Language Scaffolding as a Condition for Growth in Linguistic Complexity

Over their evolutionary history, languages most likely increased in complexity from simple signals to protolanguages to complex syntactic structures. This paper investigates processes for increasing linguistic complexity while maintaining communicability across a population. We assume that higher linguistic communicability (more accurate information exchange) increases participants’ effectiveness in coordination-based tasks. Interaction, needed for learning others’ languages and for converging to communicability, bears a cost. There is a threshold of interaction (learning) effort beyond which (the coordination payoff of) linguistic convergence either doesn’t pay or is pragmatically impossible. Our central findings, established mainly through simulation, are: 1) There is an effort-dependent “frontier of tractability” for agreement on a language that balances linguistic complexity against linguistic diversity in a population. To remain below some specific bound on collective convergence effort, either a) languages must be simpler, or b) their initial average communicability must be higher. To stay below such a pragmatic effort limit, even agents who have the ultimate capability for complex languages must not invent them from the start or they won’t be able to communicate; they must start simple and grow complexity in a staged process. 2) Such a staged approach to increasing complexity, in which agents initially converge on simple languages and then use these to “scaffold” greater complexity, can outperform initially-complex languages in terms of overall effort to convergence. This performance gain improves with more complex final languages.