A wide variety of cultural practices have a 'tacit' dimension, whose principles are neither obvious to an observer, nor known explicitly by experts. This poses a problem for cultural evolution: if beginners cannot spot the principles to imitate, and experts cannot say what they are doing, how can tacit knowledge pass from generation to generation? We present a domain-general model of 'tacit teaching', drawn from statistical physics, that shows how high-accuracy transmission of tacit knowledge is possible. It applies when the practice's underlying features are subject to interacting and competing constraints. Our model makes predictions for key features of the teaching process. It predicts a tell-tale distribution of teaching outcomes, with some students near-perfect performers while others receiving the same instruction are disastrously bad. This differs from standard cultural evolution models that rely on direct, high-fidelity copying, which lead to a much narrower distribution of mostly mediocre outcomes. The model also predicts generic features of the cultural evolution of tacit knowledge. The evolution of tacit knowledge is expected to be bursty, with long periods of stability interspersed with brief periods of dramatic change, and where tacit knowledge, once lost, becomes essentially impossible to recover.
Keywords: cultural evolution; cultural transmission; learning; tacit knowledge; teaching.