highly complex knowledge spaces. These needle-in-a-haystack type problems are pervasive in fields like genomics, drug discovery, materials science, and particle physics. We develop a...

The recruitment of foreign scientists enhances US science through an expanded workforce but could also cause harm by displacing better connected domestic scientists, thereby reducing localized knowledge spillovers. We develop a model in which a sufficient condition for the absence of overall...

We report a puzzling pair of facts concerning the organization of science. The concentration of research output is declining at the department level but increasing at the individual level. For example, in evolutionary biology, over the period 1980 to 2000, the fraction of citation-weighted...

We model a key step in the innovation process, hypothesis generation, as the making of predictions over a vast combinatorial space. Traditionally, scientists and innovators use theory or intuition to guide their search. Increasingly, however, they use artificial intelligence (AI) instead. We...