The preface paradox is a problem for everyone; you don’t need to be committed to any special epistemological theory to face the problem it raises. The problem of easy knowledge is supposed to be different in this respect. It is generally thought to arise only for those who believe there is such a thing as basic knowledge, i.e. knowledge acquired through a source that one does not know to be reliable or trustworthy. Because it is thought to arise only for (...) those who believe in basic knowledge, the problem of easy knowledge is generally regarded as a problem for, or objection to, the possibility of basic knowledge. (shrink)

Neither full belief nor partial belief is more fundamental, ontologically speaking. A survey of some relevant cognitive psychology supports a dualist ontology instead. Beliefs come in two kinds, categorical and graded, neither more fundamental than the other. In particular, the graded kind is no more fundamental. When we discuss belief in on/off terms, we are not speaking coarsely or informally about states that are ultimately credal.

Inference to the Best Explanation (IBE) and Bayesianism are our two most prominent theories of scientific inference. Are they compatible? Van Fraassen famously argued that they are not, concluding that IBE must be wrong since Bayesianism is right. Writers since then, from both the Bayesian and explanationist camps, have usually considered van Fraassen’s argument to be misguided, and have plumped for the view that Bayesianism and IBE are actually compatible. I argue that van Fraassen’s argument is actually not so misguided, (...) and that it causes more trouble for compatibilists than is typically thought. Bayesianism in its dominant, subjectivist form, can only be made compatible with IBE if IBE is made subservient to conditionalization in a way that robs IBE of much of its substance and interest. If Bayesianism and IBE are to be fit together, I argue, a strongly objective Bayesianism is the preferred option. I go on to sketch this objectivist, IBE-based Bayesianism, and offer some preliminary suggestions for its development. (shrink)

Evidence is univocal, not equivocal. Its implications don't depend on our beliefs or values, the evidence says what it says. But that doesn't mean there's no room for rational disagreement between people with the same evidence. Evaluating evidence is a lot like polling an electorate: getting an accurate reading requires a bit of luck, and even the best pollsters are bound to get slightly different results. So, even though evidence is univocal, rationality's requirements are not "unique." Understanding this resolves several (...) puzzles to do with uniqueness and disagreement. (shrink)

Conditionalization and Jeffrey Conditionalization cannot simultaneously satisfy two widely held desiderata on rules for empirical learning. The first desideratum is confirmational holism, which says that the evidential import of an experience is always sensitive to our background assumptions. The second desideratum is commutativity, which says that the order in which one acquires evidence shouldn't affect what conclusions one draws, provided the same total evidence is gathered in the end. (Jeffrey) Conditionalization cannot satisfy either of these desiderata without violating the other. (...) This is a surprising problem, and I offer a diagnosis of its source. I argue that (Jeffrey) Conditionalization is inherently anti-holistic in a way that is just exacerbated by the requirement of commutativity. The dilemma is thus a superficial manifestation of (Jeffrey) Conditionalization's fundamentally anti-holistic nature. (shrink)

The bootstrapping problem poses a general challenge, afflicting even strongly internalist theories. Even if one must always know that one’s source is reliable to gain knowledge from it, bootstrapping is still possible. I survey some solutions internalists might offer and defend the one I find most plausible: that bootstrapping involves an abuse of inductive reasoning akin to generalizing from a small or biased sample. I also argue that this solution is equally available to the reliabilist. The moral is that the (...) issues raised by bootstrapping are orthogonal to questions about internalism and basic knowledge, having more to do with the nature of good inductive reasoning. (shrink)

Representation theorems are often taken to provide the foundations for decision theory. First, they are taken to characterize degrees of belief and utilities. Second, they are taken to justify two fundamental rules of rationality: that we should have probabilistic degrees of belief and that we should act as expected utility maximizers. We argue that representation theorems cannot serve either of these foundational purposes, and that recent attempts to defend the foundational importance of representation theorems are unsuccessful. As a result, we (...) should reject these claims, and lay the foundations of decision theory on firmer ground. (shrink)

Van Fraassen famously endorses the Principle of Reflection as a constraint on rational credence, and argues that Reflection is entailed by the more traditional principle of Conditionalization. He draws two morals from this alleged entailment. First, that Reflection can be regarded as an alternative to Conditionalization – a more lenient standard of rationality. And second, that commitment to Conditionalization can be turned into support for Reflection. Van Fraassen also argues that Reflection implies Conditionalization, thus offering a new justification for Conditionalization. (...) I argue that neither principle entails the other, and thus neither can be used to motivate the other in the way van Fraassen says. There are ways to connect Conditionalization to Reflection, but these connections depend on poor assumptions about our introspective access, and are not tight enough to draw the sorts of conclusions van Fraassen wants. Upon close examination, the two principles seem to be getting at two quite independent epistemic norms. (shrink)

Recent proposals that frame norms of action in terms of knowledge have been challenged by Bayesian decision theorists. Bayesians object that knowledge-based norms conflict with the highly successful and established view that rational action is rooted in degrees of belief. I argue that the knowledge-based and Bayesian pictures are not as incompatible as these objectors have made out. Attending to the mechanisms of practical reasoning exposes space for both knowledge and degrees of belief to play their respective roles.

Handbook of the History of Logic, vol. 10, eds. Dov Gabbay, Stephan Hartmann, and John Woods, forthcoming.

Forty years ago, Bayesian philosophers were just catching a new wave of technical innovation, ushering in an era of scoring rules, imprecise credences, and infinitesimal probabilities. Meanwhile, down the hall, Gettier’s 1963 paper [28] was shaping a literature with little obvious interest in the formal programs of Reichenbach, Hempel, and Carnap, or their successors like Jeffrey, Levi, Skyrms, van Fraassen, and Lewis. And how Bayesians might accommodate the discourses of full belief and knowledge was but a glimmer in the eye (...) of Isaac Levi. Forty years later, scoring rules, imprecise credences, and infinitesimal probabilities are all the rage. And the formal and “informal” traditions are increasingly coming together as Bayesian arguments spill over into debates about the foundations of empirical knowledge, skepticism, and more. Relatedly, Bayesian interest in full belief and knowledge has never been greater. Much more besides has happened in the last forty years of Bayesian philosophy, .. (shrink)

Risk-weighted expected utility theory is motivated by small-world problems like the Allais paradox, but it is a grand-world theory by nature. And, at the grand-world level, its ability to handle the Allais paradox is dubious. The REU model described in Risk and Rationality turns out to be risk-seeking rather than risk-averse on one natural way of formulating the Allais gambles in the grand-world context. This result illustrates a general problem with the case for REU theory, we argue. There is a (...) tension between the small-world thinking marshaled against standard expected utility theory, and the grand-world thinking inherent to the risk-weighted alternative. (shrink)

Sometimes appearances provide epistemic support that gets undercut later. In an earlier paper I argued that standard Bayesian update rules are at odds with this phenomenon because they are ‘rigid’. Here I generalize and bolster that argument. I first show that the update rules of Dempster–Shafer theory and ranking theory are rigid too, hence also at odds with the defeasibility of appearances. I then rebut three Bayesian attempts to solve the problem. I conclude that defeasible appearances pose a more difficult (...) and pervasive challenge for formal epistemology than is currently thought. 1 The Challenge for Bayesianism1.1 Updating and experience1.2 The problem1.3 Objections2 The Challenge for Dempster–Shafer Theory2.1 Background on Dempster–Shafer theory2.2 The problem for Dempster–Shafer theory3 The Challenge for Ranking Theory4 The Appeal to Metacognition5 The Appeal to Richer Inputs6 The Appeal to a Generic Underminer7 Conclusion. (shrink)

Bootstrapping is a suspicious form of reasoning that verifies a source's reliability by checking it against itself. Theories that endorse such reasoning face the bootstrapping problem. This article considers which theories face the problem, and surveys potential solutions. The initial focus is on theories like reliabilism and dogmatism, which allow one to gain knowledge from a source without knowing that it is reliable. But the discussion quickly turns to a more general version of the problem that does not depend on (...) this allowance. Five potential solutions to the general problem are evaluated, and some implications for the literature on peer disagreement are considered. (shrink)

Elliott Sober has recently argued that the cosmological design argument is unsound, since our observation of cosmic fine-tuning is subject to an observation selection effect (OSE). I argue that this view commits Sober to rejecting patently correct design inferences in more mundane scenarios. I show that Sober's view, that there are OSEs in those mundane cases, rests on a confusion about what information an agent ought to treat as background when evaluating likelihoods. Applying this analysis to the design argument shows (...) that our observation of fine-tuning is not rendered uninformative by an OSE. Design and the Anthropic Objection Previous responses to the Anthropic Objection Variations: experimental squads and survivor reunions Why there is no OSE in firing squad cases Application to the design argument. (shrink)

In formal epistemology, we use mathematical methods to explore the questions of epistemology and rational choice. What can we know? What should we believe and how strongly? How should we act based on our beliefs and values? We begin by modelling phenomena like knowledge, belief, and desire using mathematical machinery, just as a biologist might model the fluctuations of a pair of competing populations, or a physicist might model the turbulence of a fluid passing through a small aperture. Then, we (...) explore, discover, and justify the laws governing those phenomena, using the precision that mathematical machinery affords. For example, we might represent a person by the strengths of their beliefs, and we might measure these using real numbers, which we call credences. Having done this, we might ask what the norms are that govern that person when we represent them in that way. How should those credences hang together? How should the credences change in response to evidence? And how should those credences guide the person’s actions? This is the approach of the first six chapters of this handbook. In the second half, we consider different representations—the set of propositions a person believes; their ranking of propositions by their plausibility. And in each case we ask again what the norms are that govern a person so represented. Or, we might represent them as having both credences and full beliefs, and then ask how those two representations should interact with one another. This handbook is incomplete, as such ventures often are. Formal epistemology is a much wider topic than we present here. One omission, for instance, is social epistemology, where we consider not only individual believers but also the epistemic aspects of their place in a social world. Michael Caie’s entry on doxastic logic touches on one part of this topic, but there is much more. Relatedly, there is no entry on epistemic logic, nor any on knowledge more generally. There are still more gaps. These omissions should not be taken as ideological choices. This material is missing, not because it is any less valuable or interesting, but because we v failed to secure it in time. Rather than delay publication further, we chose to go ahead with what is already a substantial collection. We anticipate a further volume in the future that will cover more ground. Why an open access handbook on this topic? A number of reasons. The topics covered here are large and complex and need the space allowed by the sort of 50 page treatment that many of the authors give. We also wanted to show that, using free and open software, one can overcome a major hurdle facing open access publishing, even on topics with complex typesetting needs. With the right software, one can produce attractive, clear publications at reasonably low cost. Indeed this handbook was created on a budget of exactly £0 (≈ $0). Our thanks to PhilPapers for serving as publisher, and to the authors: we are enormously grateful for the effort they put into their entries. (shrink)

We have known for a long time that there is complex, intelligent life. More recently we have discovered that the physics of our universe is fine-tuned so as to allow for the existence of such life. Call these two observations the Old Datum and the New Datum, respectively. Our question here is: once we know the Old Datum, does the New Datum provide additional evidence for the design hypothesis? I argue that it does not. Thus, there is an important sense (...) in which the much-touted fine-tuning of physics is irrelevant to debates about design. (shrink)

We often learn the opinions of others without hearing the evidence on which they're based. The orthodox Bayesian response is to treat the reported opinion as evidence itself and update on it by conditionalizing. But sometimes this isn't feasible. In these situations, a simpler way of combining one's existing opinion with opinions reported by others would be useful, especially if it yields the same results as conditionalization. We will show that one method---upco, also known as multiplicative pooling---is specially suited to (...) this role when the opinions you wish to pool concern hypotheses about chances. The result has interesting consequences: it addresses the problem of disagreement between experts; and it sheds light on the social argument for the uniqueness thesis. (shrink)

In Risk and Rationality, Lara Buchak advertised REU theory as able to recover the modal preferences in the Allais paradox. But we pointed out that REU theory only applies in the “grand world” setting, where it actually struggles with the modal Allais preferences. Buchak offers two replies. Here we enumerate technical and philosophical problems they face.

Clark and Shackel have recently argued that previous attempts to resolve the two-envelope paradox fail, and that we must look to symmetries of the relevant expected-value calculations for a solution. Clark and Shackel also argue for a novel solution to the peeking case, a variant of the two-envelope scenario in which you are allowed to look in your envelope before deciding whether or not to swap. Whatever the merits of these solutions, they go beyond accepted decision theory, even contradicting it (...) in the peeking case. Thus if we are to take their solutions seriously, we must understand Clark and Shackel to be proposing a revision of standard decision theory. Understood as such, we will argue, their proposal is both implausible and unnecessary. (shrink)

Much of our information comes to us indirectly, in the form of conclusions others have drawn from evidence they gathered. When we hear these conclusions, how can we modify our own opinions so as to gain the benefit of their evidence? In this paper we study the method known as geometric pooling. We consider two arguments in its favour, raising several objections to one, and proposing an amendment to the other.

I argue that the rationale behind the fine-tuning argument for design is self-undermining, refuting the argument’s own premise that fine-tuning is to be expected given design. In (Weisberg 2010) I argued on informal grounds that this premise is unsupported. White (2011) countered that it can be derived from three plausible assumptions. But White’s third assumption is based on a fallacious rationale, and is even objectionable by the design theorist’s own lights. The argument that shows this, the argument from divine (...) indifference, simultaneously exposes the fine-tuning argument’s self-undermining character. The same argument also answers Bradley’s (forthcoming) reply to my earlier objection. (shrink)

Some left-nested indicative conditionals are hard to interpret while others seem fine. Some proponents of the view that indicative conditionals have No Truth Values (NTV) use their view to explain why some left-nestings are hard to interpret: the embedded conditional does not express the truth conditions needed by the embedding conditional. Left-nestings that seem fine are then explained away as cases of ad hoc, pragmatic interpretation. We challenge this explanation. The standard reasons for NTV about indicative conditionals (triviality results, Gibbardian (...) standoffs, etc.) extend naturally to NTV about biconditionals. So NTVers about conditionals should also be NTVers about biconditionals. But biconditionals embed much more freely than conditionals. If NTV explains why some left-nested conditionals are hard to interpret, why do biconditionals embed successfully in the very contexts where conditionals do not embed? (shrink)

An introduction to Dempster-Shafter Theory, from a lecture at the Northern Institute of Philosophy in 2010.

Conditionalization is an intuitive and popular epistemic principle. By contrast, the Reflection principle is well known to have some very unappealing consequences. But van Fraassen argues that Conditionalization entails Reflection, so that proponents of Conditionalization must accept Reflection and its consequences. Van Fraassen also argues that Reflection implies Conditionalization, thus offering a new justification for Conditionalization. I argue that neither principle entails the other, and thus neither can be used to motivate the other in the way van Fraassen says. I (...) also propose a replacement for Reflection that accounts for the intuitions that made Reflection appealing, but doesn’t lead to Reflection’s bad consequences. (shrink)

Offers a diagnosis of the easy knowledge problem, according to which easy knowledge is unjustified belief because the inferences that deliver easy knowledge feign evidential support that is not actually there. This diagnosis leads to a rejection of Closure. But, I argue, this rejection of Closure is more plausible than the traditional one endorsed by tracking theorists. I also argue that my diagnosis suggests a general plausibility argument against Closure, since a number of epistemic goods traditionally associated with knowledge do (...) not transfer across known entailments. Finally, I defend Anti-Closure against two recent objections. (shrink)

An introduction to the motivations and mechanics of John Pollock's theory of defeasible reasoning, from a lecture at the Northern Institute of Philosophy in 2010.

An introduction to the motivations and mechanics of upper and lower probabilities, from a lecture given at the Northern Institute of Philosophy in 2010.

Jonathan Weisberg (2010 ) argues that, given that life exists, the fact that the universe is fine-tuned for life does not confirm the design hypothesis. And if the fact that life exists confirms the design hypothesis, fine-tuning is irrelevant. So either way, fine-tuning has nothing to do with it. I will defend a design argument that survives Weisberg’s critique — the fact that life exists supports the design hypothesis, but it only does so given fine-tuning.

The Fine-tuning argument takes the existence of life as evidence that an agent had a hand in making the universe. The argument is thought to hinge on the claim that ‘fine-tuning’ of various parameters is required for life to evolve. Jonathan Weisberg argues that even granting that life can provide evidence for design, further data about the fine-tuning required add nothing to the case. Weisberg charges the argument rests on unsupported assumptions about a designer’s preference for a (...) fine-tuned universe (over and above favouring life). I argue that he is mistaken. The assumptions that Weisberg grants (for the sake of argument) are sufficient to make fine-tuning relevant to design. (shrink)

Modelers often rely on robustness analysis, the search for predictions common to several independent models. Robustness analysis has been characterized and championed by Richard Levins and William Wimsatt, who see it as central to modern theoretical practice. The practice has also been severely criticized by Steven Orzack and Elliott Sober, who claim that it is a nonempirical form of confirmation, effective only under unusual circumstances. This paper addresses Orzack and Sober's criticisms by giving a new account of robustness analysis and (...) showing how the practice can identify robust theorems. Once the structure of robust theorems is clearly articulated, it can be shown that such theorems have a degree of confirmation, despite the lack of direct empirical evidence for their truth. (shrink)

This article reviews the recent literature on idealization, specifically idealization in the course of scientific modeling. We argue that idealization is not a unified concept and that there are three different types of idealization: Galilean, minimalist, and multiple models, each with its own justification. We explore the extent to which idealization is a permanent feature of scientific representation and discuss its implications for debates about scientific realism.

s Gibson (1982) correctly points out, despite Quine’s brief flirtation with a “mitigated phenomenalism” (Gibson’s phrase) in the late 1940’s and early 1950’s, Quine’s ontology of 1953 (“On Mental Entities”) and beyond left no room for non-physical sensory objects or qualities. Anyone familiar with the contemporary neo-dualist qualia-freak-fest might wonder why Quinean lessons were insufficiently transmitted to the current generation.

George P. Fletcher, With Justice for Some: Victims? Rights in Criminal Trials Reading, MA: Addison?Wesley Publishing Co., 1995, xi + 304 pp.

The Oxford Translation of Aristotle was originally published in 12 volumes between 1912 and 1954. It is universally recognized as the standard English version of Aristotle. This revised edition contains the substance of the original Translation, slightly emended in light of recent scholarship three of the original versions have been replaced by new translations and a new and enlarged selection of Fragments has been added. The aim of the translation remains the same: to make the surviving works of Aristotle readily (...) accessible to English speaking readers. (shrink)

one takes to be the most salient, any pair could be judged more similar to each other than to the third. Goodman uses this second problem to showthat there can be no context-free similarity metric, either in the trivial case or in a scientifically ...

From mitochondria to meerkats, the natural world is full of spectacular examples of social behaviour. In the early 1960s W. D. Hamilton changed the way we think about how such behaviour evolves. He introduced three key innovations - now known as Hamilton's rule, kin selection, and inclusive fitness - and his pioneering work kick-started a research program now known as social evolution theory. This is a book about the philosophical foundations and future prospects of that program. [Note: only the Introduction (...) is available to download.]. (shrink)

In debates about animal sentience, the precautionary principle is often invoked. The idea is that when the evidence of sentience is inconclusive, we should “give the animal the benefit of the doubt” or “err on the side of caution” in formulating animal protection legislation. Yet there remains confusion as to whether it is appropriate to apply the precautionary principle in this context, and, if so, what “applying the precautionary principle” means in practice regarding the burden of proof for animal sentience. (...) Here I construct a version of the precautionary principle tailored to the question of animal sentience together with a practical framework for implementing it. I explain and defend the key features of this framework, argue that it is well-aligned with current practice in animal welfare science, and consider and reject a number of influential counterarguments to the use of precautionary reasoning in this area. (shrink)

Evolutionary biology – or, more precisely, two (purported) applications of Darwin's theory of evolution by natural selection, namely, evolutionary psychology and what has been called human behavioral biology – is on the cusp of becoming the new rage among legal scholars looking for interdisciplinary insights into the law. We argue that as the actual science stands today, evolutionary biology offers nothing to help with questions about legal regulation of behavior. Only systematic misrepresentations or lack of understanding of the relevant biology, (...) together with far-reaching analytical and philosophical confusions, have led anyone to think otherwise. Evolutionary accounts are etiological accounts of how a trait evolved. We argue that an account of causal etiology could be relevant to law if (1) the account of causal etiology is scientifically well-confirmed, and (2) there is an explanation of how the well-confirmed etiology bears on questions of development (what we call the Environmental Gap Objection). We then show that the accounts of causal etiology that might be relevant are not remotely well-confirmed by scientific standards. We argue, in particular, that (a) evolutionary psychology is not entitled to assume selectionist accounts of human behaviors, (b) the assumptions necessary for the selectionist accounts to be true are not warranted by standard criteria for theory choice, and (c) only confusions about levels of explanation of human behavior create the appearance that understanding the biology of behavior is important. We also note that no response to the Environmental Gap Objection has been proffered. In the concluding section of the article, we turn directly to the work of Owen Jones, a leading proponent of the relevance of evolutionary biology to law, and show that he does not come to terms with any of the fundamental problems identified in this article. (shrink)

Sentience is the capacity to have feelings, such as feelings of pain, pleasure, hunger, thirst, warmth, joy, comfort and excitement. It is not simply the capacity to feel pain, but feelings of pain, distress or harm, broadly understood, have a special significance for animal welfare law. Drawing on over 300 scientific studies, we evaluate the evidence of sentience in two groups of invertebrate animals: the cephalopod molluscs or, for short, cephalopods (including octopods, squid and cuttlefish) and the decapod crustaceans or, (...) for short, decapods (including crabs, lobsters and crayfish). We also evaluate the potential welfare implications of current commercial practices involving these animals. (shrink)

Scientific research is almost always conducted by communities of scientists of varying size and complexity. Such communities are effective, in part, because they divide their cognitive labor: not every scientist works on the same project. Philip Kitcher and Michael Strevens have pioneered efforts to understand this division of cognitive labor by proposing models of how scientists make decisions about which project to work on. For such models to be useful, they must be simple enough for us to understand their dynamics, (...) but faithful enough to reality that we can use them to analyze real scientific communities. To satisfy the first requirement, we must employ idealizations to simplify the model. The second requirement demands that these idealizations not be so extreme that we lose the ability to describe real-world phenomena. This paper investigates the status of the assumptions that Kitcher and Strevens make in their models, by first inquiring whether they are reasonable representations of reality, and then by checking the models' robustness against weakenings of these assumptions. To do this, we first argue against the reality of the assumptions, and then develop a series of agent-based simulations to systematically test their effects on model outcomes. We find that the models are not robust against weakenings of these idealizations. In fact we find that under certain conditions, this can lead to the model predicting outcomes that are qualitatively opposite of the original model outcomes. (shrink)

This paper examines a series of Schelling-like models of residential segregation, in which agents prefer to be in the minority. We demon- strate that as long as agents care about the characteristics of their wider community, they tend to end up in a segregated state. We then investigate the process that causes this, and conclude that the result hinges on the similarity of informational states amongst agents of the same type. This is quite di erent from Schelling-like behavior, and sug- (...) gests (in his terms) that segregation is an instance of macro behavior which can arise from a wide variety of micro motives. (shrink)

What makes fast, cumulative cultural evolution work? Where did it come from? Why is it the sole preserve of humans? We set out a self-assembly hypothesis: cultural evolution evolved culturally. We present an evolutionary account that shows this hypothesis to be coherent, plausible, and worthy of further investigation. It has the following steps: (0) in common with other animals, early hominins had significant capacity for social learning; (1) knowledge and skills learned by offspring from their parents began to spread because (...) bearers had more offspring, a process we call CS1 (or Cultural Selection 1); (2) CS1 shaped attentional learning biases; (3) these attentional biases were augmented by explicit learning biases (judgements about what should be copied from whom). Explicit learning biases enabled (4) the high-fidelity, exclusive copying required for fast cultural accumulation of knowledge and skills by a process we call CS2 (or Cultural Selection 2), and (5) the emergence of cognitive processes such as imitation, mindreading and metacognition – ‘cognitive gadgets’ specialised for cultural learning. This self-assembly hypothesis is consistent with archaeological evidence that the stone tools used by early hominins were not dependent on fast, cumulative cultural evolution, and suggests new priorities for research on ‘animal culture’. (shrink)