According to a standard assumption in epistemology, if one only partially believes that p , then one cannot thereby have knowledge that p. For example, if one only partially believes that that it is raining outside, one cannot know that it is raining outside; and if one only partially believes that it is likely that it will rain outside, one cannot know that it is likely that it will rain outside. Many epistemologists will agree that epistemic agents are capable (...) of partial beliefs in addition to full beliefs and that partial beliefs can be epistemically assessed along some dimensions. However, it has been generally assumed that such doxastic attitudes cannot possibly amount to knowledge. In Probabilistic Knowledge, Moss challenges this standard assumption and provides a formidable defense of the claim that probabilistic beliefs—a class of doxastic attitudes including credences and degrees of beliefs—can amount to knowledge too. Call this the probabilistic knowledge claim . Throughout the book, Moss goes to great lengths to show that probabilistic knowledge can be fruitfully applied to a variety of debates in epistemology and beyond. My goal in this essay is to explore a further application for probabilistic knowledge. I want to look at the role of probabilistic knowledge within a “knowledge-centered” psychology—a kind of psychology that assigns knowledge a central stage in explanations of intentional behavior. My suggestion is that Moss’s notion of probabilistic knowledge considerably helps further both a knowledge-centered psychology and a broadly intellectualist picture of action and know-how that naturally goes along with it. At the same time, though, it raises some interesting issues about the notion of explanation afforded by the resulting psychology. (shrink)

A critical reading of Sarah Moss's "Probabilistic Knowledge".

We report a series of experiments examining whether people ascribe knowledge for true beliefs based on probabilistic evidence. Participants were less likely to ascribe knowledge for beliefs based on probabilistic evidence than for beliefs based on perceptual evidence or testimony providing causal information. Denial of knowledge for beliefs based on probabilistic evidence did not arise because participants viewed such beliefs as unjustified, nor because such beliefs leave open the possibility of error. These findings rule (...) out traditional philosophical accounts for why probabilistic evidence does not produce knowledge. The experiments instead suggest that people deny knowledge because they distrust drawing conclusions about an individual based on reasoning about the population to which it belongs, a tendency previously identified by “judgment and decision making” researchers. Consistent with this, participants were more willing to ascribe knowledge for beliefs based on probabilistic evidence that is specific to a particular case. 2016 APA, all rights reserved). (shrink)

In mathematics, any form of probabilistic proof obtained through the application of a probabilistic method is not considered as a legitimate way of gaining mathematical knowledge. In a series of papers, Don Fallis has defended the thesis that there are no epistemic reasons justifying mathematicians’ rejection of probabilistic proofs. This paper identifies such an epistemic reason. More specifically, it is argued here that if one adopts a conception of mathematical knowledge in which an epistemic subject (...) can know a mathematical proposition based solely on a probabilistic proof, one is then forced to admit that such an epistemic subject can know several lottery propositions based solely on probabilistic evidence. Insofar as knowledge of lottery propositions on the basis of probabilistic evidence alone is denied by the vast majority of epistemologists, it is concluded that this constitutes an epistemic reason for rejecting probabilistic proofs as a means of acquiring mathematical knowledge. (shrink)

The value of knowledge can vary in that knowledge of important facts is more valuable than knowledge of trivialities. This variation in the value of knowledge is mirrored by a variation in evidential standards. Matters of greater importance require greater evidential support. But all knowledge, however trivial, needs to be evidentially certain. So on one hand we have a variable evidential standard that depends on the value of the knowledge, and on the other, we (...) have the invariant standard of evidential certainty. This paradox in the concept of knowledge runs deep in the history of philosophy. We approach this paradox by proposing a bet settlement theory of knowledge. Degrees of belief can be measured by the expected value of a bet divided by stake size, with the highest degree of belief being probability 1, or certainty. Evidence sufficient to settle the bet makes the expectation equal to the stake size and therefore has evidential probability 1. This gives us the invariant evidential certainty standard for knowledge. The value of knowledge relative to a bet is given by the stake size. We propose that evidential probability can vary with stake size, so that evidential certainty at low stakes does not entail evidential certainty at high stakes. This solves the paradox by allowing that certainty is necessary for knowledge at any stakes, but that the evidential standards for knowledge vary according to what is at stake. We give a Stake Size Variation Principle that calculates evidential probability from the value of evidence and the stakes. Stake size variant degrees of belief are probabilistically coherent and explain a greater range of preferences than orthodox expected utility theory, namely the Ellsberg and Allais preferences. The resulting theory of knowledge gives an empirically adequate, rationally grounded, unified account of evidence, value and probability. (shrink)

Moss (2018) argues that rational agents are best thought of not as having degrees of belief in various propositions but as having beliefs in probabilistic contents, or probabilistic beliefs. Probabilistic contents are sets of probability functions. Probabilistic belief states, in turn, are modeled by sets of probabilistic contents, or sets of sets of probability functions. We argue that this Mossean framework is of considerable interest quite independently of its role in Moss’ account of probabilistic (...) knowledge or her semantics for epistemic modals and probability operators. It is an extremely general model of uncertainty. Indeed, it is at least as general and expressively powerful as every other current imprecise probability framework, including lower probabilities, lower previsions, sets of probabilities, sets of desirable gambles, and choice functions. In addition, we partially answer an important question that Moss leaves open, viz., why should rational agents have consistent probabilistic beliefs? We show that an important subclass of Mossean believers avoid Dutch bookability iff they have consistent probabilistic beliefs. (shrink)

to appear in Lambert, E. and J. Schwenkler (eds.) Transformative Experience (OUP) -/- L. A. Paul (2014, 2015) argues that the possibility of epistemically transformative experiences poses serious and novel problems for the orthodox theory of rational choice, namely, expected utility theory — I call her argument the Utility Ignorance Objection. In a pair of earlier papers, I responded to Paul’s challenge (Pettigrew 2015, 2016), and a number of other philosophers have responded in similar ways (Dougherty, et al. 2015, Harman (...) 2015) — I call our argument the Fine-Graining Response. Paul has her own reply to this response, which we might call the Authenticity Reply. But Sarah Moss has recently offered an alternative reply to the Fine-Graining Response on Paul’s behalf (Moss 2017) — we’ll call it the No Knowledge Reply. This appeals to the knowledge norm of action, together with Moss’ novel and intriguing account of probabilistic knowledge. In this paper, I consider Moss’ reply and argue that it fails. I argue first that it fails as a reply made on Paul’s behalf, since it forces us to abandon many of the features of Paul’s challenge that make it distinctive and with which Paul herself is particularly concerned. Then I argue that it fails as a reply independent of its fidelity to Paul’s intentions. (shrink)

A consistent finding in research on conditional reasoning is that individuals are more likely to endorse the valid modus ponens (MP) inference than the equally valid modus tollens (MT) inference. This pattern holds for both abstract task and probabilistic task. The existing explanation for this phenomenon within a Bayesian framework (e.g., Oaksford & Chater, 2008) accounts for this asymmetry by assuming separate probability distributions for both MP and MT. We propose a novel explanation within a computational-level Bayesian account of (...) reasoning according to which “argumentation is learning”. We show that the asymmetry must appear for certain prior probability distributions, under the assumption that the conditional inference provides the agent with new information that is integrated into the existing knowledge by minimizing the Kullback-Leibler divergence between the posterior and prior probability distribution. We also show under which conditions we would expect the opposite pattern, an MT-MP asymmetry. (shrink)

There are numerous formal systems that allow inference of new conditionals based on a conditional knowledge base. Many of these systems have been analysed theoretically and some have been tested against human reasoning in psychological studies, but experiments evaluating the performance of such systems are rare. In this article, we extend the experiments in [19] in order to evaluate the inferential properties of c-representations in comparison to the well-known Systems P and Z. Since it is known that System Z (...) and c-representations mainly differ in the sorts of inheritance inferences they allow, we discuss subclass inheritance and present experimental data for this type of inference in particular. (shrink)

The goal of this paper is to review and critically discuss the philosophical aspects of probabilistic seismic hazard analysis (PSHA). Given that estimates of seismic hazard are typically riddled with uncertainty, diferent epistemic values (related to the pursuit of scientifc knowledge) compete in the selection of seismic hazard models, in a context infuenced by non-epistemic values (related to practical goals and aims) as well. We frst distinguish between the diferent types of uncertainty in PSHA. We claim that epistemic (...) and nonepistemic considerations are closely related in the selection of the appropriate estimate of seismic hazard by the experts. Finally, we argue that the division of scientifc responsibility among the experts can lead to responsibility gaps. This raises a problem for the ownership of the results (“no one’s model” problem) similar to the “problem of many hands” in the ethics of technology. We conclude with a plea for a close collaboration between philosophy and engineering. (shrink)

One thousand fair causally isolated coins will be independently flipped tomorrow morning and you know this fact. I argue that the probability, conditional on your knowledge, that any coin will land tails is almost 1 if that coin in fact lands tails, and almost 0 if it in fact lands heads. I also show that the coin flips are not probabilistically independent given your knowledge. These results are uncomfortable for those, like Timothy Williamson, who take these probabilities to (...) play a central role in their theorizing. (shrink)

McTaggart distinguished two conceptions of time: the A-series, according to which events are either past, present or future; and the B-series, according to which events are merely earlier or later than other events. Elsewhere, I have argued that these two views, ostensibly about the nature of time, need to be reinterpreted as two views about the nature of the universe. According to the so-called A-theory, the universe is three dimensional, with a past and future; according to the B-theory, the universe (...) is four dimensional. Given special relativity (SR), we are obliged, it seems, to accept (a modified version of) the B-series, four dimensional view, and reject the A-series, three dimensional view, because SR denies that there is a privileged, instantaneous cosmic "now" which seems to be required by the A-theory. Whether this is correct or not, it is important to remember that the fundamental problem, here, is not "What does SR imply?", but rather "What is the best guess about the ultimate nature of the universe in the light of current theoretical knowledge in physics?". In order to know how to answer this question, we need to have some inkling as to how the correct theory of quantum gravity incorporates quantum theory, probability and time. This is, at present, an entirely open question. String theory, or M-theory, seems to evade the issue, and other approaches to quantum gravity seem equally evasive. However, if probabilism is a fundamental feature of ultimate physical reality, then it may well be that the A-theory, or rather a closely related doctrine I call “objectism”, is built into the ultimate constitution of things. (shrink)

I review recent empirical findings on knowledge attributions in lottery cases and report a new experiment that advances our understanding of the topic. The main novel finding is that people deny knowledge in lottery cases because of an underlying qualitative difference in how they process probabilistic information. “Outside” information is generic and pertains to a base rate within a population. “Inside” information is specific and pertains to a particular item’s propensity. When an agent receives information that 99% (...) of all lottery tickets lose (outside information), people judge that she does not know that her ticket will lose. By contrast, when an agent receives information that her specific ticket is 99% likely to lose (inside information), people judge that she knows that her ticket will lose. Despite this difference in knowledge judgments, people rate the likelihood of her ticket losing the exact same in both cases (i.e. 99%). The results shed light on other factors affecting knowledge judgments in lottery cases, including formulaic expression and participants’ own estimation of whether it is true that the ticket will lose. The results also undermine previous hypotheses offered for knowledge denial in lottery cases, including the hypotheses that people deny knowledge because they either deny justification or acknowledge a chance for error. (shrink)

Many who think that naked statistical evidence alone is inadequate for a trial verdict think that use of probability is the problem, and something other than probability – knowledge, full belief, causal relations – is the solution. I argue that the issue of whether naked statistical evidence is weak can be formulated within the probabilistic idiom, as the question whether likelihoods or only posterior probabilities should be taken into account in our judgment of a case. This question also (...) identifies a major difference between the Process Reliabilist and Probabilistic Tracking views of knowledge and other concepts. Though both are externalist, and probabilistic, epistemic theories, Tracking does and Process Reliabilism does not put conditions on likelihoods. So Tracking implies that a naked statistic is not adequate evidence about an individual, and does not yield knowledge, whereas the Reliabilist thinks it gives justified belief and knowledge. Not only does the Tracking view imply that naked statistical evidence is insufficient for a verdict, but it gives us resources to explain why, in terms of risk and the special conditions of a trial. (shrink)

The principle of epistemic closure is the claim that what is known to follow from knowledge is known to be true. This intuitively plausible idea is endorsed by a vast majority of knowledge theorists. There are significant problems, however, that have to be addressed if epistemic closure – closed knowledge – is endorsed. The present essay locates the problem for closed knowledge in the separation it imposes between knowledge and evidence. Although it might appear that (...) all that stands between knowing the truth of the premises of a valid inference and knowledge of its conclusion is inferring it from the premises, the evidence for each of the premises may jointly count against the conclusion. The intuitive view regarding inferred knowledge says one thing, the evidence says another. One epistemological framework that seems to have the resources to resolve this tension endorses the view that knowledge always requires conclusive evidence. A second framework resolves the tension by limiting the scope of the closure principle. Only inferences drawn directly from propositions contained in the scope of a single knowledge operator are considered closed. The aim of the present essay is to revive the unpopular third option, the idea that knowledge is open. The essay proceeds by arguing that in different ways the two former frameworks only succeed in relocating the problem, not in resolving it. The first framework, the infallibilist view, relocates the problem to a sharp separation between knowledge of the occurrences of events from knowledge of their chance of occurring, a separation leading to several significant additional problems. The fallibilist view, the second framework, in endorsing closure neglects to take into full account the ways in which evidence fails to be transitive. For instance, evidence can count in favor of a conjunction while counting against each of its conjuncts. This fact, which is argued for in the essay on probabilistic as well as non-probabilistic grounds, is used as the foundation of an argument against closed knowledge that can be used as a way to understand several of the most fundamental challenges of epistemology. Not only can an open knowledge view that is based on open evidence resolve all these problems in a simple and natural way, it can also respond to formidable challenges that significantly hinder other open knowledge views. There are good reasons, then, to view both knowledge and evidence as open. (shrink)

In this paper it will be attempted to dissolve the lottery problem based on fallibilism, probabilism and the introduction of a so far widely neglected second context of knowledge. First, it will be argued that the lottery problem is actually an exemplification of the much wider Humean "future knowledge problem" (ch. 1). Two types of inferences and arguments will be examined, compared and evaluated in respect to their ability to fittingly describe the thought processes behind lottery/future knowledge (...) propositions (ch. 2). A second context of knowledge that underlines the importance of fallibilism and probabilism in a somewhat different manner will be introduced (ch. 3) and, based on that "two-context probabilism," the lottery/future knowledge problem will be dissolved (ch. 4). Lastly, it will be hinted at the necessity of adopting not just fallibilism including and two context minding probabilism, but, beyond that, also the even more encompassing position of both ontological and epistemological "gradualism" (ch. 5). (shrink)

There is a widespread view that in order to be rational we must mostly know what we believe. In the probabilistic tradition this is defended by arguments that a person who failed to have this knowledge would be vulnerable to sure loss, or probabilistically incoherent. I argue that even gross failure to know one's own beliefs need not expose one to sure loss, and does not if we follow a generalization of the standard bridge principle between first-order and (...) second-order beliefs. This makes it possible for a subject to use probabilistic decision theory to manage in a rational way cases of potential failure of this self-knowledge, as we find in implicit bias. Through such cases I argue that it is possible for uncertainty about what our beliefs are to be not only rationally permissible but advantageous. (shrink)

In the aftermath of Gettier’s examples, knowledge came to be thought of as what you would have if in addition to a true belief and your favorite epistemic goody, such as justifiedness, you also were ungettiered, and the theory of knowledge was frequently equated, especially by its detractors, with the project of pinning down that extra bit. It would follow that knowledge contributes something distinctive that makes it indispensable in our pantheon of epistemic concepts only if avoiding (...) gettierization has a value that can be explained without presupposing the value of knowledge. Tracking-type knowledge has a value that no other logically possible conditions on true belief does. As an Evolutionarily Stable Strategy it preserves appropriate belief states through time and changing circumstances. If we characterize gettierization through the concept of relevance matching, then we see that avoiding gettierization has a value independent of that of knowledge, namely, understanding, and that it is unnecessary to add a clause to the tracking conditions to make them suppress gettierization directly, though fallibly. The bright line of value is between gettierization avoidance and understanding on the one hand and knowledge on the other, and so should be the bright line defining concepts. The concept of relevance matching is key to a definition of what it is to understand why p is true, as opposed merely to knowing that p is true. Perfect tracking implies perfect relevance matching, so knowledge and understanding are intimately connected but understanding also requires that one own states that accomplish the relevance matching rather than achieving it vicariously. The theory of understanding based on relevance matching implies that understanding requires appreciation of not only p but its connections to other matters, and explains how it is possible to know that p is true without understanding why. The view implies that understanding is literally simulation, and is suggestive about understanding other minds. (shrink)

Inventing novel knowledge to solve problems is a crucial, creative, mechanism employed by humans, to extend their range of action. In this paper, we present TCL (typicality-based compositional logic): a probabilistic, non monotonic extension of standard Description Logics of typicality, and will show how this framework is able to endow artificial systems of a human-like, commonsense based, concept composition procedure that allows its employment in a number of applications (ranging from computational creativity to goal-based reasoning to recommender systems (...) and affective computing). -/- The framework relies on 3 main ingredients: a non monotonic extension of standard Description Logics (allowing to reason on exceptions to inheritance in standard knowledge bases) a probabilistic extension coming from the field of logic programming (the DISPONTE semantics) a cognitive heuristics known ad HEAD-Modifier determining preference rules for the inheritance mechanisms of the novel concepts to be generated via commonsense rules. -/- We report the obtained results and the lessons learned of this research path in the context of model-based AI applications. -/- . (shrink)

There are two competing theoretical frameworks with which cognitive sciences examines how people reason. These frameworks are broadly categorized into logic and probability. This paper reports two applied experiments to test which framework explains better how people reason about evidence in criminal cases. Logical frameworks predict that people derive conclusions from the presented evidence to endorse an absolute value of certainty such as ‘guilty’ or ‘not guilty’ (e.g., Johnson-Laird, 1999). But probabilistic frameworks predict that people derive conclusions from the (...) presented evidence in order that they may use knowledge of prior instances to endorse a conclusion of guilt which varies in certainty (e.g., Tenenbaum, Griffiths, & Kemp, 2006). Experiment 1 showed that reasoning about evidence of prior instances, such as disclosed prior convictions, affected participants’ underlying ratings of guilt. Participants’ guilt ratings increased in certainty according to the number of disclosed prior convictions. Experiment 2 showed that participants’ reasoning about evidence of prior convictions and some forensic evidence tended to lead participants to endorse biased ‘guilty’ verdicts when rationally the evidence does not prove guilt. Both results are predicted by probabilistic frameworks. The paper considers the implications for logical and probabilistic frameworks for reasoning in the real world. (shrink)

This paper briefly outlines some advancements in paraconsistent logics for modelling knowledge representation and reasoning. Emphasis is given on the so-called Logics of Formal Inconsistency (LFIs), a class of paraconsistent logics that formally internalize the very concept(s) of consistency and inconsistency. A couple of specialized systems based on the LFIs will be reviewed, including belief revision and probabilistic reasoning. Potential applications of those systems in the AI area of KRR are tackled by illustrating some examples that emphasizes the (...) importance of a fine-tuned treatment of consistency in modelling reputation systems, preferences, argumentation, and evidence. (shrink)

One is occasionally reminded of Foucault's proclamation in a 1970 interview that "perhaps, one day this century will be known as Deleuzian." Less often is one compelled to update and restart with a supplementary counter-proclamation of the mathematician, David Lindley: "the twenty-first century would be a Bayesian era..." The verb tenses of both are conspicuous. // To critically attend to what is today often feared and demonized, but also revered, deployed, and commonly referred to as algorithm(s), one cannot avoid the (...) mathematical and philosophical legacies of probability. // But attending to these probabilistic or Bayesian legacies must include an undeniable theological legacy in which they remain entangled. // We are not, today, discovering quirky theological metaphors in contemporary technics. It's the other way around. The technologies are mere metaphors of past theologies. (shrink)

There is a middle ground of imperfect knowledge in fields like medicine and the social sciences. It stands between our day-to-day relatively certain knowledge obtained from ordinary basic observation of regularities in our world and our knowledge from well-validated theories in the physical sciences. -/- The latter enable reliable prediction a great deal of the time of the happening of events never before experienced. The former enable prediction only of what has happened before and beyond that of (...) educated guesses which may sometimes prove right and others not when we test them. -/- The imperfection of our knowledge between those limits is a consequence of complexity. -/- Reductionist empiricism fails when faced with complexity but we all still have to live in a complex world where reductionist science cannot help us devise reliable theories from which we can predict the behaviour of the world around us. We cannot predict reliably. We can only monitor actively and manage actively the world around us if we want to try to control our environment. We have a limited prediction horizon. -/- Science and empiricism work well if we want to send Voyager I and II over 3 billion miles away but not for most other things. -/- In medicine how and when to apply probabilistic, conjectural, incomplete medical theories and explanations requires professional expertise, intuition and judgement (non scientific knowledge) which is essential. Medical diagnosis is a skill of predicting from knowledge of what has happened before that the past will recur in the current patient applying expertise and intuition from knowledge and experience of prior cases and probabilistic medical research and theory. The physician is left to an educated guess as to how the future will develop for the particular individual patient the focus of his or her current attention. (shrink)

When one thinks—knows, believes, imagines—that something is the case, one’s thought has a topic: it is about something, towards which one’s mind is directed. What is the logic of thought, so understood? This book begins to explore the idea that, to answer the question, we should take topics seriously. It proposes a hyperintensional account of the propositional contents of thought, arguing that these are individuated not only by the set of possible worlds at which they are true, but also by (...) their topic: what they are about. The book then builds epistemic, doxastic, probabilistic, and conditional logics based on this view. It applies them to issues ranging from dogmatism, scepticism, and epistemic fallibilism, to imagination and suppositional reasoning, belief revision, framing effects, and the acceptability of indicative conditionals. (shrink)

The paper argues that knowledge is not closed under logical inference. The argument proceeds from the openness of evidential support and the dependence of empirical knowledge on evidence, to the conclusion that knowledge is open. Without attempting to provide a full-fledged theory of evidence, we show that on the modest assumption that evidence cannot support both a proposition and its negation, or, alternatively, that information that reduces the probability of a proposition cannot constitute evidence for its truth, (...) the relation of evidential support is not closed under known entailment. Therefore the evidence-for relation is deductively open regardless of whether evidence is probabilistic or not. Given even a weak dependence of empirical knowledge on evidence, we argue that empirical knowledge is also open. On this basis, we also respond to the strongest argument in support of knowledge closure. Finally, we present a number of significant benefits of our position, namely, offering a unified explanation for a range of epistemological puzzles. (shrink)

The law views with suspicion statistical evidence, even evidence that is probabilistically on a par with direct, individual evidence that the law is in no way suspicious of. But it has proved remarkably hard to either justify this suspicion, or to debunk it. In this paper, we connect the discussion of statistical evidence to broader epistemological discussions of similar phenomena. We highlight Sensitivity – the requirement that a belief be counterfactually sensitive to the truth in a specific way – as (...) a way of epistemically explaining the legal suspicion towards statistical evidence. Still, we do not think of this as a satisfactory vindication of the reluctance to rely on statistical evidence. Knowledge – and Sensitivity, and indeed epistemology in general – are of little, if any, legal value. Instead, we tell an incentive-based story vindicating the suspicion towards statistical evidence. We conclude by showing that the epistemological story and the incentive-based story are closely and interestingly related, and by offering initial thoughts about the role of statistical evidence in morality. (shrink)

The deterministic or probabilistic laws of our representations and our science do not link what “is” to what “will be” but what “I know” to what “I could know”. Consistency is not a predicate on the physical laws of the world but on the logical laws of Meaning. If you cannot convince yourself of that. If you want to believe that the Softmatter of the Meaning cannot be more consistent than the Hardmatter of the physical world. Think again ... (...) ...and try to answer this question : Why would it be less unlikely for a physical world to evolve from the big bang to individuated knowing persons than for an amorphous interdependence to assemble (logically) individuated representations of the world ? (shrink)

The following article will attempt to highlight four questions which, in my opinion, are left unanswered (or overlooked) by QBism and to show the answers that the Ontology of Knowledge (OK) can provide. ● How does the subject come to exist for itself, individuated and persistent? ● From what common reality do world, mind, and meaning emerge? ● How does meaning emerge from the mathematical fact of probabilistic expectation? ● Is meaning animated by its own nature?

We propose a typology of representational artifacts for health care and life sciences domains and associate this typology with different kinds of formal ontology and logic, drawing conclusions as to the strengths and limitations for ontology in a description logics framework. The four types of domain representation we consider are: (i) lexico-semantic representation, (ii) representation of types of entities, (iii) representations of background knowledge, and (iv) representation of individuals. We advocate a clear distinction of the four kinds of representation (...) in order to provide a more rational basis for using ontologies and related artifacts to advance integration of data and enhance interoperability of associated reasoning systems. We highlight the fact that only a minor portion of scientifically relevant facts in a domain such as biomedicine can be adequately represented by formal ontologies as long as the latter are conceived as representations of entity types. In particular, the attempt to encode default or probabilistic knowledge using ontologies so conceived is prone to produce unintended, erroneous models. (shrink)

Plausible probabilistic accounts of evidential support entail that every true proposition is evidence for itself. This paper defends this surprising principle against a series of recent objections from Jessica Brown. Specifically, the paper argues that: (i) explanationist accounts of evidential support convergently entail that every true proposition is self-evident, and (ii) it is often felicitous to cite a true proposition as evidence for itself, just not under that description. The paper also develops an objection involving the apparent impossibility of (...) believing P on the evidential basis of P itself, but gives a reason not to be too worried about this objection. Establishing that every true proposition is self-evident saves probabilistic accounts of evidential support from absurdity, paves the way for a non-sceptical infallibilist theory of knowledge and has distinctive practical consequences. (shrink)

This is a critical discussion of the accuracy-first approach to epistemic norms. If you think of accuracy (gradational or categorical) as the fundamental epistemic good and think of epistemic goods as things that call for promotion, you might think that we should use broadly consequentialist reasoning to determine which norms govern partial and full belief. After presenting consequentialist arguments for probabilism and the normative Lockean view, I shall argue that the consequentialist framework isn't nearly as promising as it might first (...) appear. (shrink)

In this paper, I examine Cicero’s oft-neglected De Divinatione, a dialogue investigating the legitimacy of the practice of divination. First, I offer a novel analysis of the main arguments for divination given by Quintus, highlighting the fact that he employs two logically distinct argument forms. Next, I turn to the first of the main arguments against divination given by Marcus. Here I show, with the help of modern probabilistic tools, that Marcus’ skeptical response is far from the decisive, proto-naturalistic (...) assault on superstition that it is sometimes portrayed to be. Then, I offer an extended analysis of the second of the main arguments against divination given by Marcus. Inspired by Marcus’ second main argument, I formulate, explicate, and defend a substantive principle of scientific methodology that I call the “Ciceronian Causal-Nomological Requirement” (CCR). Roughly, this principle states that causal knowledge is essential for relying on correlations in predictive inference. Although I go on to argue that Marcus’ application of the CCR in his debate with Quintus is dialectically inadequate, I conclude that De Divinatione deserves its place in Cicero’s philosophical corpus, and that ultimately, its significance for the history and philosophy of science ought to be recognized. (shrink)

Reasoning over our knowledge bases and theories often requires non-deductive inferences, especially – but by no means only – when commonsense reasoning is the case, i.e. when practical agency is called for. This kind of reasoning can be adequately formalized via the notion of supraclassical consequence, a non-deductive consequence tightly associated with default and non-monotonic reasoning and featuring centrally in abductive, inductive, and probabilistic logical systems. In this paper, we analyze core concepts and problems of these systems in (...) the light of supraclassical consequence. (shrink)

Dawkins’ Ballet in the Garden of Theology. A Critical Assessment of Richard Dawkins’ Epistemological Theses on Theistic Beliefs from the God Delusion. Part II My paper presents an analysis and assessment of Richard Dawkins’ assumption from his book The God Delusion that there are no reason against treating belief in God as a scientific hypothesis, because even if the God existence is not disprovable, we could and maybe should ask if His existence is probable or highly improbable. My first aim (...) is to examine Dawkins' argumentation against if he is aware multiple possible ways interpretation of the claim that religious belief in God, construed as the hypothesis that existence of Creator may be treated as a scientific kind of hypothesis. My second aim is to show a nature of relation between his scientific God-hypothesis and his criticism of Thomas Henry Huxley agnosticism. I maintain that the he can't treat his probabilistic account of theism/atheism controversy as a ground for possible evidence for his controversial claim, that scientific knowledge could solve the problem of God's existence. As the matter of facts , things are just the opposite. I argue for claim that his construal of belief in God in terms of probabilistic scientific hypothesis is normatively weak and he can't use it in argumentation against rationality of belief in God even if he would be succesfully show that God-hypothesis is very weak and improbable explanation of origins and complexity of life. (shrink)

This paper argues that if knowledge is defined in terms of probabilistic tracking then the benefits of epistemic closure follow without the addition of a closure clause. (This updates my definition of knowledge in Tracking Truth 2005.) An important condition on this result is found in "Closure Failure and Scientific Inquiry" (2017).

This paper provides a systematic reconstruction of Cavendish's general epistemology and a characterization of the fundamental role of that theory in her natural philosophy. After reviewing the outlines of her natural philosophy, I describe her treatment of 'exterior knowledge', i.e. of perception in general and of sense perception in particular. I then describe her treatment of 'interior knowledge', i.e. of self-knowledge and 'conception'. I conclude by drawing out some implications of this reconstruction for our developing understanding of (...) Cavendish's natural philosophy. (shrink)

Indicative judgments pertain to what is true. Epistemic modal judgments pertain to what must or might be true relative to a body of information. A standard view is that epistemic modals implicitly quantify over alternative possibilities, or ways things could turn out. On this view, a proposition must be true just in case it is true in all the possibilities consistent with the available information, and a proposition might be true just in case it is true in at least one (...) possibility consistent with the available information. I report three experiments testing this view of epistemic modals. The results show that although modal judgments are sensitive to information about alternative possibilities, the standard quantification theory mischaracterizes the ordinary meaning of modals. I then report two more experiments testing the hypothesis that epistemic modals express willingness to attribute knowledge based on the available information. The results support this hypothesis. The results also show that the difference between “inside” and “outside” probabilistic information, familiar from the judgment and decision-making literature, affects epistemic modal judgments. (shrink)

Epistemic closure under known implication is the principle that knowledge of "p" and knowledge of "p implies q", together, imply knowledge of "q". This principle is intuitive, yet several putative counterexamples have been formulated against it. This paper addresses the question, why is epistemic closure both intuitive and prone to counterexamples? In particular, the paper examines whether probability theory can offer an answer to this question based on four strategies. The first probability-based strategy rests on the accumulation (...) of risks. The problem with this strategy is that risk accumulation cannot accommodate certain counterexamples to epistemic closure. The second strategy is based on the idea of evidential support, that is, a piece of evidence supports a proposition whenever it increases the probability of the proposition. This strategy makes progress and can accommodate certain putative counterexamples to closure. However, this strategy also gives rise to a number of counterintuitive results. Finally, there are two broadly probabilistic strategies, one based on the idea of resilient probability and the other on the idea of assumptions that are taken for granted. These strategies are promising but are prone to some of the shortcomings of the second strategy. All in all, I conclude that each strategy fails. Probability theory, then, is unlikely to offer the account we need. (shrink)

Against modal rationalism, Manolo Martínez argues that elementary bodily mechanisms allow cognizers to know possibility. He presents an exemplary behavioral mechanism adapted to maximizing expected outcome in a random game. The bodily mechanism purportedly tracks probabilities and related possibilities. However, it is doubtful that cognizers like us can know metaphysical modalities purely by virtue of bodily mechanisms without using rational capacities. Firstly, Martínez’s mechanism is limited. But knowledge of probabilities arguably has to cover a variety of probabilistic outcomes. (...) One may need an ability to calculate probabilities. Bodily mechanisms can realize such an ability, but this will presumably amount to instantiating rational capacities. Secondly, the purported connection between the items tracked by the bodily mechanism and genuine metaphysical possibilities is tenuous. There are points at which it may fail. Further, we would need to know by rational metaphysical considerations that the connection holds in order to bodily know possibilities. (shrink)

According to the probabilistic relevance account of confirmation, E confirms H relative to background knowledge K just in case P(H/K&E) > P(H/K). This requires an inequality between the rational degree of belief in H determined relative to two bodies of total knowledge which are such that one (K&E) includes the other (K) as a proper part. In this paper, I argue that it is quite plausible that there are no two possible bodies of total knowledge for (...) ideally rational agents meeting this requirement. Hence, the positive relevance account may have to be rejected. (shrink)

The problem of evil is the most prominent argument against the existence of God. Skeptical theists contend that it is not a good argument. Their reasons for this contention vary widely, involving such notions as CORNEA, epistemic appearances, 'gratuitous' evils, 'levering' evidence, and the representativeness of goods. We aim to dispel some confusions about these notions, in particular by clarifying their roles within a probabilistic epistemology. In addition, we develop new responses to the problem of evil from both the (...) phenomenal conception of evidence and the knowledge-first view of evidence. (shrink)

One very popular framework in contemporary epistemology is Bayesian. The central epistemic state is subjective confidence, or credence. Traditional epistemic states like belief and knowledge tend to be sidelined, or even dispensed with entirely. Credences are often introduced as familiar mental states, merely in need of a special label for the purposes of epistemology. But whether they are implicitly recognized by the folk or posits of a sophisticated scientific psychology, they do not appear to fit well with perception, as (...) is often noted. -/- This paper investigates the tension between probabilistic cognition and non-probabilistic perception. The tension is real, and the solution—to adapt a phrase from Quine and Goodman—is to renounce credences altogether. (shrink)

Games of chance are developed in their physical consumer-ready form on the basis of mathematical models, which stand as the premises of their existence and represent their physical processes. There is a prevalence of statistical and probabilistic models in the interest of all parties involved in the study of gambling – researchers, game producers and operators, and players – while functional models are of interest more to math-inclined players than problem-gambling researchers. In this paper I present a structural analysis (...) of the knowledge attached to mathematical models of games of chance and the act of modeling, arguing that such knowledge holds potential in the prevention and cognitive treatment of excessive gambling, and I propose further research in this direction. (shrink)

This paper defines the form of prior knowledge that is required for sound inferences by analogy and single-instance generalizations, in both logical and probabilistic reasoning. In the logical case, the first order determination rule defined in Davies (1985) is shown to solve both the justification and non-redundancy problems for analogical inference. The statistical analogue of determination that is put forward is termed 'uniformity'. Based on the semantics of determination and uniformity, a third notion of "relevance" is defined, both (...) logically and probabilistically. The statistical relevance of one function in determining another is put forward as a way of defining the value of information: The statistical relevance of a function F to a function G is the absolute value of the change in one's information about the value of G afforded by specifying the value of F. This theory provides normative justifications for conclusions projected by analogy from one case to another, and for generalization from an instance to a rule. The soundness of such conclusions, in either the logical or the probabilistic case, can be identified with the extent to which the corresponding criteria (determination and uniformity) actually hold for the features being related. (shrink)

This book tells the story of modern ethics, namely the story of a discourse that, after the Renaissance, went through a methodological revolution giving birth to Grotius’s and Pufendorf’s new science of natural law, leaving room for two centuries of explorations of the possible developments and implications of this new paradigm, up to the crisis of the Eighties of the eighteenth century, a crisis that carried a kind of mitosis, the act of birth of both basic paradigms of the two (...) following centuries: Kantian ethics and utilitarianism. The new science of natural law carried a fresh start for ethics, resulting from a mixture of the Old and the New. It was, as suggested by Schneewind, an attempt at rescuing the content of Scholastic and Stoic doctrines on a new methodological basis. The former was the claim of existence of objective and universal moral laws; the latter was the self-aware attempt at justifying a minimal kernel of such laws facing skeptical doubt. What Bentham and Kant did was precisely carrying this strategy further on, even if restructuring it each of them around one out of two alternative basic claims. The nineteenth- and twentieth-century critics of the Enlightenment attacked both not on their alleged failure in carrying out their own projects, but precisely on having adopted Grotius’s and Pufendorf’s project. What counter-enlightenment has been unable to spell out is which alternative project could be carried out facing the modern condition of pluralism, while on the contrary, if we takes a closer look at developments in twentieth-century ethics or at on-going discussions on practical issues, we might feel inclined to believe that Grotius’s and Pufendorf’s project is as up-to-date as ever. -/- Table of Contents -/- Preface I. Fathers of the Reformation and Schoolmen 1.1. Luther: passive justice and the good deeds; 1.2. Calvin: voluntarism and predestination; 1.3. Baroque Scholasticism; 1.4. Casuistry and Institutiones morales -/- II Neo-Platonists, neo-Stoics, neo-Sceptics 2.1. Aristotelian, neo-Platonic, neo-Epicurean and neo-Cynic Humanists; 2.2. Oeconomica and the art of living; 2.3. Neo-Stoics; 2.4. Neo-Sceptics; 2.5. Moralistic literature -/- III Neo-Augustinians 3.l. The Jansenists on natura lapsa, sufficient grace, pure love; 3.2. Nicole on the impossibility of self-knowledge; 3.3. Nicole on self-love and charity; 3.4. Nicole against civic virtue, for Christian civility; 3.5. Malebranche on general laws and necessary evil; 3.6. Malebranche on Neo-Augustinianism and Platonism. -/- IV Grotius, Pufendorf and the new moral science 4.1. Grotius against Aristotle and the sceptics; 4.2. Mersenne and Gassendi; 4.3. Descartes on ethics as the last branch of philosophy’s tree; 4.4. Hobbes on scepticism and the new moral science; 4.5. Spinoza on the new moral science as a descriptive science;4.6. Locke on voluntarism and probabilism; 4.7. Pufendorf on natural law as an exact science; 4.8. Pufendorf on physical and moral entities; 10. Pufendorf on self-preservation -/- V The empiricist version of the new moral science: from Cumberland to Paley 5.1. Cumberland against Hobbesian voluntarism; 5.2. Cumberland and theological consequentialism; 5.3. Cumberland on universal benevolence and self-love; 5.4. Shaftesbury on the moral sense; 5.5. Hutcheson on natural law and moral faculties; 5.6. Gay, Brown, Paley and theological consequentialism. -/- VI The rationalist version of the new moral science: from Cudworth to Price 6.1. The Cambridge Platonists; 6.2. Shaftesbury on the moral sense; 6.3. Butler and a third way between voluntarism and scepticism; 6.4. Price and the rational character of moral truths; -/- VII Leibniz’s compromise between the new moral science and Aristotelianism 1.Leibniz against voluntarism; 2.Leibniz against the division between the physical and the moral good; 3.Leibniz on la place d’autrui and theological consequentialism; 4.Thomasius, Wolff, Crusius -/- VIII French eighteenth-century philosophers without the new moral science 8.1. The genealogy of our ideas of virtue and vice; 8.2. Maupertuis and moral arithmetic 8.3. The philosophes and the harmony of interests; 8.4. Rousseau on corruption, self-love, and virtue; 8.5. Sade on the merits of vice -/- IX Experimental moral science: Hume and Adam Smith 9.1. Mandeville’s paradox; 9.2. Hutcheson on the law of nature and moral faculties; 9.3. Hume on experimental moral philosophy and the intermediate principles; 9.4. Hume’s Law; 9.5. Hume on the fellow-feeling; 9.6. Hume on natural and artificial virtues and disinterested pleasure for utility; 9.7. Adam Smith’s anti-realist metaethics; 9.8. Adam Smith on self-deception and the paradox of happiness; 9.9. Adam Smith on sympathy and the impartial spectator; 9.10. Adam Smith on the twofold criterion for moral judgement and its paradox; 9.11. Reid on the refutation of scepticism and the self-evidence of duty -/- X Kantian ethics 10.1. Kantian metaethics: moral epistemology; 10.2. Kantian metaethics: moral ontology; 10.3. Kantian metaethics: moral psychology; 10.4. Kantian normative ethics; 10.5. Kant on the impracticability of applied ethics; 10.6. Kantian moral anthropology; 10.7. Civilisation and moralisation; 10.8. Theology on a moral basis and the origins of evil; 10.9. Fichte and the transformation of theoretical philosophy into practical philosophy XI Bentham and utilitarianism 11.1. Bentham’s linguistic theory; 11.2. Bentham’s moral ontology, psychology, and theory of action; 11.3. The principle of greatest happiness; 11.4. The critique of religious ethics; 11.5. The new morality; 11.6. Interest and duty; 11.7. Virtues; 11.8. Private ethics and legislation -/- XII Followers of the Enlightenment: liberal Judaism and Liberal Theology 12.1. Mendelssohn; 12.2. Salomon Maimon; 12.3. Haskalā and liberal Judaism; 12.4. Liberal Theology. -/- XIII Counter-Enlighteners 13.1.Romanticism and the fulfilment of individuality as the Summum Bonum; 13.2. Hegel on history as the making of liberty; 13.3. Hegel on the unhappy consciousness and the beautiful soul; 13.4. Hegel on Morality and Sittlichkeit; 13.5. Marx on ideology, alienation, and praxis; 13.6. Schopenhauer on compassion; 13.7. Kierkegaard on faith beyond ethics. -/- XIV Followers of the Enlightenment: intuitionists and utilitarian 14.1 Whewell‘s criticism of utilitarianism; 14.2 Whewell on morality and the philosophy of morality; 14.3 Whewell on the Supreme Norm; 14.4 Whewell on the conflict between duties; 14.5 Mill and the proof of the principle of utility; 14.6 Mill’s eudemonistic utilitarianism; 14.7 Mill on rules -/- XV Followers of the Enlightenment: neo-Kantians and positivists 15.1. French spiritualism; 15.2. Neo-Kantians: the Marburg school; 15.3. Neo-Kantians: the Marburg school; 15.4. Comte’s positivism and the invention of altruism; 15.5. Social Darwinism; 15.6. Wundt and an ethic of humankind -/- XVI Post-enlighteners: Sidgwick 16.1. Criticism of intuitionism; 16.2. On ethical egoism; 16.3. Criticism of utilitarianism -/- XVII Post-enlighteners: Durkheim 17.1. Sociology as physics of customs; 17.2. Morality as physics of customs and as practical science; 17.3. On Kantian ethics and utilitarianism; 17.4. The variability of moralities;17.5. Social solidarity as end and justification of morality; 17.6. Secular morality as “sociodicy”; XVIII Post-enlighteners: Nietzsche 18.1. On the Dionysian; 18.2. On the deconstruction of the world of values 18.3 On the twofold genealogy of moralities; 18.4. On ascetics and nihilism; 18.5. Normative ethics of self-fulfilment -/- Bibliography / Index of names / Index of concepts -/- . (shrink)

This dissertation concerns Kierkegaard’s theory of indirect communication. A central aspect of this theory is what I call the “indispensability thesis”: there are some projects only indirect communication can accomplish. The purpose of the dissertation is to disclose and assess the rationale behind the indispensability thesis. -/- A pair of questions guides the project. First, to what does ‘indirect communication’ refer? Two acceptable responses exist: (1) Kierkegaard’s version of Socrates’ midwifery method and (2) Kierkegaard’s use of artful literary devices. Second, (...) for what end does Kierkegaard use indirect communication? There are two acceptable responses here as well: (1) helping others become religious and (2) making others aware of the nature of existence. -/- These responses are interrelated. First, Kierkegaard’s notion of religion places restrictions on the means he can use to get readers to become religious. These restrictions ultimately entail that the only viable form of religious pedagogy is the midwifery method. Second, Kierkegaard engages in the midwifery method in part by making readers aware of the nature of existence (especially religious existence). But given the problems plaguing his readers, he thinks a straightforward approach to this project will likely fail. An approach that used artful literary devices such as deception and humor would be more successful. Third, Kierkegaard believes that there is one aspect of religious existence (viz. subjectivity) that people can come to know only first-hand. As such, he cannot directly impart knowledge of subjectivity to his readers. He argues that this means he must use the midwifery method. And he thinks the most productive way to do so is to provide readers with the kind of fictional narratives found in his early pseudonymous writings. Thus artful rhetorical devices play a role here as well. -/- All of Kierkegaard’s arguments for the indispensability thesis turn on debatable assumptions. But the arguments concerning artful rhetorical devices have the additional defect of being merely probabilistic in nature. They lack the strength to support the indispensability thesis even if we grant the relevant background assumptions. Therefore, to the degree that the indispensability thesis has merit, it lies with the arguments concerning the midwifery method. (shrink)

Bayesianism is our leading theory of uncertainty. Epistemology is defined as the theory of knowledge. So “Bayesian Epistemology” may sound like an oxymoron. Bayesianism, after all, studies the properties and dynamics of degrees of belief, understood to be probabilities. Traditional epistemology, on the other hand, places the singularly non-probabilistic notion of knowledge at centre stage, and to the extent that it traffics in belief, that notion does not come in degrees. So how can there be a Bayesian (...) epistemology? (shrink)

Several scholars, including Martin Hengel, R. Alan Culpepper, and Richard Bauckham, have argued that Papias had knowledge of the Gospel of John on the grounds that Papias’s prologue lists six of Jesus’s disciples in the same order that they are named in the Gospel of John: Andrew, Peter, Philip, Thomas, James, and John. In “A Note on Papias’s Knowledge of the Fourth Gospel” (JBL 129 [2010]: 793–794), Jake H. O’Connell presents a statistical analysis of this argument, according to (...) which the probability of this correspondence occurring by chance is lower than 1%. O’Connell concludes that it is more than 99% probable that this correspondence is the result of Papias copying John, rather than chance. I show that O’Connell’s analysis contains multiple mistakes, both substantive and mathematical: it ignores relevant evidence, overstates the correspondence between John and Papias, wrongly assumes that if Papias did not know John he ordered the disciples randomly, and conflates the probability of A given B with the probability of B given A. In discussing these errors, I aim to inform both Johannine scholarship and the use of probabilistic methods in historical reasoning. (shrink)

The standard representation theorem for expected utility theory tells us that if a subject’s preferences conform to certain axioms, then she can be represented as maximising her expected utility given a particular set of credences and utilities—and, moreover, that having those credences and utilities is the only way that she could be maximising her expected utility. However, the kinds of agents these theorems seem apt to tell us anything about are highly idealised, being always probabilistically coherent with infinitely precise degrees (...) of belief and full knowledge of all a priori truths. Ordinary subjects do not look very rational when compared to the kinds of agents usually talked about in decision theory. In this paper, I will develop an expected utility representation theorem aimed at the representation of those who are neither probabilistically coherent, logically omniscient, nor expected utility maximisers across the board—that is, agents who are frequently irrational. The agents in question may be deductively fallible, have incoherent credences, limited representational capacities, and fail to maximise expected utility for all but a limited class of gambles. (shrink)