"This is a powerful technology that will sweep through American offices with potentially very significant geographic implications," said Mark Muro, a senior fellow at the Brookings Institution, where he studies the regional effects of technology and government policy. "We need to think about what's coming down the pike." At issue is a new and rapidly growing breed of the technology known as generative A.I., which can quickly draft business reports, write software and answer questions, often with human-level skill. Already, predictions abound that generative A.I. will displace workers in call centers, software developers and business analysts. That pattern of technology disruption has happened before.

The role of geographical proximity in facilitating inter-regional or inter-organizational collaborations has been studied thoroughly in recent years. However, the effect of geographical proximity on forming scientific collaborations at the individual level still needs to be addressed. Using publication data in the field of artificial intelligence from 2001 to 2019, in this work, the effect of geographical proximity on the likelihood of forming future scientific collaborations among researchers is studied. In addition, the interaction between geographical and network proximities is examined to see whether network proximity can substitute geographical proximity in encouraging long-distance scientific collaborations. Employing conventional and machine learning techniques, our results suggest that geographical distance impedes scientific collaboration at the individual level despite the tremendous improvements in transportation and communication technologies during recent decades. Moreover, our findings show that the effect of network proximity on the likelihood of scientific collaboration increases with geographical distance, implying that network proximity can act as a substitute for geographical proximity.