Monoculture or Multiplicity: Which Is It?

Two narratives about machine learning ecosystems grew out of recent algorithmic fairness discourse. In one, dubbed \emph{monoculture}, algorithmic ecosystems tend toward homogeneity akin to a single model making all decisions. Individuals then face the risk of systematic exclusion with no recourse. In the other, \emph{model multiplicity}, many models solve the same task with similar accuracy, causing excessive variation in outcomes. Both narratives are compelling, yet, seemingly at odds: model multiplicity can't exist in a strict monoculture.