On the Coevolution of Theory and Language and the Nature of Successful Inquiry

Insofar as empirical inquiry involves the coevolution of descriptive language and theoretical commitments, a satisfactory model of empirical knowledge should describe the coordinated evolution of both language and theory. But since we do not know what conceptual resources we might need to express our future theories or to provide our best future faithful descriptions of the world, we do not now know even what the space of future descriptive options might be. One strategy for addressing this shifting-resource problem is to track the predictive and linguistic dispositions of inquirers rather than their theories and conceptual resources. Sender-predictor games, a variant of Skyrms-Lewis sender-receiver games, provide very simple models for the coordinated coevolution of predictive and linguistic dispositions. Such models explain how it is possible for (1) predictive and descriptive dispositions of inquirers to coevolve, (2) term-wise incommensurable, but nevertheless descriptively faithful languages, to sequentially evolve, and (3) a sort of underdetermination to occur where inquirers might satisfy their descriptive and predictive aims by revising their linguistic dispositions, their theoretical dispositions, or both. Such models also provide an elementary characterization of what it might mean for descriptions of the world to be faithful and for empirical inquiry to be successful. In doing so they provide a relatively weak, but perfectly clear, endogenous account of epistemic norms. 1. Knowledge and the evolution of descriptive language On the standard account of propositional knowledge, an agent X knows proposition P if and only if (1) X believes P , (2) P is true, and (3) X has rational justification for believing P . In contrast, belief-revision models of knowledge seek to describe how one’s local descriptive, predictive, and explanatory commitments do and should evolve as one gains new evidence. On a Bayesian belief-revision model, for example, one fixes a descriptive language, sets prior probabilities over a fixed set of hypotheses expressed in the language, then considers how one’s coherent degrees of belief evolve as one conditions on new evidence. Date: April 23, 2012.