  What large-scale cohesive behaviors -- desirable or dangerous -- can suddenly
emerge from systems with interacting humans, machinery and software including
AI? When will they emerge? How will they evolve and be controlled? Here we
offer some answers to these urgent questions by introducing an aggregation
model that accounts for entities' inter- and intra-species diversities. It
yields a novel multi-dimensional 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 related
real-world systems, e.g. Hamas-Hezbollah online support, human-machine team
interactions, AI-determined topic coherence. A key takeaway is that good and
bad 'surprises' will appear increasingly quickly as humans-machinery-AI etc.
mix more -- but the theory offers a rigorous approach for understanding and
controlling this.
