Predictive algorithms serving users can lead to varying prediction quality.
Users' responses to accurate predictions can create feedback loops affecting the model and user population.
Evolutionary prediction games framework introduced for modeling feedback loops using evolutionary game theory.
Analysis shows competition and competitive exclusion in ideal settings with unlimited resources, while coexistence is possible in realistic constraints.
Stable coexistence and mutualistic symbiosis between user groups feasible under constraints like finite data and limited compute.
Mechanisms to sustain coexistence presented and empirical evidence provided to support the findings.