Epistemology without guidance

Epistemologists often appeal to the idea that a normative theory must provide useful, usable, guidance to argue for one normative epistemology over another. I argue that this is a mistake. Guidance considerations have no role to play in theory choice in epistemology. I show how this has implications for debates about the possibility and scope of epistemic dilemmas, the legitimacy of idealisation in Bayesian epistemology, uniqueness versus permissivism, sharp versus mushy credences, and internalism versus externalism.

Coherence & Confirmation: The Epistemic Limitations of the Impossibility Theorems

It is a widespread intuition that the coherence of independent reports provides a powerful reason to believe that the reports are true. Formal results by Huemer, M. 1997. “Probability and Coherence Justification.” Southern Journal of Philosophy 35: 463–72, Olsson, E. 2002. “What is the Problem of Coherence and Truth?” Journal of Philosophy XCIX (5): 246–72, Olsson, E. 2005. Against Coherence: Truth, Probability, and Justification. Oxford University Press., Bovens, L., and S. Hartmann. 2003. Bayesian Epistemology. Oxford University Press, prove that, under certain conditions, coherence cannot increase the probability of the target claim. These formal results, known as ‘the impossibility theorems’ have been widely discussed in the literature. They are taken to have significant epistemic upshot. In particular, they are taken to show that reports must first individually confirm the target claim before the coherence of multiple reports offers any positive confirmation. In this paper, I dispute this epistemic interpretation. The impossibility theorems are consistent with the idea that the coherence of independent reports provides a powerful reason to believe that the reports are true even if the reports do not individually confirm prior to coherence. Once we see that the formal discoveries do not have this implication, we can recover a model of coherence justification consistent with Bayesianism and these results. This paper, thus, seeks to turn the tide of the negative findings for coherence reasoning by defending coherence as a unique source of confirmation.

Philosophy’s rematch: A new conceptualization of the study of higher education

In recent decades, philosophy has been identified as a general approach to enhance the maturity of higher education as a field of study by enriching theory and method. In this article, I offer a new set of philosophical recommendations to spur the disciplinary development of higher education, departing from previous work in several meaningful ways. Due to their deep and useful connections to higher education research, philosophy of measurement, virtue epistemology, and Bayesian epistemology are introduced and discussed in relation to their conceptual association and potential practical influence on the study of higher education. The culmination of these points signals a learnercentered lens focused on the development of students.

Bayesian Epistemology

Everyone agrees that it is good to know. We however believe many more things than we know, which has made the notion of belief a target of recent work in epistemology. Not only do we believe propositions, we also believe them to different degrees. That beliefs come in degrees is often taken as a psychological fact and as a normative principle of rationality. The most prominent normative approach to beliefs which come in degrees is Bayesian epistemology. Bayesian degrees of belief are postulated to be represented by numbers in the unit interval [0, 1] obeying the axioms of probability. The convention is that a greater number expresses a stronger belief. The second postulate of Bayesian epistemology governs the change of beliefs whenever new evidence becomes available via updating procedures, Bayesian updating for categorical evidence and the more general Jeffrey updating for uncertain evidence.

What is conditionalization, and why should we do it?

Conditionalization is one of the central norms of Bayesian epistemology. But there are a number of competing formulations, and a number of arguments that purport to establish it. In this paper, I explore which formulations of the norm are supported by which arguments. In their standard formulations, each of the arguments I consider here depends on the same assumption, which I call Deterministic Updating. I will investigate whether it is possible to amend these arguments so that they no longer depend on it. As I show, whether this is possible depends on the formulation of the norm under consideration.

Learning from Conditionals

In this article, we address a major outstanding question of probabilistic Bayesian epistemology: how should a rational Bayesian agent update their beliefs upon learning an indicative conditional? A number of authors have recently contended that this question is fundamentally underdetermined by Bayesian norms, and hence that there is no single update procedure that rational agents are obliged to follow upon learning an indicative conditional. Here we resist this trend and argue that a core set of widely accepted Bayesian norms is sufficient to identify a normatively privileged updating procedure for this kind of learning. Along the way, we justify a privileged formalization of the notion of ‘epistemic conservativity’, offer a new analysis of the Judy Benjamin problem, and emphasize the distinction between interpreting the content of new evidence and updating one’s beliefs on the basis of that content.