Abstract
AbstractThe account of meta-induction (G. Schurz, Hume’s problem solved: the optimality of meta-induction, MIT Press, Cambridge, 2019) proposes a two-step solution to the problem of induction. Step 1 consists in a mathematical a priori justification of the predictive optimality of meta-induction, upon which step 2 builds a meta-inductive a posteriori justification of object-induction based on its superior track record (Sect. 1). Sterkenburg (Br J Philos Sci, forthcoming. 10.1086/717068/) challenged this account by arguing that meta-induction can only provide a (non-circular) justification of inductive predictions for now and for the next future, but not a justification of inductive generalizations (Sect. 2). This paper develops a meta-inductive method that does provide an a posteriori justification of inductive generalizations, in the form of exchangeability conditions (Sect. 3). In Sect. 4, a limitation of the proposed method is worked out: while the method can justify weakly lawlike generalizations, the justification of strongly lawlike generalizations (claimed to hold for all eternity) requires epistemic principles going beyond meta-induction based on predictive success.
Funder
Heinrich-Heine-Universität Düsseldorf
Publisher
Springer Science and Business Media LLC
Reference30 articles.
1. Armstrong, D. M. (1983). What is a law of nature? Cambridge University Press.
2. Carnap, R. (1950). Logical foundations of probability. University of Chicago Press.
3. Cesa-Bianchi, N., & Lugosi, G. (2006). Prediction, learning, and games. Cambridge University Press.
4. De Finetti, B. (1937/64). Foresight, its logical laws, its subjective sources. In H. Kyburg & H. Smokler (eds.), Studies in subjective probability (pp. 93–159). John Wiley 1964.
5. Diaconis, P., & Friedman, D. (1980). De Finetti’s theorem for Markov chains. The Annals of Probability, 8, 115–130.