  In summary, then, Bayesianism appeals to Empiricists for at least two important reasons. First, because it reinstates learning from experience as a central process in cognitive development and change. This focus on learning contrasts sharply with the first wave of Nativist cognitive research, which, inspired by Chomsky’s work in linguistics, tended to assign a diminished role to learning from experience. Experience was thought to act as a trigger/releaser of innate information, or, as in some linguistic theorizing, as setting values to parameters that were left unspecified by our innate endowment. The lead role, again following Chomsky, was assigned to growth, understood simply as biological maturation. The second reason is that the current Bayesian mindset tends in some ways towards Empiricism.  This is primarily because Bayesian learning can, at least in principle, be extended hierarchically, in the ways we’ve discussed. But Bayesianism also has some appeal to Nativists, because it focuses attention on the role of background knowledge in learning, and this is a theme that Nativists have pressed against bottom-up Associationist forms of Empiricism from the outset. Nativists can welcome a renewed focus on learning, and join in the development of Bayesian theories of cognitive development. So in the end, Bayesianism—as an approach to cognitive development—is, like Connectionism, compatible with Nativism. (For recent discussion of this last point, see Colombo 2017; for a more pessimistic assessment of the potential contribution of Bayesian approaches to psychology see Jones and Love 2011.)