Igor Douven

Assertion, Knowledge, and Rational Credibility

The view that assertions are governed by the rule that we should assert only what we know, is enjoying growing popularity. This paper argues that it is more plausible to assume that assertions are governed by the rule that we should assert only what is rationally credible to us. Specifically, it is shown that while the two rules are equally able to accommodate the relevant linguistic data, the latter is simpler than the former. There is a growing consensus among philosophers that the following rule governs the practice of assertion: One should assert only what one knows. (1) Call this the knowledge rule of assertion (or simply the knowledge rule), and call the thesis that (1) governs the practice of assertion the knowledge account of assertion. The present paper aims to make a case for a rival account of assertion, to wit (what I will refer to as) the rational credibility account of assertion. According to this, assertion is governed by the rational credibility rule, that is, the rule that One should assert only what is rationally credible to one. (2) Thus, on the view I will defend it is not required that a proposition be known for it to be warrantedly assertable; rational credibility suffices for that. In order to explain the methodology to be assumed in the following, I should note that in my view the project of determining which rule governs the practice of assertion is best not conceived as being an a priori investigation into the nature of assertion but rather as an empirical project, and that therefore any proposal that is being made in the course of this project is subject to the exact same standards of evaluation as are employed in the empirical sciences generally. That is to say, any hypothesis stating that a particular rule governs the practice of assertion must face the linguistic data about that practice; and if two or more such hypotheses are equally able to accommodate those data, then we may appeal to the so-called theoretical virtues (such as, most notably, simplicity) to help us choose between these hypotheses. I do not expect there to be any serious disagreement about the appropriateness of these methodological standards. Most proponents of the knowledge account 1See, for example, DeRose 1991, 1996, 2002, Brandom 1994, Williamson 1996, 2000, Sundholm 1999, 2004, and Adler 2002. In a rudimentary form, the view is already present in Black 1952, Moore 1962a, and Unger 1975.

Generalizing the Lottery Paradox

This paper is concerned with formal solutions to the lottery paradox on which high probability defeasibly warrants acceptance. It considers some recently proposed solutions of this type and presents an argument showing that these solutions are trivial in that they boil down to the claim that perfect probability is sufficient for rational acceptability. The argument is then generalized, showing that a broad class of similar solutions faces the same problem. 1. An argument against some formal solutions to the lottery paradox2. The argument generalized3. Some variations4. Adding modalities5. Anticipated objections An argument against some formal solutions to the lottery paradox The argument generalized Some variations Adding modalities Anticipated objections

A New Solution to the Paradoxes of Rational Acceptability

The Lottery Paradox and the Preface Paradox both involve the thesis that high probability is sufficient for rational acceptability. The standard solution to these paradoxes denies that rational acceptability is deductively closed. This solution has a number of untoward consequences. The present paper suggests that a better solution to the paradoxes is to replace the thesis that high probability suffices for rational acceptability with a somewhat stricter thesis. This avoids the untoward consequences of the standard solution. The new solution will be defended against a seemingly obvious objection. 1 The paradoxes of rational acceptability 2 The standard solution 3 A new solution to the paradoxes 4 Basic assumptions 5 The new solution defended 6 Conclusion 7 Appendix

Extending the Hegselmann–Krause Model III: From Single Beliefs to Complex Belief States

In recent years, various computational models have been developed for studying the dynamics of belief formation in a population of epistemically interacting agents that try to determine the numerical value of a given parameter. Whereas in those models, agents’ belief states consist of single numerical beliefs, the present paper describes a model that equips agents with richer belief states containing many beliefs that, moreover, are logically interconnected. Correspondingly, the truth the agents are after is a theory (a set of sentences of a given language) rather than a numerical value. The agents epistemically interact with each other and also receive evidence in varying degrees of informativeness about the truth. We use computer simulations to study how fast and accurately such populations as wholes are able to approach the truth under differing combinations of settings of the key parameters of the model, such as the degree of informativeness of the evidence and the weight the agents give to the evidence.

Similarity After Goodman

In a famous critique, Goodman dismissed similarity as a slippery and both philosophically and scientifically useless notion. We revisit his critique in the light of important recent work on similarity in psychology and cognitive science. Specifically, we use Tversky’s influential set-theoretic account of similarity as well as Gärdenfors’s more recent resuscitation of the geometrical account to show that, while Goodman’s critique contained valuable insights, it does not warrant a dismissal of similarity.

Extending the Hegselmann-Krause model I

Hegselmann and Krause have developed a simple yet powerful computational model for studying the opinion dynamics in societies of epistemically interacting truth-seeking agents. We present various extensions of this model and show their relevance to the investigation of socio-epistemic questions, with an emphasis on normative questions. Agent-based computer simulations have been successfully employed in the study of broadly social processes for over thirty years now. Researchers have investigated by these means such diverse phenomena as the spread of wealth in a population, the emergence and evolution of friendship networks, integration and segregation of different racial groups, the transmission of cultural values, and the propagation of infectious diseases. It is only in the past decade that agent-based simulations have come to be used for studying distinctively socio-epistemic (or socio-doxastic) questions, such as, most notably, questions concerning the roles various types of social interaction play in the acquisition and transmission of beliefs and knowledge. Pioneering work in this area has been carried out by Rainer Hegselmann and Ulrich Krause, who have developed, and systematically investigated, a simple yet already quite powerful model for simulating the opinion dynamics in societies of epistemically interacting truthseeking agents. By thus initiating what they have termed “Computer Aided Social Epistemology,” they have, in our eyes, made an important contribution to social epistemology. After all, social epistemology can be considered to be as much a branch of philosophy as of social science, and one may thus expect that it is able to profit from the deployment of simulation tools no less than the more traditional social sciences have been (and still are). Nevertheless, it has been generally recognized that, in addition to considerable virtues, the Hegselmann–Krause (HK) model also has some important inherent limitations, these being largely due to the fact that the model is starkly idealized in several respects. The present paper proposes various extensions of the model that do away 1See Epstein and Axtell [1996] and the references given there. 2See, e.g., Hegselmann and Krause [2002], [2005], and [2006]; see also Dittmer [2001], Fortunato [2004], and Lorenz [2007]. Similar work is to be found in Deffuant et al. [2000], Weisbuch et al. [2002], and Ramirez-Cano and Pitt [2006].

On the alleged impossibility of coherence

If coherence is to have justificatory status, as some analytical philosophers think it has, it must be truth-conducive, if perhaps only under certain specific conditions. This paper is a critical discussion of some recent arguments that seek to show that under no reasonable conditions can coherence be truth-conducive. More specifically, it considers Bovens and Hartmann’s and Olsson’s “impossibility results,” which attempt to show that coherence cannot possibly be a truth-conducive property. We point to various ways in which the advocates of a coherence theory of justification may attempt to divert the threat of these results.

The preface paradox revisited

The Preface Paradox has led many philosophers to believe that, if it isassumed that high probability is necessary for rational acceptability, the principleaccording to which rational acceptability is closed under conjunction (CP)must be abandoned. In this paper we argue that the paradox is far less damaging to CP than is generally believed. We describe how, given certain plausibleassumptions, in a large class of cases in which CP seems to lead tocontradiction, it does not do so after all. A restricted version of CP canthus be maintained.

THE DISCURSIVE DILEMMA AS A LOTTERY PARADOX

List and Pettit have stated an impossibility theorem about the aggregation of individual opinion states. Building on recent work on the lottery paradox, this paper offers a variation on that result. The present result places different constraints on the voting agenda and the domain of profiles, but it covers a larger class of voting rules, which need not satisfy the proposition-wise independence of votes.

Kaufmann on the Probabilities of Conditionals

Kaufmann has recently argued that the thesis according to which the probability of an indicative conditional equals the conditional probability of the consequent given the antecedent under certain specifiable circumstances deviates from intuition. He presents a method for calculating the probability of a conditional that does seem to give the intuitively correct result under those circumstances. However, the present paper shows that Kaufmann’s method is inconsistent in that it may lead one to assign different probabilities to a single conditional at the same time.