The Gulf between Practical and Theoretical Reason

Southern Journal of Philosophy, 1993

Economics and Philosophy, 2015

One kind of deliberation involves an individual reassessing the strengths of her beliefs in the light of new evidence. Bayesian epistemology measures the strength to which one ought to believe a proposition by its probability relative to all available evidence, and thus provides a normative account of individual deliberation. This can be extended to an account of individual judgement by treating the act of judgement as a decision problem, amenable to the tools of decision theory. A normative account of public deliberation and judgement can be provided by merging the evidence of the individuals in question and calculating appropriate Bayesian probabilities and judgement thresholds relative to this merged evidence. But this formal epistemology for deliberation and judgement lacks substance without an account of how evidence can be merged. And in order to provide such an account, we need in turn an account of what the evidence is that grounds Bayesian probabilities. This paper attempts to tackle these two concerns. After finding fault with several views on the nature of evidence (the views that evidence is knowledge; that evidence is whatever is fully believed; that evidence is observationally set credence; that evidence is information), it is argued that evidence is whatever is rationally taken for granted. This view has consequences for an account of merging, and it is shown that standard axioms for merging need to be altered somewhat. §1 Deliberation and Judgement Bayesianism provides a natural account of certain questions to do with judgement and doxastic deliberation: Individual Deliberation. How strongly should I believe θ? Individual Judgement. Should I judge θ as true? Public Deliberation. How strongly should we believe θ? Public Judgement. Should we judge θ as true? Let us consider these questions in turn. 1 There is no need to assume a common prior probability function or common knowledge here (Aumann, 1976), merely a common interest.

The British Journal for the Philosophy of Science, 2021

When a proposition is established, it can be taken as evidence for other propositions. Can the Bayesian theory of rational belief and action provide an account of establishing? I argue that it can, but only if the Bayesian is willing to endorse objective constraints on both probabilities and utilities, and willing to deny that it is rationally permissible to defer wholesale to expert opinion. I develop a new account of deference that accommodates this latter requirement.

When is a person justified in believing a proposition? In this paper, I defend a view according to which a person is justified in believing a proposition just in case the person’s evidence sufficiently supports the proposition and the person responsibly acquired and sustained the evidence that supports the proposition. This view overcomes a deficiency in a prominent theory of epistemic justification. As championed by Earl Conee and Richard Feldman, Evidentialism is a theory subject to counterexamples at the hands of cases involving epistemic irresponsibility. I critically discuss such a case as put forward by Jason Baehr. After providing an argument that clarifies why the case is problematic for Evidentialism, I defend my argument from a response by Earl Conee. Then I develop a theory of epistemic justification capable of handling cases involving epistemic irresponsibility, and I defend this theory from evidentialist objections.

Nous, 2001

Synthese (SYNT)

To say that evidence is normative is to say that what evidence one possesses, and how this evidence relates to any proposition, determines which attitude among believing, disbe-lieving and withholding one ought to take toward this proposition if one deliberates about whether to believe it. It has been suggested by McHugh that this view can be vindicated by resting on the premise that truth is epistemically valuable. In this paper, I modify the strategy sketched by McHugh so as to overcome the initial difficulty that it is unable to vindicate the claim that on counterbalanced evidence with respect to P one ought to conclude deliberation by withholding on P. However, I describe the more serious difficulty that this strategy rests on principles whose acceptance commits one to acknowledging non-evidential reasons for believing. A way to overcome this second difficulty, against the evidentialists who deny this, is to show that we sometimes manage to believe on the basis of non-epis-temic considerations. If this is so, one fundamental motivation behind the evidentialist idea that non-epistemic considerations could not enter as reasons in deliberation would lose its force. In the second part of this paper I address several strategies proposed in the attempt to show that we sometimes manage to believe on the basis of non-epistemic considerations and show that they all fail. So, I conclude that the strategy inspired by McHugh to ground the normativity of evidence of the value of truth ultimately fails.

Reason to Dissent. Proceedings of the 3rd European Conference on Argumentation [Groningen 2019]. Vol. 1., 2020

In times of populist mistrust towards experts, it is important and the aim of the paper to ascertain the rationality of arguments from expert opinion and to reconstruct their rational foundations as well as to determine their limits. The foundational approach chosen is probabilistic. However, there are at least three correct probabilistic reconstructions of such argumentations: statistical inferences, Bayesian updating, and interpretive arguments. To solve this competition problem, the paper proposes a recourse to the arguments' justification strengths achievable in the respective situation.

Argumentation

The study of presumptions has intensified in argumentation theory over the last years. Although scholars put forward different accounts, they mostly agree that presumptions can be studied in deliberative and epistemic contexts, have distinct contextual functions (guiding decisions vs. acquiring information), and promote different kinds of goals (non-epistemic vs. epistemic). Accordingly, there are "practical" and "cognitive" presumptions. In this paper, I show that the differences between practical and cognitive presumptions go far beyond contextual considerations. The central aim is to explore Nicholas Rescher's contention that both types of presumptions have a closely analogous pragmatic function, i.e., that practical and cognitive presumptions are made to avoid greater harm in circumstances of epistemic uncertainty. By comparing schemes of practical and cognitive reasoning, I show that Rescher's contention requires qualifications. Moreover, not only do practical and cognitive presumptions have distinct pragmatic functions, but they also perform different dialogical functions (enabling progress vs. preventing regress) and, in some circumstances, cannot be defeated by the same kinds of evidence. Hence, I conclude that the two classes of presumptions merit distinct treatment in argumentation theory.

Philosophical Foundations of Evidence Law, 2021

While the laws of probability are rarely disputed, the question of how we should interpret probability judgments is less straightforward. Broadly, there are two ways to conceive of probability—either as an objective feature of the world, or as a subjective measure of our uncertainty. Both notions have their place in science, but it is the latter subjective notion (the Bayesian approach) that is crucial in legal reasoning. This chapter explains the advantages of using Bayesian networks in adjudicative factfinding. It addresses a number of common objections to the Bayesian approach, such as “There is no such thing as a probability of a single specified event”; “The Bayesian approach only works with statistical evidence”; “The Bayesian approach is too difficult for legal factfinders to comprehend”; and “A Bayesian network can never capture the full complexity of a legal case.” Fenton and Lagnado offer rebuttals to each of these objections.