Abstract
Objective standards for justification or for being a reason would be desirable, but inductive skepticism tells us that they cannot be presupposed. Rather, we have to start from subjective-relative notions of justification and of being a reason. The paper lays out the strategic options we have given this dilemma. The paper explains the requirements for this subject-relative notion and how they may be satisfied. Then it discusses four quite heterogeneous ways of providing more objective standards, which combine without guaranteeing complete success.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
Here I use “inductive” in the widest possible sense of “non-deductive”. There is a widespread prejudice that inductive reasoning is nothing but deductive reasoning with implicit premises. This prejudice is deeply amiss.
Freitag (2015) gives an entertaining and convincing analysis of a crucial aspect that goes wrong in Goodman’s riddle.
My own attempts are contained in Spohn (2012), at least in chapters 5, 6, 12, 15, and 17.
For instance, one may also have moral reasons for having a certain belief (if one manages thereby to acquire or maintain that belief). The distinction between epistemic and other reasons to believe is an interesting side issue. Cf., e.g., BonJour (1985, sect. 1.2).
Note that we can give a similar account of what it means that A is a reason against B or may speak against B. This has equally many ways of linguistic expression.
Horty (2012) is the most elaborate attempt to provide a theory of reasons in terms of default logic. It does not point out, though, any way how to conform to Definition 1. Of course, one might start with defaults and construct from them a suitable credibility function, as first proposed by Pearl (1990). However, this is not Horty’s way, since he wants to provide an alternative to what he calls the weighing and the force conception of reasons, both of which he finds too metaphorical (pp. 2ff.).
The AGM way of specifying conditional degrees of belief would consist in specifying a posterior entrenchment order after a first belief change, which would govern then a second (iterated) change. See, however, the many possibilities of specifying such a posterior order in Rott (2009), none of which seems generally adequate.
This is the main reason why traditional epistemologists are reserved or even hostile towards Bayesian epistemology.
There is a rich discussion trying to get around this devastating conclusion. Understandably so. On the one hand, there is little sympathy with Jeffrey’s radical probabilism (1992, ch. 1) simply dispensing with the notion of belief; on the other hand, one very much wants to preserve the unity of our epistemological accounts. In my view, however, this discussion is a complete failure (as explained in some detail in Spohn 2012, sect. 10.1). Let’s not enter it. The most sophisticated recent attempt of Leitgeb (2014) leads to an extremely partition-relative notion of belief. He defends this consequence; I find it unacceptable.
Note that \(\upkappa (A \cup B)\) = min {\(\upkappa (A)\), \(\upkappa (B)\)} translates into \(\upbeta (A \cap B)\) = min {\(\upbeta (A)\), \(\upkappa (B)\)}.
In the lottery paradox we may have \(\tau (W) > z\), i.e., a belief in the proposition Wthat exactly one ticket wins, and the same attitude \(\tau (L _{i})\) = 0, i.e., suspense of judgment, for all propositions \(L _{i}\) that ticket i loses. This is not an exciting solution, but it clearly is a consistent belief state, and this is all that matters.
This definition is the crucial progress of ranking theory over its predecessors such as the functions of potential surprise of Shackle (1961) or Baconian probability as conceived by Cohen (1977) and even over parallel developments such as possibility theory presented in Dubois, Prade (1988), which is formally equivalent to ranking theory, but gives no clear intuitive guidance for defining conditional degrees of possibility; this may be done in a way equivalent to Definition 3 or in some other way as well.
Just replace min in (b) by + and addition and subtraction of ranks, respectively, by multiplication and division, and you get the basic laws of probability.
There is formal literature that tries to explicate the degree of coherence one proposition has with others; cf., e.g., Shogenji (1999) and Olsson (2012). However, it remains unclear there what this has to do with reasons and justifiedness. Moreover, I am obviously neglecting the third option of accepting an infinite regress of justification.
Proof: \(\upbeta (B) > z\) entails that both \(\upkappa (A \cap {\sim }B) > z \) and \(\upkappa ({\sim }A \cap {\sim }B) > z\). \(\tau (B {\vert } {\sim }A) = 0\) entails \(\upkappa ({\sim }B {\vert } {\sim }A) = 0\) and hence \(\upkappa ({\sim }A \cap {\sim }B)=\upkappa ({\sim }A)\). Therefore \(\upkappa ({\sim }A)=\upbeta (A) > z.\)
This theorem has no probabilistic counterpart, at least if one identifies justifiedness of a proposition A with its probability P(A) being above some threshold x. Even if A is a sufficient reason for B in the sense of \(P(B {\vert } A) = 1 > P(B {\vert } {\sim }A)\), \(P(B) > x \) does not entail \(P(A) > x\).
I have addressed this issue more extensively in Spohn (2012, ch. 16), where I find only little fault with traditional foundationalism with respect to perception, i.e., just as much fault as to satisfy its opponents.
The distinction is not always drawn in the same way. For instance, Friedman (1999) identifies a constitutive, relativized a priori diverging from the traditional Kantian a priori, whereas Field (1996) distinguishes a weak and a strong form of apriority. I have explained my two notions more carefully in Spohn (2012, sect. 6.5 and 17.1).
This explains the difficulty of characterizing “initial” in the explication of defeasible apriority. Given literally no experience whatsoever, we cannot form any concepts or any doxastic state at all. Hence, initiality must be understood in a relative sense: after sufficient experience to develop the relevant concepts, but before any experience applying these concepts to a new case to be judged.
Cf. Spohn (2012, sect. 13.3–4).
Literally, Kripke’s contingent a priori also counts as synthetic a priori. But since it is still purely conceptual it thoroughly misses Kant’s intentions.
The only exception I know of is my own in terms of ranking theory; cf. Spohn (2012, ch. 17).
This was first proved by Savage (1954, p. 114).
Shafer (1976, p. 78) mentions that “evidence of infinite weight produces ... certainty”.
For a criticism see Lukits (2014).
As more fully explained in Spohn (2016a).
J. Williamson’s (2005) objective Bayesianism is a strong effort to reestablish objective inductive probabilities. T. Williamson (2000, ch. 10) intends to relaunch them as well as what he calls evidential probabilities. He has interesting things to say about the form in which they process evidence. However, unlike Carnap and J. Williamson, he makes no efforts to say anything about their a priori shape. Thus, he just postulates them. I cannot find that this procedure makes his posits credible.
References
Besnard, P., & Hunter, A. (2008). Elements of argumentation. Cambridge, MA: MIT Press.
Betz, G. (2010). Theorie dialektischer Strukturen. Frankfurt a.M: Klostermann.
Bittner, R. (2001). Doing things for reasons. Oxford: Oxford University Press.
Blackburn, S. (1990). Hume and thick connexions. Philosophy and Phenomenological Research, 50 (Supplement), 237–250.
BonJour, L. (1985). The structure of empirical knowledge. Cambridge, MA: Harvard University Press.
Carnap, R. (1950). The logical foundations of probability. Chicago: Chicago University Press.
Carnap, R. (1952). The continuum of inductive methods. Chicago: University of Chicago Press.
Carnap, R. (1956). The methodological character of theoretical concepts. In H. Feigl & M. Scriven (Eds.), Minnesota studies in the philosophy of science (Vol. I, pp. 38–76). Minneapolis: University of Minnesota Press.
Carnap, R., & Jeffrey, R. C. (Eds.). (1971). Studies in inductive logic and probability (Vol. I). Berkeley: University of California Press.
Cohen, L. J. (1977). The probable and the provable. Oxford: Oxford University Press.
Dancy, J. (2000). Practical reality. Oxford: Oxford University Press.
de Finetti, B. (1937). La Prévision: Ses Lois Logiques, Ses Sources Subjectives. Annales de l’Institut Henri Poincaré 7, 1–68. Engl. translation: Foresight: Its logical laws, its subjective sources. In: H. E. Kyburg Jr, & H. E. Smokler (Eds.) (1964) Studies in subjective probability. New York: Wiley, pp. 93–158.
Dubois, D., & Prade, H. (1988). Possibility theory: An approach to computerized processing of uncertainty. New York: Plenum Press.
Field, H. (1996). The A prioricity of logic. Proceedings of the Aristotelian Society, 96, 359–379.
Freitag, W. (2015). I bet you’ll solve Goodman’s Riddle. Philosophical Quarterly, 65, 254–267.
Friedman, M. (1999). Dynamics of reason. Stanford: CSLI Publications.
Greaves, H., & Wallace, D. (2006). Justifying conditionalization: Conditionalization maximizes expected epistemic utility. Mind, 115, 607–632.
Hempel, C. G., & Oppenheim, P. (1948). Studies in the logic of explanation. Philosophy of Science, 15, 135–175.
Hempel, C. G. (1965). Aspects of scientific explanation and other essays in the philosophy of science. New York: Free Press.
Horty, J. F. (2012). Reasons as defaults. Oxford: Oxford University Press.
Huber, F. (2013). Belief revision II: Ranking theory. Philosophical Compass, 8, 613–621.
Huber, F. (2014). New foundations for counterfactuals. Synthese, 191, 2167–2193.
Halpern, J. Y. (2003). Reasoning about uncertainty. Cambridge, MA: MIT Press.
Jeffrey, R. C. (1992). Probability and the art of judgment. Cambridge: Cambridge University Press.
Joyce, J. (1998). A nonpragmatic vindication of probabilism. Philosophy of Science, 65, 575–603.
Kelly, K. (1996). The logic of reliable inquiry. Oxford: Oxford University Press.
Kelly, K. (1999). Iterated belief revision, reliability, and inductive amnesia. Erkenntnis, 50, 11–58.
Leitgeb, H. (2004). Inference on the low level. An investigation into deduction, nonmonotonic reasoning, and the philosophy of cognition. Dordrecht: Kluwer.
Leitgeb, H. (2014). The stability theory of belief. Philosophical Review, 123, 131–171.
Leitgeb, H., & Pettigrew, R. (2010). An objective justification of Bayesianism II: The consequences of minimizing accuracy. Philosophy of Science, 77, 26–272.
Lewis, D. K. (1973). Counterfactuals. Oxford: Blackwell.
Lewis, D. K. (1980). A subjectivist’s guide to objective chance. In: R. C. Jeffrey (ed.), Studies in inductive logic and probability (Vol. II, pp. 263–293). University of California Press. (also in D. K. Lewis (1986). Philosophical papers (Vol. II, pp. 83–113, supplemented by postscripts). Oxford: Oxford University Press).
Lukits, S. (2014). The principle of maximum entropy and a problem in probability kinematics. Synthese, 191, 1409–1431.
Oddie, G. (2014). Truthlikeness. In: E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy. http://plato.stanford.edu/entries/truthlikeness/.
Olsson, E. J. (2012). Coherentist theories of epistemic justification. In: E. N. Zalta (Ed.), The Stanford encyclopedia of philosophy. https://plato.stanford.edu/entries/justep-coherence/.
Pearl, J. (1988). Probabilistic reasoning in intelligent systems: Networks of plausible inference. San Mateo, CA: Morgan Kaufmann.
Pearl, J. (1990). System Z: A natural ordering of defaults with tractable applications to default reasoning. In R. Parikh (Ed.), Proceedings TARK-90 (pp. 121–135). San Mateo, CA: Morgan Kaufmann.
Pettigrew, R. (2016). Accuracy and the laws of credence. Oxford: Oxford University Press.
Pollock, J. L. (1990). Nomic probability and the foundations of induction. Oxford: Oxford University Press.
Pollock, J. L. (1995). Cognitive carpentry: A blueprint for how to build a person. Cambridge, MA: MIT Press.
Rosenkrantz, R. D. (1992). The justification of induction. Philosophy of Science, 59, 527–539.
Rott, H. (2009). Shifting priorities: Simple representations for twenty seven iterated theory change operators. In D. Makinson, J. Malinowski, & H. Wansing (Eds.), Towards mathematical philosophy (pp. 269–296). Dordrecht: Springer.
Savage, L. J. (1954). The foundations of statistics. New York: Wiley.
Shackle, G. L. S. (1961). Decision, order, and time in human affairs (2nd ed.). Cambridge: Cambridge University Press.
Shafer, G. (1976). A mathematical theory of evidence. Princeton: Princeton University Press.
Shogenji, T. (1999). Is coherence truth-conducive? Analysis, 59, 338–345.
Spohn, W. (2001). Vier Begründungsbegriffe. In T. Grundmann (Ed.), Erkenntnistheorie. Positionen zwischen Tradition und Gegenwart (pp. 33–52). Mentis, Paderborn.
Spohn, W. (2009). A survey of ranking theory. In F. Huber & C. Schmidt-Petri (Eds.), Degrees of belief. An anthology (pp. 185–228). Dordrecht: Springer.
Spohn, W. (2010). Chance and necessity: From humean supervenience to humean projection. In E. Eells & J. Fetzer (Eds.), The place of probability in science (pp. 101–131). Dordrecht: Springer.
Spohn, W. (2012). The laws of belief. Ranking theory and its philosophical applications. Oxford: Oxford University Press.
Spohn, W. (2016a). Three kinds of worlds and two kinds of truth. Philosophical Studies, 173(5), 1335–1359.
Spohn, W. (2016b). Enumerative induction. In C. Beyer, G. Brewka, & M. Timm (Eds.), Foundations of formal rationality: Essays dedicated to Gabriele Kern-Isberner on the occasion of her 60th birthday (pp. 96–114). London: College Publications.
Spohn, W. (2017). How the modalities come into the world. Erkenntnis, 82. doi:10.1007/s10670-016-9874-y.
Walley, P. (1991). Statistical reasoning with imprecise probabilities. London: Chapman & Hall.
Williamson, J. (2005). Bayesian nets and causality. Philosophical and computational foundations. Oxford: Oxford University Press.
Williamson, T. (2000). Knowledge and its limits. Oxford: Oxford University Press.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Spohn, W. Epistemic justification: its subjective and its objective ways. Synthese 195, 3837–3856 (2018). https://doi.org/10.1007/s11229-017-1393-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11229-017-1393-0