Multispecies Cohesion: Humans, Machinery, AI, and Beyond

The global chaos caused by the July 19, 2024 technology meltdown highlights the need for a theory of what large-scale cohesive behaviors-dangerous or desirable-could suddenly emerge from future systems of interacting humans, machinery, and software, including artificial intelligence; when they will emerge; and how they will evolve and be controlled. Here, we offer answers by introducing an aggregation model that accounts for the interacting entities' inter- and intraspecies diversities. It yields a novel multidimensional generalization of existing aggregation physics. We derive exact analytic solutions for the time to cohesion and growth of cohesion for two species, and some generalizations for an arbitrary number of species. These solutions reproduce-and offer a microscopic explanation for-an anomalous nonlinear growth feature observed in various current real-world systems. Our theory suggests good and bad "surprises" will appear sooner and more strongly as humans, machinery, artificial intelligence, and so on interact more, but it also offers a rigorous approach for understanding and controlling this.

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Publication Details

Journal
Physical Review Letters
Published
2024-12-10
DOI
https://doi.org/10.1103/physrevlett.133.247401
Citations
12
Primary Topic
Evolutionary Game Theory and Cooperation
Type
article
Field-Weighted Citation Impact
13.58

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article

Multispecies Cohesion: Humans, Machinery, AI, and Beyond

Frank Yingjie Huo, Neil F. Johnson, Pedro D. Manrique
12 citations
Physical Review Letters
Evolutionary Game Theory and Cooperation
13.58
article

Multispecies Cohesion: Humans, Machinery, AI, and Beyond

Frank Yingjie Huo, Neil F. Johnson, Pedro D. Manrique
article en
12 citations

Abstract

The global chaos caused by the July 19, 2024 technology meltdown highlights the need for a theory of what large-scale cohesive behaviors-dangerous or desirable-could suddenly emerge from future systems of interacting humans, machinery, and software, including artificial intelligence; when they will emerge; and how they will evolve and be controlled. Here, we offer answers by introducing an aggregation model that accounts for the interacting entities' inter- and intraspecies diversities. It yields a novel multidimensional generalization of existing aggregation physics. We derive exact analytic solutions for the time to cohesion and growth of cohesion for two species, and some generalizations for an arbitrary number of species. These solutions reproduce-and offer a microscopic explanation for-an anomalous nonlinear growth feature observed in various current real-world systems. Our theory suggests good and bad "surprises" will appear sooner and more strongly as humans, machinery, artificial intelligence, and so on interact more, but it also offers a rigorous approach for understanding and controlling this.

Physical Review LettersVol. 133(24)
George Washington University (US)
John Templeton Foundation, Air Force Office of Scientific Research
Openalex Percentile: Top 1%
Evolutionary Game Theory and Cooperation
13.58
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