2024/09/13 by Natalia Vélez, Charley M. Wu, Samuel J. Gershman +1 · 1 voice · 5 citations
Engineering · Social Sciences · #Artificial intelligence #Business #Computer science #Economic geography #Geography #ICT Impact and Policies #Knowledge Management and Sharing #Technological change
paper · doi:10.31234/osf.io/tz4dn
openalex publication_date 2024/09/13 · openalex created_date 2024/09/14 · openalex updated_date 2026/07/14
Humans have developed technologies to adapt to virtually every habitat on Earth. But why do some communities develop thriving technological repertoires while others stagnate? We address this question by analyzing player behavior in One Hour One Life (OHOL), a multiplayer online game where players can build technologically advanced communities from scratch (N = 22,011 players, 2,700 communities, 428,255 playthroughs). Players are randomly assigned to a community in each playthrough and can contribute to it for up to one hour. Over time, through many players' contributions, communities can survive for weeks and amass rich technological repertoires. Thus, this dataset provides a unique quasi-experiment into how the composition of communities affects their growth and decline. Using this approach, we find that technological developments are the product of interactions between individuals and the communities where they are placed. Individuals take on jobs that align with those of their closest peers, and they selectively contribute new technologies in areas of their expertise that diverge from the rest of the community. In the aggregate, these two processes—aligning to form specialized communities, or diverging to form diverse ones—have opposing effects on the size and stability of a community's technological repertoire, and imbalances in specialization serve as an early indicator of population collapse. Our results suggest that, to survive, communities must balance between diversifying to develop new technologies, while specializing to maintain the ones they already have. Our approach provides a testbed for theories of large-scale social phenomena that would otherwise be difficult to test against real-world data or traditional laboratory experiments.