A previously unrecognised argument against deterministic chance is introduced. The argument rests on the twin ideas that determined outcomes are settled, while chancy outcomes are unsettled, thus making cases of determined but chancy outcomes impossible. Closer attention to tacit assumptions about settledness makes available some principled lines of resistance to the argument for compatibilists about chance and determinism. Yet the costs of maintaining compatibilism may be higher with respect to this argument than with respect to existing incompatibilist arguments.

It has been argued recently that dogmatism in epistemology is incompatible with Bayesianism. That is, it has been argued that dogmatism cannot be modelled using traditional techniques for Bayesian modelling. I argue that our response to this should not be to throw out dogmatism, but to develop better modelling techniques. I sketch a model for formal learning in which an agent can discover a posteriori fundamental epistemic connections. In this model, there is no formal objection to dogmatism.

Although it has often been claimed that all the information contained in second‐order probabilities can be contained in first‐order probabilities, no practical recipe for the elimination of second‐order probabilities without loss of information seems to have been presented. Here, such an elimination method is introduced for repeatable events. However, its application comes at the price of losses in cognitive realism. In spite of their technical eliminability, second‐order probabilities are useful because they can provide models of important features of the world (...) that are cognitively more plausible than those that can be obtained with single‐level probabilities. (shrink)

Traditional Bayesianism requires that an agent’s degrees of belief be represented by a real-valued, probabilistic credence function. However, in many cases it seems that our evidence is not rich enough to warrant such precision. In light of this, some have proposed that we instead represent an agent’s degrees of belief as a set of credence functions. This way, we can respect the evidence by requiring that the set, often called the agent’s credal state, includes all credence functions that are in (...) some sense compatible with the evidence. One known problem for this evidentially motivated imprecise view is that in certain cases, our imprecise credence in a particular proposition will remain the same no matter how much evidence we receive. In this article I argue that the problem is much more general than has been appreciated so far, and that it’s difficult to avoid it without compromising the initial evidentialist motivation. _1_ Introduction _2_ Precision and Its Problems _3_ Imprecise Bayesianism and Respecting Ambiguous Evidence _4_ Local Belief Inertia _5_ From Local to Global Belief Inertia _6_ Responding to Global Belief Inertia _7_ Conclusion. (shrink)

This chapter contains sections titled: Highlights of Past Literature Current Work Future Work.

Bayesian reasoning has been applied formally to statistical inference, machine learning and analysing scientific method. Here I apply it informally to more common forms of inference, namely natural language arguments. I analyse a variety of traditional fallacies, deductive, inductive and causal, and find more merit in them than is generally acknowledged. Bayesian principles provide a framework for understanding ordinary arguments which is well worth developing.

Bayesians since Savage (1972) have appealed to asymptotic results to counter charges of excessive subjectivity. Their claim is that objectionable differences in prior probability judgments will vanish as agents learn from evidence, and individual agents will converge to the truth. Glymour (1980), Earman (1992) and others have voiced the complaint that the theorems used to support these claims tell us, not how probabilities updated on evidence will actually}behave in the limit, but merely how Bayesian agents believe they will behave, suggesting (...) that the theorems are too weak to underwrite notions of scientific objectivity and intersubjective agreement. I investigate, in a very general framework, the conditions under which updated probabilities actually converge to a settled opinion and the conditions under which the updated probabilities of two agents actually converge to the same settled opinion. I call this mode of convergence deterministic, and derive results that extend those found in Huttegger (2015b). The results here lead to a simple characterization of deterministic convergence for Bayesian learners and give rise to an interesting argument for what I call strong regularity, the view that probabilities of non-empty events should be bounded away from zero. (shrink)

There are two ways of representing rational belief: qualitatively as yes-or-no belief, and quantitatively as degrees of belief. Standard rationality conditions are: consistency and logical closure, for qualitative belief, satisfaction of the probability axioms, for quantitative belief, and a relationship between qualitative and quantitative beliefs in accordance with the Lockean thesis. In this paper, it is shown that these conditions are inconsistent with each of three further rationality conditions: fallibilism, open-mindedness, and invariance under independent conceptual expansions. Restrictions of the Lockean (...) thesis that have been suggested in the literature cannot remove the inconsistency. In the outlook we discuss two alternative ways of dealing with this problem: restricting conjunctive closure or going for a dual system account. (shrink)

The knowledge norm of assertion is mainly in competition with a high probability or rational credibility norm. The argument for the knowledge norm that I offer turns on cases in which a hearer responds to a speaker's assertion by asserting another sentence that would lower the probability of the speaker's assertion, were its probability less than one. In cases like this, though with qualifications, is the hearer's contribution a challenge to the speaker's assertion or complementary to it? My answer is (...) the latter, and that only the knowledge norm yields that answer.The cases that I rely on follow from an elementary probability relation, though one that is inconsistent with the still influential relevance criterion for confirmation and evidence . Assume, for illustrative purposes, that p is in your belief corpus, as a consequence of your believing ∨ ∨ . 1 You learn that ∼ & ∼ , which would lessen the probability of p, were its probability less than one, 2 since it eliminates two rows of the truth-table in which p holds. What conclusion do you reach about p?Rather than withdrawing p, you acquire the belief that p & ∼ s & ∼ r, even though Formula where pr would be the subjective or epistemic probability of p on a probabilistic view of the knowledge norm before learning ∼ & ∼ . Instead of withdrawal …. (shrink)

Scientific inquiry is represented as a process of rational hypothesis revision in the face of data. For the concept of rationality, we rely on the theory of belief dynamics as developed in [5, 9]. Among other things, it is shown that if belief states are left unclosed under deductive logic then scientific theories can be expanded in a uniform, consistent fashion that allows inquiry to proceed by any method of hypothesis revision based on "kernel" contraction. In contrast, if belief states (...) are closed under logic, then no such expansion is possible. (shrink)

There is currently much discussion about how decision making should proceed when an agent's degrees of belief are imprecise; represented by a set of probability functions. I show that decision rules recently discussed by Sarah Moss, Susanna Rinard and Rohan Sud all suffer from the same defect: they all struggle to rationalize diachronic ambiguity aversion. Since ambiguity aversion is among the motivations for imprecise credence, this suggests that the search for an adequate imprecise decision rule is not yet over.

Do time travellers retain their normal freedom and abilities when they travel back in time? Lewis, Horwich and Sider argue that they do. Time-travelling Tim can kill his young grandfather, his younger self, or whomever else he pleases—and so, it seems can reasonably deliberate about whether to do these things. He might not succeed. But he is still just as free as a non-time traveller. I’ll disagree. The freedom of time travellers is limited by a rational constraint. Tim can’t reasonably (...) deliberate on killing his grandfather, certain that he’ll fail. If Tim follows his evidence, and appropriately self-predicts, he will be certain he won’t kill his grandfather. So if Tim is both evidentially and deliberatively rational, he can’t deliberate on killing his grandfather. This result has consequences. Firstly, it shows how evidential limits in the actual world contribute to our conception of the future as open. Secondly, it undercuts arguments against the possibility of time travel. Thirdly, it affects how we evaluate counterfactuals in time travel worlds, as well as our own. I’ll use the constraint to motivate an evidential and temporally neutral method of evaluating counterfactuals that holds fixed what a relevant deliberating agent has evidence of, independently of her decision. Using this method, an agent’s local abilities may be affected by what happens globally at other times, including the future. (shrink)

We introduce a distinction, unnoticed in the literature, between four varieties of objective Bayesianism. What we call ' strong objective Bayesianism' is characterized by two claims, that all scientific inference is 'logical' and that, given the same background information two agents will ascribe a unique probability to their priors. We think that neither of these claims can be sustained; in this sense, they are 'dogmatic'. The first fails to recognize that some scientific inference, in particular that concerning evidential relations, is (...) not (in the appropriate sense) logical, the second fails to provide a non-question-begging account of 'same background information'. We urge that a suitably objective Bayesian account of scientific inference does not require either of the claims. Finally, we argue that Bayesianism needs to be fine-grained in the same way that Bayesians fine-grain their beliefs. (shrink)

The author uses a series of potential counterexamples to argue against attempts by Bergmann and Plantinga to articulate a distinction between malignant and benign epistemic circularity and, more radically, to argue that epistemic circularity per se is no fallacy, and the concept of epistemic circularity plays no role in the explanation of why some instances of epistemic circularity are irrational. The author contrasts an inferential framework, in which circularity is a problem, with an equilibrium framework, in which the concept of (...) circularity plays no useful role and argues that defeasible reasoning can only be understood in an equilibrium, not an inferential, framework. The author uses an example of reasoning about the reliability of one’s own memory to explain how seemingly malignant epistemic circularity can be rational in an equilibrium framework. The author discusses the relevance of this conclusion to two contemporary issues: the cogency of Plantinga’s Evolutionary Argument against Naturalism and the evolutionary naturalists’ challenges to non-naturalist moral realism—and, indeed, to all forms of non-naturalist normative realism. (shrink)

Two compelling principles, the Reasonable Range Principle and the Preservation of Irrelevant Evidence Principle, are necessary conditions that any response to peer disagreements ought to abide by. The Reasonable Range Principle maintains that a resolution to a peer disagreement should not fall outside the range of views expressed by the peers in their dispute, whereas the Preservation of Irrelevant Evidence Principle maintains that a resolution strategy should be able to preserve unanimous judgments of evidential irrelevance among the peers. No standard (...) Bayesian resolution strategy satisfies the PIE Principle, however, and we give a loss aversion argument in support of PIE and against Bayes. The theory of imprecise probability allows one to satisfy both principles, and we introduce the notion of a set-based credal judgment to frame and address a range of subtle issues that arise in peer disagreements. (shrink)

Hans Herzberger's 1973 essay 'Ordinal Preference and Rational Choice' is a classic milestone in the erosion of the idea that rational agents are maximizers of utility. By the time Herzberger wrote, many authors had replaced this claim with the thesis that rational agents are maximizers of preference. That is to say, it was assumed that at the moment of choice a rational agent has a weak ordering representing his or her preferences among the options available to the agent for choice (...) and that the rational agent restricts choice to one of the optimal options. Such an option is an available option judged at least as good as any other.Herzberger explored the prospects of weakening this ordinalist view of maximizing .. (shrink)

Richard Rorty sings in the antifoundationalist chorus. His song equates the rise of foundationalist epistemology with the professionalization of philosophy. The discordant notes he finds in the foundationalist score become, as a consequence, subversive of philosophy as an autonomous discipline.Nonetheless, the most salient feature of Rorty's recent book, Philosophy and the Mirror of Nature, is that it is by a professional philosopher, for professional philosophers and about the future of philosophy as a profession. The early chapters of the book are (...) polished pieces of professional philosophical prose addressed to issues which have provoked interest in recent years among members of academic philosophy departments. They represent efforts to undermine foundationalist epistemology even in some of its currently fashionable guises as philosophy of language. (shrink)

While orthodox (Neyman-Pearson) statistical tests enjoy widespread use in science, the philosophical controversy over their appropriateness for obtaining scientific knowledge remains unresolved. I shall suggest an explanation and a resolution of this controversy. The source of the controversy, I argue, is that orthodox tests are typically interpreted as rules for making optimal decisions as to how to behave--where optimality is measured by the frequency of errors the test would commit in a long series of trials. Most philosophers of statistics, however, (...) view the task of statistical methods as providing appropriate measures of the evidential-strength that data affords hypotheses. Since tests appropriate for the behavioral-decision task fail to provide measures of evidential-strength, philosophers of statistics claim the use of orthodox tests in science is misleading and unjustified. What critics of orthodox tests overlook, I argue, is that the primary function of statistical tests in science is neither to decide how to behave nor to assign measures of evidential strength to hypotheses. Rather, tests provide a tool for using incomplete data to learn about the process that generated it. This they do, I show, by providing a standard for distinguishing differences (between observed and hypothesized results) due to accidental or trivial errors from those due to systematic or substantively important discrepancies. I propose a reinterpretation of a commonly used orthodox test to make this learning model of tests explicit. (shrink)

In “Truth and Probability” Ramsey claimed that the logic of consistency for probability is not a logic of truth. After supporting this claim, he proceeded to explore the possibilities for a logic of truth for probability. An examination of Ramsey's intent reveals that Ramsey was far from being an orthodox Bayesian when it comes to statistical reasoning. The relations between Ramsey's thought and the ideas of Keynes and Peirce are discussed.

The paper deals mainly with two problems in the epistemology of Frank Plumpton Ramsey. One concerns his account of knowledge, the other his fallibilism. I argue that Ramsey failed to make room for the social aspect of knowledge and, furthermore, that he did not separate the fallibility of our view from its corrigibility. My positive proposal is to combine social reliabilism and corrigibilism with a rejection of fallibilism.

We explore the question of whether sustained rational disagreement is possible from a broadly Bayesian perspective. The setting is one where agents update on the same information, with special consideration being given to the case of uncertain information. The classical merging of opinions theorem of Blackwell and Dubins shows when updated beliefs come and stay closer for Bayesian conditioning. We extend this result to a type of Jeffrey conditioning where agents update on evidence that is uncertain but solid (hard Jeffrey (...) shifts). However, merging of beliefs does not generally hold for Jeffrey conditioning on evidence that is fluid (soft Jeffrey shifts, Field shifts). Several theorems on the asymptotic behavior of subjective probabilities are proven. Taken together they show that while a consensus nearly always emerges in important special cases, sustained rational disagreement can be expected in many other situations. (shrink)

ABSTRACT: I shall consider the phenomenon of believing ourselves to have at least one false belief: a phenomenon I call believed fallibility I shall first present a paradoxical argument which appears to show that believed fallibility is incoherent; second, note that this argument assumes that we are committed to the conjunction of all our beliefs; third, sketch a more intuitive notion of commitment in which we are not committed to the conjunction of all our beliefs and argue that the original (...) paradoxical argument is now defused; fourth, construct a new paradoxical argument showing that if we believe that we have at least one false belief we are committed to a contradiction, employing the preferable notion of commitment; and, fifth, suggest that perhaps we might avoid the new paradox by denying that closing our beliefs under conjunction is required by rationalityRÉSUMÉ: Je me pencherai ici sur le phénomène qui consiste à penser que nous avons au moins une opinion fausse: je nomme ce phénoméne «la croyance d’etre faillible». Je présente en premier lieu un argument paradoxal qui semble démontrer que la croyance d’être faillible est incohérente. Deuxièmement, je remarque que cet argument suppose que nous nous obligions à réaliser la conjonction de toutes nosopinions. Troisièmement, je propose une version plus intuitive de cette obligation selon laquelle nous ne sommes pas obligés de réaliser la conjonction de toutes nos opinions, et je soutiens que le paradoxe initial est alors désamorcé. Quatrièmement, je construis un nouvel argument paradoxal démontrant que, si nous croyons que nous avons au moins une opinion fausse, nous sommes obligés de nous contredire, selon la notion d’obligation que je préconise d’adopter. Cinquièmement, je suggère que nous pourrions peut-être éviter ce nouveau paradoxe en niant que la rationalité exige de soumettre nos opinions à la conjonction. (shrink)