Finnur Dellsén

This paper presents and argues for an account of objectual understanding that aims to do justice to the full range of cases of scientific understanding, including cases in which one does not have an explanation of the understood phenomenon. According to the proposed account, one understands a phenomenon just in case one grasps a sufficiently accurate and comprehensive model of the ways in which it or its features are situated within a network of dependence relations; one’s degree of understanding is proportional to the comprehensiveness and accuracy of such a model. I compare this account with accounts of scientific understanding that explicate understanding in terms of having an explanation of the understood phenomenon. I discuss three distinct types of cases in which scientific understanding does not amount to possessing an explanation of any kind, and argue that the proposed model-based account can accommodate these cases while still retaining a strong link between understanding and explanation.

Suppose you and I are equally well informed on some factual issue and equally competent in forming beliefs on the basis of the information we possess. Having evaluated this information, each of us independently forms a belief on the issue. However, since neither of us is infallible, we may end up with contrary beliefs. How should I react if I discover that we disagree in this way? According to conciliatory views in the epistemology of disagreement, I should modify my original opinion by moving closer to your opinion. According to steadfast views, I should not.In the past decade or so, this issue has been addressed in hundreds of journal articles and a number of edited collections. The literature...

Scientists are constantly making observations, carrying out experiments, and analyzing empirical data. Meanwhile, scientific theories are routinely being adopted, revised, discarded, and replaced. But when are such changes to the content of science improvements on what came before? This is the question of scientific progress. One answer is that progress occurs when scientific theories ‘get closer to the truth’, i.e. increase their degree of truthlikeness. A second answer is that progress consists in increasing theories’ effectiveness for solving scientific problems. A third answer is that progress occurs when the stock of scientific knowledge accumulates. A fourth and final answer is that scientific progress consists in increasing scientific understanding, i.e. the capacity to correctly explain and reliably predict relevant phenomena. This paper compares and contrasts these four accounts of scientific progress, considers some of the most prominent arguments for and against each account, and briefly explores connections to different forms of scientific realism.

Dellsén (2017) has recently argued for an understanding-based account of scientific progress, the noetic account, according to which science (or a particular scientific discipline) makes cognitive progress precisely when it increases our understanding of some aspect of the world. Dellsén contrasts this account with Bird’s (2007, 2015) epistemic account, according to which such progress is made precisely when our knowledge of the world is increased or accumulated. In a recent paper, Park (2017) criticizes various aspects of Dellsén’s account and his arguments in favor of the noetic account as against Bird’s epistemic account. This paper responds to Park’s objections. Since a number of Park’s arguments rely on the idea that scientific progress may merely consists in “achieving the means to increase knowledge” (Park 2017: 570), I will start by discussing this “means-end thesis”.

What is required for an action to promote the satisfaction of a desire? We reject extant answers and propose an alternative. Our account differs from competing answers in two ways: first, it is contrastive, in that actions promote the satisfaction of desires only as contrasted with other possible actions. Second, it employs a notion of expected fit between desire and world, defined as the weighted sum of the fit between the desire and the world in all possible outcomes, where each weight is given by the probability of the agent’s obtaining the relevant outcome. According to our proposal, then, an action promotes a desire when the expected fit for the desire given that the agent performs the action is greater than the expected fit of the desire given that the agent performs the contrasting action. We highlight this account’s attractive features and explain how it improves on its competitors.

The moral of Buridan's Ass is that it can sometimes be rational to perform one action rather than another even though one lacks stronger reason to do so. Yet it is also commonly believed that it cannot ever be rational to believe one proposition rather than another if one lacks stronger reason to do so. This asymmetry has been taken to indicate a deep difference between epistemic and practical rationality. According to the view articulated here, the asymmetry should instead be explained by the difference between rational intentions and rational actions. Thus, it turns out, Buridan's Ass-style cases do not indicate an asymmetry between epistemic and practical rationality as such.

An influential suggestion about the relationship between Bayesianism and inference to the best explanation holds that IBE functions as a heuristic to approximate Bayesian reasoning. While this view promises to unify Bayesianism and IBE in a very attractive manner, important elements of the view have not yet been spelled out in detail. I present and argue for a heuristic conception of IBE on which IBE serves primarily to locate the most probable available explanatory hypothesis to serve as a working hypothesis in an agent’s further investigations. Along the way, I criticize what I consider to be an overly ambitious conception of the heuristic role of IBE, according to which IBE serves as a guide to absolute probability values. My own conception, by contrast, requires only that IBE can function as a guide to the comparative probability values of available hypotheses. This is shown to be a much more realistic role for IBE given the nature and limitations of the explanatory considerations with which IBE operates.

Inference to the Best Explanation (IBE) is widely criticized for being an unreliable form of ampliative inference – partly because the explanatory hypotheses we have considered at a given time may all be false, and partly because there is an asymmetry between the comparative judgment on which an IBE is based and the absolute verdict that IBE is meant to license. In this paper, I present a further reason to doubt the epistemic merits of IBE and argue that it motivates moving to an inferential pattern in which IBE emerges as a degenerate limiting case. Since this inferential pattern is structurally similar to an argumentative strategy known as Inferential Robustness Analysis (IRA), it effectively combines the most attractive features of IBE and IRA into a unified approach to non-deductive inference.

In recent years there has been a resurgence of interest among epistemologists in the nature of understanding, with some authors arguing that understanding should replace knowledge as the primary focus of epistemology. But what is understanding? According to what is often called the standard view, understanding is a species of knowledge. Although this view has recently been challenged in various ways, even the critics of the standard view have assumed that understanding requires justification and belief. I argue that it requires neither. If sound, these arguments have important upshots not only for the nature of understanding, but also for its distinctive epistemic value and its role in contemporary epistemology.

There are two main approaches to the epistemology of science. On the one hand, some hold that a scientific hypothesis is confirmed to the extent that the hypothesis explains the evidence better than alternative hypotheses concerning the same subject-matter. This idea is often referred to as Inference to the Best Explanation. On the other hand, some hold that a scientific hypothesis is confirmed to the extent that the hypothesis is probable given the evidence. This idea is often associated with Bayesianism or Bayesian epistemology. There has been some controversy on whether and how these two approaches may be reconciled. This paper criticizes some recent attempts to make peace between Bayesianism and Inference to the Best Explanation and sketches a new account of how the two approaches may be reconciled.

Among the most serious challenges to scientific realism are arguments for the underdetermination of theory by evidence. This paper defends a version of scientific realism against what is perhaps the most influential recent argument of this sort, viz. Kyle Stanford’s New Induction over the History of Science. An essential part of the defense consists in a probabilistic analysis of the slogan “absence of evidence is not evidence of absence”. On this basis it is argued that the likelihood of a theory being underdetermined depends crucially on social and historical factors, such as the structure of scientific communities and the time that has passed since the theory first became accepted. This is then shown to serve as the epistemological foundation for a version of scientific realism which avoids Stanford’s New Induction in a principled and non-question-begging way

This paper presents a new approach to resolving an apparent tension in Descartes’ discussion of scientific theories and explanations in the Principles of Philosophy. On the one hand, Descartes repeatedly claims that any theories presented in science must be certain and indubitable. On the other hand, Descartes himself presents an astonishing number of speculative explanations of various scientific phenomena. In response to this tension, commentators have suggested that Descartes changed his mind about scientific theories having to be certain and indubitable, that he lacked the conceptual resources to describe the appropriate epistemic attitude towards speculative theories, or that the presence of geometrical principles in these explanations guarantee their certainty. I argue that none of these responses is satisfactory and suggest a different resolution to the tension by examining Descartes’ notion of explanation. On Descartes’ view, providing an adequate explanation does not require being certain of the theories that constitute the explanans. Relatedly, the purpose of Cartesian explanations is not to discover the truth about the various underlying mechanisms that such explanations appeal to, but to support his general philosophical thesis that all natural phenomena can be explained by appealing to the extension of matter.

As it is standardly conceived, Inference to the Best Explanation (IBE) is a form of ampliative inference in which one infers a hypothesis because it provides a better potential explanation of one’s evidence than any other available, competing explanatory hypothesis. Bas van Fraassen famously objected to IBE thus formulated that we may have no reason to think that any of the available, competing explanatory hypotheses are true. While revisionary responses to the Bad Lot Objection concede that IBE needs to be reformulated in light of this problem, reactionary responses argue that the Bad Lot Objection is fallacious, incoherent, or misguided. This paper shows that the most influential reactionary responses to the Bad Lot Objection do nothing to undermine the original objection. This strongly suggests that proponents of IBE should focus their efforts on revisionary responses, i.e. on finding a more sophisticated characterization of IBE for which the Bad Lot Objection loses its bite.

What is scientific progress? On Alexander Bird’s epistemic account of scientific progress, an episode in science is progressive precisely when there is more scientific knowledge at the end of the episode than at the beginning. Using Bird’s epistemic account as a foil, this paper develops an alternative understanding-based account on which an episode in science is progressive precisely when scientists grasp how to correctly explain or predict more aspects of the world at the end of the episode than at the beginning. This account is shown to be superior to the epistemic account by examining cases in which knowledge and understanding come apart. In these cases, it is argued that scientific progress matches increases in scientific understanding rather than accumulations of knowledge. In addition, considerations having to do with minimalist idealizations, pragmatic virtues, and epistemic value all favor this understanding-based account over its epistemic counterpart.

Deductive Cogency holds that the set of propositions towards which one has, or is prepared to have, a given type of propositional attitude should be consistent and closed under logical consequence. While there are many propositional attitudes that are not subject to this requirement, e.g. hoping and imagining, it is at least prima facie plausible that Deductive Cogency applies to the doxastic attitude involved in propositional knowledge, viz. belief. However, this thought is undermined by the well-known preface paradox, leading a number of philosophers to conclude that Deductive Cogency has at best a very limited role to play in our epistemic lives. I argue here that Deductive Cogency is still an important epistemic requirement, albeit not as a requirement on belief. Instead, building on a distinction between belief and acceptance introduced by Jonathan Cohen and recent developments in the epistemology of understanding, I propose that Deductive Cogency applies to the attitude of treating propositions as given in the context of attempting to understand a given phenomenon. I then argue that this simultaneously accounts for the plausibility of the considerations in favor of Deductive Cogency and avoids the problematic consequences of the preface paradox.

It is often suggested that disagreement among scientific experts is a reason not to trust those experts, even about matters on which they are in agreement. In direct opposition to this view, I argue here that the very fact that there is disagreement among experts on a given issue provides a positive reason for non-experts to trust that the experts really are justified in their attitudes towards consensus theories. I show how this line of thought can be spelled out in three distinct frameworks for non-deductive reasoning: namely, Bayesian Confirmation Theory, Inference to the Best Explanation, and Inferential Robustness Analysis.

According to Bas van Fraassen, scientific realists and anti-realists disagree about whether accepting a scientific theory involves believing that the theory is true. On van Fraassen’s own anti-realist empiricist position, accepting a theory involves believing only that the theory is correct in its claims about observable aspects of the world. However, a number of philosophers have argued that acceptance and belief cannot be distinguished and thus that the debate is either confused or trivially settled in favor of the realist. In addition, another set of philosophers have argued that van Fraassen’s empiricist position appeals to an unmotivated distinction between observable and unobservable aspects of the world. This paper aims to reconstruct a van Fraassen-style empiricism about scientific acceptance that avoids these two objections – reconstructed empiricism.

Although many aspects of Inference to the Best Explanation have been extensively discussed, very little has so far been said about what it takes for a hypothesis to count as a rival explanatory hypothesis in the context of IBE. The primary aim of this article is to rectify this situation by arguing for a specific account of explanatory rivalry. On this account, explanatory rivals are complete explanations of a given explanandum. When explanatory rivals are conceived of in this way, I argue that IBE is a more plausible and defensible rule of inference than it would otherwise be. The secondary aim of the article is to demonstrate the importance of accounts of explanatory rivalry by examining a prominent philosophical argument in which IBE is employed, viz. the so-called Ultimate Argument for scientific realism. In short, I argue that a well-known objection to the Ultimate Argument due to Arthur Fine fails in virtue of tacitly assuming an account of explanatory rivalry that we have independent reasons to reject.