The two volumes to which this is apreface consist of the Proceedings of the Second International Conference on History and Philosophy of Science. The Conference was organized by the Joint Commission of the International Union of History and Philosophy of Science (IUHPS) under the auspices of the IUHPS, the Italian Society for Logic and Philosophy of Science, and the Domus Galilaeana of Pisa, headed by Professor Vincenzo Cappelletti. Domus Galilaeana also served as the host institution, with some help from the (...) University of Pisa. The Conference took place in Pisa, Italy, on September 4-8, 1978. The editors of these two volumes of the Proceedings of the Pisa Conference acknowledge with gratitude the help by the different sponsoring organizations, and in the first place that by both Divisions of the IUHPS, which made the Conference possible. A special recognition is due to Professor Evandro Agazzi, President of the Italian Society for Logic and Philosophy of Science, who was co opted as an additional member of the Organizing Committee. This committee was otherwise identical with the Joint Commission, whose members were initially John Murdoch, John North, Arpad Szab6, Robert Butts, Jaakko Hintikka, and Vadim Sadovsky. Later, Erwin Hiebert and Lubos Novy were appointed as additional members. (shrink)

The two volumes to which this is apreface consist of the Proceedings of the Second International Conference on History and Philosophy of Science. The Conference was organized by the Joint Commission of the International Union of History and Philosophy of Science under the auspices of the IUHPS, the Italian Society for Logic and Philosophy of Science, and the Domus Galilaeana of Pisa, headed by Professor Vincenzo Cappelletti. Domus Galilaeana also served as the host institution, with some help from the University (...) of Pisa. The Conference took place in Pisa, Italy, on September 4-8, 1978. The editors of these two volumes of the Proceedings of the Pisa Conference acknowledge with gratitude the help by the different sponsoring organizations, and in the first place that by both Divisions of the IUHPS, which made the Conference possible. A special recognition is due to Professor Evandro Agazzi, President of the Italian Society for Logic and Philosophy of Science, who was co opted as an additional member of the Organizing Committee. This committee was otherwise identical with the Joint Commission, whose members were initially John Murdoch, John North, Arpad Szab6, Robert Butts, Jaakko Hintikka, and Vadim Sadovsky. Later, Erwin Hiebert and Lubos Novy were appointed as additional members. (shrink)

A brief review and discussion of E. Fischbein's "The Intuitive Sources of Probabilistic Thinking in Children.".

In three experiments we explored developmental changes in probabilistic reasoning, taking into account the effects of cognitive capacity, thinking styles, and instructions. Normative responding increased with grade levels and cognitive capacity in all experiments, and it showed a negative relationship with superstitious thinking. The effect of instructions (in Experiments 2 and 3) was moderated by level of education and cognitive capacity. Specifically, only higher-grade students with higher cognitive capacity benefited from instructions to reason on the basis of (...) logic. The implications of these findings for research on the development of probabilistic reasoning are also discussed. (shrink)

Richard Jeffrey espoused an antifoundationalist variant of Bayesian thinking that he termed ‘Radical Probabilism’. Radical Probabilism denies both the existence of an ideal, unbiased starting point for our attempts to learn about the world and the dogma of classical Bayesianism that the only justified change of belief is one based on the learning of certainties. Probabilistic judgment is basic and irreducible. Bayesian conditioning is appropriate when interaction with the environment yields new certainty of belief in some proposition but (...) leaves one’s conditional beliefs untouched (the ‘Rigidity’ condition). Although Richard Jeffrey denied the general applicability of this condition, one of his main contributions to probabilistic thinking is a form of belief updating—now typically called ‘Jeffrey conditioning’ or ‘probability kinematics’—that is appropriate in circumstances in which Rigidity is satisfied, but where the interaction causes one to reevaluate one’s probability judgments over some partition of the possibility space without conferring certainty on any particular element. The most familiar occasion for Jeffrey conditioning is receipt of uncertain evidence: things partially perceived or remembered. But it also serves to illuminate belief updating occasioned by a change in one’s degrees of conditional belief, a kind of belief change largely ignored by classical Bayesianism. I argue that such changes in conditional belief can also be basic (in the sense of not being analyzable as a consequence of conditioning on factual information) and offer a kinematical model for a particular kind change in conditional belief. Both are applied to changes in preference. Finally, I argue that Rigidity can fail when changes of belief give inferential grounds for changes in conditional belief (and vice versa). These failures show that conditioning methods are properly regarded, not as valid rules of inference, but as tools in the ‘art of judgment’. (shrink)

I PSYCHOLOGY 5 The Probabilistic Revolution in Psychology--an Overview Gerd Gigerenzer 7 1 Probabilistic Thinking and the Fight against Subjectivity Gerd Gigerenzer 11 2 Statistical Method and the Historical Development of Research Practice in American Psychology Kurt Danziger 35 3 Survival of the Fittest Probabilist: Brunswik, Thurstone, and the Two Disciplines of Psychology Gerd Gigerenzer 49 4 A Perspective for Viewing the Integration of Probability Theory in Psychology David J. Murray 73 II SOCIOLOGY 101 5 The Two (...) Empirical Roots of Social Theory and the Probability Revolution Anthony Oberschall 103 III ECONOMICS 133 The Probabilistic Revolution in Economics--an Overview Mary S. Morgan 135 6 Why Was There No Probabilistic Revolution in Economic Thought? Claude Mènard 139 7 The Rise of Macroeconomic Calculations in Economic Statistics Robert A. Horváth 147 8 Statistics without Probability and Haavelmo’s Revolution in Econometrics Mary S. Morgan 171 IV PHYSIOLOGY 199 9 Experimental Physiology and Statistical Inference: The Therapeutic Trial in Nineteenth-Century Germany William Coleman 201 V EVOLUTIONARY BIOLOGY 227 The Probabilistic Revolution in Evolutionary Biology--an Overview John H. Beatty 229 10 Natural Selection as a Causal, Empirical, and Probabilistic Theory M. J. S. Hodge 233 11 Dobzhansky and Drift: Facts, Values, and Chance in Evolutionary Biology John H. Beatty 271 12 Random Genetic Drift, R. A. Fisher, and the Oxford School of Ecological Genetics John R. G. Turner 313 13 On the Prior Probability of the Existence of Life Bernd-Olaf Küppers 355 VI PHYSICS 371 The Probabilistic Revolution in Physics--an Overview Lorenz Krüger 373 14 Probabilistic Physics the Classical Way Jan von Plato 379 15 Max Born and the Reality of Quantum Probabilities Nancy Cartwright 409 16 Philosophical Problems of Quantum Theory: The Response of American Physicists Nancy Cartwright. (shrink)

The framework of elementary probabilistic operations (EPO) explains the structure of elementary probabilistic reasoning tasks as well as people’s performance on these tasks. The framework comprises three components: (a) Three types of probabilities: joint, marginal, and conditional probabilities; (b) three elementary probabilistic operations: combination, marginalization, and conditioning, and (c) quantitative inference schemas implementing the EPO. The formal part of the EPO framework is a computational level theory that provides a problem space representation and a classification of elementary (...) probabilistic problems based on computational requirements for solving a problem. According to the EPO framework, current methods for improving probabilistic reasoning are of two kinds: First, reduction of Bayesian problems to a type of probabilistic problems requiring less conceptual and procedural competencies. Second, enhancing people’s utilization competence by fostering the application of quantitative inference schemas. The approach suggests new applications, including the teaching of probabilistic reasoning, using analogical problem solving in probabilistic reasoning, and new methods for analyzing errors in probabilistic problem solving. (shrink)

Four experiments investigated the effects of probability manipulations on the indicative four card selection task (Wason, 1966, 1968). All looked at the effects of high and low probability antecedents (p) and consequents (q) on participants' data selections when determining the truth or falsity of a conditional rule, if p then q . Experiments 1 and 2 also manipulated believability. In Experiment 1, 128 participants performed the task using rules with varied contents pretested for probability of occurrence. Probabilistic effects were (...) observed which were partly consistent with some probabilistic accounts but not with non-probabilistic approaches to selection task performance. No effects of believability were observed, a finding replicated in Experiment 2 which used 80 participants with standardised and familiar contents. Some effects in this experiment appeared inconsistent with existing probabilistic approaches. To avoid possible effects of content, Experiments 3 (48 participants) and 4 (20 participants) used abstract material. Both experiments revealed probabilistic effects. In the Discussion we examine the compatibility of these results with the various models of selection task performance. (shrink)

This work is in two parts. The main aim of part 1 is a systematic examination of deductive, probabilistic, inductive and purely inductive dependence relations within the framework of Kolmogorov probability semantics. The main aim of part 2 is a systematic comparison of (in all) 20 different relations of probabilistic (in)dependence within the framework of Popper probability semantics (for Kolmogorov probability semantics does not allow such a comparison). Added to this comparison is an examination of (in all) 15 (...) purely inductive dependence relations. ————Part 1 leads in an axiomatic step-by-step development from the elementary classical truth value semantics of a sentential-logical language, called ‘L’, (chapter 1) to the elementary Kolmogorov probability semantics of L (chapter 2), which is then extended to four axiomatic semantical theories of dependence relations between the formulae of L. First the elementary Kolmogorov probability semantics of L is extended to a theory, called ‘Kdd’, of the relations of deductive dependence and deductive independence between formulae of L (chapter 3). Then Kdd is extended to a theory, called ‘Kpd1’, of the degree to which formulae of L probabilistically depend on each other in regard to a given probability distribution on the set of all formulae of L (chapter 4). Kpd1, in its turn, gets extended to a theory, called ‘Kpd2’, of the relations of probabilistic dependence and independence, relativized to unary Kolmogorov probability functions defined on L (chapter 5). Then Kpd2 is extended to a theory, called ‘Kid’, of the relations of inductive dependence and inductive independence, again relativized to unary Kolmogorov probability functions defined on L (chapter 6). Finally, Kid is extended to a theory, called ‘Kpid’, of the relations of purely inductive positive and negative dependence, relativized to unary Kolmogorov probability functions defined on L (chapter 7). ——Chapter 1, which deals with the familiar notions of truth value functions, tautologies, consequence relations and relations of logical opposition, is naturally the shortest chapter of part 1.——In chapter 2, the elementary classical semantics of L is extended to the elementary Kolmogorov probability semantics of L, i.e. to an axiomatic theory of unary and of binary Kolmogorov probability functions defined on the set of formulae of L. Because of the elementary character of this theory, chapter 2 is also rather short.——Chapter 3 introduces the first theory on dependence relations, to wit: Kdd, the theory of deductive (in)dependence between formulae of L. I follow here the well-known idea of Popper and Miller, who have used it in a famous discussion on the nature of probabilistic support for their arguments that probabilistic support is deductive, not inductive. I develop Kdd in the form of about 100 theorems, making ample use of the fact that deductive independence is nothing but subcontrary opposition, and close with a remark on the fundamental difference between deductive and logical dependence—two relations the ideas of which are all too easily mixed up.——Chapters 4 and 5 deal extensively with the traditional ideas of probabilistic (in)dependence, applied to formulae rather than to events. As always, I proceed axiomatically in a step-by-step process under systematic viewpoints and obtain about 300 theorems in this way. In the formulation of the theorems, I took special care to state clearly and expressly so-called tacit assumptions, especially those concerning the probability values of the formulae said to be dependent on each other. These assumptions are usually missing in the literature, due either to economy of writing or to sloppiness of thinking. Presumably, both chapters contain little that is new, their value lying more in the systematic grouping and organic development of the theorems than in the newness of these.——In chapter 6, I extend the axiomatic theory about probabilistic (in)dependence which has been elaborated in chapter 5, to an axiomatic theory of inductive (in)dependence by requiring of the relation of inductive (in)dependence that it be probabilistic (in)dependence, but not also logical implication or logical opposition. I point out the differences between probabilistic and inductive (in)dependence by means of some 60 theorems and close my examination of inductive (in)dependence by considering its relationship to the notion of support in the philosophy of science.——Finally, in chapter 7, the last of part 1, I take the step from inductive dependence to what I call ‘purely inductive dependence’ by combining the idea of inductive dependence with that of deductive independence in a way which is suggested by writings of Popper and Miller. I arrive at two noteworthy theorems. Firstly, there is indeed no purely inductive support. But secondly, and perhaps amazingly, countersupport is purely inductive.————Whereas the probabilistic framework of part 1 of the present work is Kolmogorov probability semantics, the framework of part 2 is Popper probability semantics, which is not only worth examining as a fascinating alternative to orthodox Kolmogorov probability semantics, but also allows us to examine dependence relations more deeply, than Kolmogorov probability semantics does. Part 2 leads—again in an axiomatic step-by-step development—from the basic Popper probability semantics of L, called ‘Pb’, (chapter 8) via a probabilistic theory of logical attributes, called ‘Ps’, (chapter 9) to four axiomatic semantical theories of dependence relations between the formulae of L. First, Ps is extended to a theory, called ‘Pdd’, of the relations of deductive dependence and deductive independence between formulae of L (chapter 10). Then Pdd is extended to a theory, called ‘Ppd’, of (in all) 20 relations of probabilistic (in)dependence, relativized to binary Popper probability functions defined on L (chapter 11). Ppd, in its turn, is extended to a theory, called ‘Pid’, of (in all) 10 relations of inductive dependence, again relativized to binary Popper probability functions defined on L (first part of chapter 12). Finally, Pid is extended to a theory, called ‘Ppid’, of (in all) 15 relations of purely inductive positive and negative dependence, relativized to binary Popper probability functions defined on L (second part of chapter 12).——Chapter 8, the first chapter of part 2 of the present work, is entirely preparatory. It introduces the axioms and about 180 theorems (150 of them together with their proofs) of basic Popper probability semantics in order to set this kind of semantics under way.——Then, in chapter 9, basic Popper probability semantics is extended to a probabilistic theory of logical properties of and relations between the formulae of L. Although I think that the way I did this extension is of some interest in itself, the main task of chapter 9 is again a preparatory one: to yield the indispensable lemmata (about 90 in number) for the theorems concerning probabilistic dependence relations in chapter 11 and concerning inductive dependence relations in chapter 12.——Chapter 10 brings the extension of Ps to the theory Pdd of deductive (in)dependence. Only half a dozen theorems are noted here for later use in the Pdd-extensions Ppd and Ppid. In view of the over 100 theorems already gained on this topic in the Kolmogorovian framework (cf. chapter 3), a similar extensive elaboration of Pdd would have been superfluous.——Chapter 11 is the most important one of part 2. It consists of a systematic comparison of 20 probabilistic (in)dependence concepts by means of about 230 theorems, obtained within the axiomatic theory Ppd, which is built up as an extension of Pdd. The main points of comparison were: differences in logical strength; reflexivity and symmetry; behaviour under the condition that the probability values of the formulae in question are extreme. It turned out that each of the examined concepts violates a strong and straightforward version of the intuitive requirement that probabilistic dependence should go with logical dependence. Whereas the corresponding chapter 5 in part 1 of the present work may not have led to new theorems, chapter 11 yields dozens of them in the process of comparison of concepts of dependence and independence which had—as far as I know—never before been treated in a single theoretical framework. With Popper probability semantics, this framework has become available, and here I have simply made full use of it.——In chapter 12, I extend the theory Ppd of probabilistic (in)dependence to the theories Pid and Ppid of inductive and purely inductive dependence, in a way very similar to that in which I have extended the theory Kpd2 to the theories Kid and Kpid in chapters 6 and 7. The first main result of Kpid (roughly: there is no purely inductive support) could be repeated for four of the five purely inductive positive dependence relations considered in chapter 12, whereas the second main result of Kpid (roughly: there is purely inductive countersupport ) could be repeated for each of the five examined purely inductive negative dependence relations. Chapter 12 closes with a brief recapitulation and critical discussion of the main results. (shrink)

Humean promotionalists about reasons think that whether there is a reason for an agent to ϕ depends on whether her ϕ-ing promotes the satisfaction of at least one of her desires. Several authors have recently defended probabilistic accounts of promotion, according to which an agent’s ϕ-ing promotes the satisfaction of one of her desires just in case her ϕ-ing makes the satisfaction of that desire more probable relative to some baseline. In this paper I do three things. First, I (...) formalize an argument, due to Jeff Behrends and Joshua DiPaolo, to the effect that Mark Schroeder’s and Stephen Finlay’s probabilistic accounts of promotion cannot be correct. Next, I extend this argument to a recent alternative offered by D. Justin Coates and show how Coates’ attempt to avoid the argument by introducing a distinction between ‘intrinsic’ and ‘extrinsic’ probability doesn’t help. Finally, I suggest an alternative way of understanding promotion in terms of increase in degree of fit between the causal upshot of an action and the content of a desire. I show how this view, disjunctively paired with probabilism about promotion, solves the problems with previous accounts. (shrink)

In the two-envelope problem, a reasoner is offered two envelopes, one containing exactly twice the money in the other. After observing the amount in one envelope, it can be traded for the unseen contents of the other. It appears that it should not matter whether the envelope is traded, but recent mathematical analyses have shown that gains could be made if trading was a probabilistic function of amount observed. As a problem with a purely probabilistic solution, it provides (...) a potentially interesting way to test people's consistency with probabilistic models. Three experiments did this by varying the size of both the observed and maximum amounts, and their possible distribution. The results showed that trading decisions were affected by where the observed amount in the opened envelope fell in the distribution, though its size did not always do so. This suggests that participants’ trade decisions could be affected by the perceived probabilities of different observed amounts, which is consistent with the pro.. (shrink)

In addition to beliefs, people have attitudes of confidence called credences. Combinations of credences, like combinations of beliefs, can be inconsistent. It is common to use tools from probability theory to understand the normative relationships between a person’s credences. More precisely, it is common to think that something is a consistency norm on a person’s credal state if and only if it is a simple transformation of a truth of probability. Though it is common to challenge the right-to-left direction of (...) this biconditional, I argue in this paper that the left-to-right direction is false for standard versions of probability theory. That is, I make the case that there are consistency constraints on credal states that are not simple transformations of truths of standard versions of probability theory. I do so by drawing on a newly discovered type of credal attitude, a quantificational credence, and by showing how the consistency norms on this attitude can’t be represented as simple transformations of truths of standard versions of probability theory. I conclude by showing that a probability theory that could avoid the result would have to be strikingly different from the standard versions—so different that I suspect many would hesitate to call it a theory of probability at all. (shrink)

The aim of this paper is to examine whether it would be advantageous to introduce knowledge norms instead of the currently assumed rational credence norms into the debate about decision making under normative uncertainty. There is reason to think that this could help us better accommodate cases in which agents are rationally highly confident in false moral views. I show how Moss’ view of probabilistic knowledge can be fruitfully employed to develop a decision theory that delivers plausible verdicts in (...) these cases. I also argue that, for this new view to be better than existing alternatives, it must adopt a particular solution to the new evil demon problem, which asks whether agents and their BIV-counterparts are equally justified. In order to get an attractive decision theory for cases of moral uncertainty, we must reject the claim that agents and their BIV-counterparts are equally justified. Moreover, the resulting view must be supplemented with a moral epistemology that explains how it is possible to be rationally morally uncertain. This is especially challenging if we assume that moral truths are knowable a priori. (shrink)

If we are eventually to understand the capability of higher organisms for perceptual recognition, generalization, recall, and thinking, we must first have answers to three fundamental questions: 1. How is information about the physical world sensed, or detected, by the biological system? 2. In what form is information stored, or remembered? 3. How does information contained in storage, or in memory, influence recognition and behavior? The first of these questions is in the.

I generalize the notion of a conditional attitude by bringing together two topics of inquiry. One is the ordinary inquiry into conditional attitudes. The other topic is the inquiry into the attitude of thinking that a proposition is likely, or having a high credence in a proposition. For instance, what is it to intend to go to the game if it is likely that Kershaw pitches? Being likely that Kershaw pitches is the condition of the attitude. Given a natural (...) position about statements like “It is likely that Kershaw pitches,” the target attitude looks different from ordinary conditional attitudes. (shrink)

Here's a short introduction to some mind-boggling paradoxes concerning probability.

The present study assessed the degree to which probabilistic reasoning performance and thinking style influenced perception of risk and self-reported levels of terrorism-related behaviour change. A sample of 263 respondents, recruited via convenience sampling, completed a series of measures comprising probabilistic reasoning tasks (perception of randomness, base rate, probability, and conjunction fallacy), the Reality Testing subscale of the Inventory of Personality Organization (IPO-RT), the Domain-Specific Risk-Taking Scale, and a terrorism-related behaviour change scale. Structural equation modelling examined three (...) progressive models. Firstly, the Independence Model assumed that probabilistic reasoning, perception of risk and reality testing independently predicted terrorism-related behaviour change. Secondly, the Mediation Model supposed that probabilistic reasoning and reality testing correlated, and indirectly predicted terrorism-related behaviour change through perception of risk. Lastly, the Dual-Influence Model proposed that probabilistic reasoning indirectly predicted terrorism-related behaviour change via perception of risk, independent of reality testing. Results indicated that performance on probabilistic reasoning tasks most strongly predicted perception of risk, and preference for an intuitive thinking style (measured by the IPO-RT) best explained terrorism-related behaviour change. The combination of perception of risk with probabilistic reasoning ability in the Dual-Influence Model enhanced the predictive power of the analytical-rational route, with conjunction fallacy having a significant indirect effect on terrorism-related behaviour change via perception of risk. The Dual-Influence Model possessed superior fit and reported similar predictive relations between intuitive-experiential and analytical-rational routes and terrorism-related behaviour change. The discussion critically examines these findings in relation to dual-processing frameworks. This includes considering the limitations of current operationalisations and recommendations for future research that align outcomes and subsequent work more closely to specific dual-process models. (shrink)

The unanimity theory is an account of property-level causation requiring that causes raise the probability of their effects in specified test situations. Richard Otte (1981) and others have presented counterexamples in which one property is probabilistically sufficient for at least one other property. Given the continuing discussion (e.g., Cartwright 1989; Cartwright and Dupre 1988; Eells 1988a,b), many apparently think that these problems are minor. By considering the impact of Otte's cases on recent versions of the theory, by raising several new (...) examples, and by criticizing natural replies, I argue that the problems for the unanimity theory are severe. (shrink)

A great deal of scholarship defines rational thought in terms of probability theory. An important problem with such an approach is that disasters, particularly large disasters, do not provide us with a meaningful distribution of events that would approximate a normal curve. Here, I propose that using possibilistic thinking can helpfully complement probabilistic thinking regarding risk and disaster. Possibilistic thinking highlights consequences of actions or events, while not ignoring their likelihood of occurrence. I point out the (...) myriad ways that individuals and organizations use possibilistic thinking, even if they do not recognized it as such. I propose several conceptual tools to help discipline a possibilistic approach. (shrink)

This innovative text is psychologically informed, both in its diagnosis of inferential errors, and in teaching students how to watch out for and work around their natural intellectual blind spots. It also incorporates insights from epistemology and philosophy of science that are indispensable for learning how to evaluate premises. The result is a hands-on primer for real world critical thinking. The authors bring a fresh approach to the traditional challenges of a critical thinking course: effectively explaining the nature (...) of validity, assessing deductive arguments, reconstructing, identifying and diagramming arguments, and causal and probabilistic inference. Additionally, they discuss in detail, important, frequently neglected topics, including testimony, including the evaluation of news and other information sources, the nature and credibility of science, rhetoric, and dialectical argumentation. The treatment of probability uses frequency trees and a frequency approach more generally, and argument reconstruction is taught using argument maps; these methods have been shown to improve students’ reasoning and argument evaluation. (shrink)

The second edition of a unique introductory text, offering an account of the logical tradition in philosophy and its influence on contemporary scientific disciplines. Thinking Things Through offers a broad, historical, and rigorous introduction to the logical tradition in philosophy and its contemporary significance. It is unique among introductory philosophy texts in that it considers both the historical development and modern fruition of a few central questions. It traces the influence of philosophical ideas and arguments on modern logic, statistics, (...) decision theory, computer science, cognitive science, and public policy. The text offers an account of the history of speculation and argument, and the development of theories of deductive and probabilistic reasoning. It considers whether and how new knowledge of the world is possible at all, investigates rational decision making and causality, explores the nature of mind, and considers ethical theories. Suggestions for reading, both historical and contemporary, accompany most chapters. This second edition includes four new chapters, on decision theory and causal relations, moral and political theories, “moral tools” such as game theory and voting theory, and ethical theories and their relation to real-world issues. Examples have been updated throughout, and some new material has been added. It is suitable for use in advanced undergraduate and beginning graduate classes in philosophy, and as an ancillary text for students in computer science and the natural sciences. (shrink)

Scoring rules measure the deviation between a credence assignment and reality. Probabilism holds that only those credence assignments that satisfy the axioms of probability are rationally admissible. Accuracy-based arguments for probabilism observe that given certain conditions on a scoring rule, the score of any non-probability is dominated by the score of a probability. The conditions in the arguments we will consider include propriety: the claim that the expected accuracy of _p_ is not beaten by the expected accuracy of any other (...) credence _c_ by the lights of _p_ if _p_ is a probability. I argue that if we think through how a non-probabilist can respond to pragmatic arguments for probabilism, we will expect the non-probabilist to accept a condition _stronger_ than propriety for the same reasons that the probabilist gives for propriety, but this stronger condition is incompatible with the other conditions that the probabilist needs to run the accuracy argument. This makes it unlikely for the probabilist’s argument to be compelling. (shrink)

This paper analyzes individual probabilistic predictions of state outcomes in the 2008 U.S. presidential election. Employing an original survey of more than 19,000 respondents, ours is the first study of electoral forecasting to involve multiple subnational predictions and to incorporate the influence of respondents’ home states. We relate a range of demographic, political, and cognitive variables to individual accuracy and predictions, as well as to how accuracy improved over time. We find strong support for wishful thinking bias in (...) expectations, as Republicans gave higher probabilities to McCain victories and were worse at overall prediction. In addition, we find that respondents living in states with higher vote shares for Obama performed better at prediction and displayed less wishful thinking bias. We conclude by showing that suitable aggregations of our respondents’ predictions outperformed Intrade (a prediction market) and fivethirtyeight.com (a poll-based forecast) at most points in time. (shrink)

The term “exchange paradox” refers to a situation in which it appears to be advantageous for each of two holders of an envelope containing some amount of money to always exchange his or her envelope for that of the other individual, which they know contains either half or twice their own amount. We review several versions of the problem and show that resolving the paradox depends on the specifics of the situation, which must be disambiguated, and on the player's beliefs. (...) The latter psychological variables are part and parcel of the resolution. Assuming reasonable subjective distributions, exchanging cannot always be advantageous for both players. We suggest several deep-rooted psychological reasons for the considerable difficulty people demonstrably have in dealing with this problem. Implicit widespread and compelling assumptions—that affect judgement in diverse contexts—obstruct the solution. Analysing this paradox underscores the close connection between psychology and probability theory. (shrink)

This book argues that there is a joint in nature between seeing and thinking, perception, and cognition. Perception is constitutively iconic, nonconceptual, and nonpropositional, whereas cognition does not have these properties constitutively. The book does not appeal to “intuitions,” as is common in philosophy, but to empirical evidence, including experiments in neuroscience and psychology. The book argues that cognition affects perception, i.e., that perception is cognitively penetrable, but that this does not impugn the joint in nature. A key part (...) of the argument is that we perceive not only low-level properties like colors, shapes, and textures but also high-level properties such as faces and causation. Along the way, the book explains the difference between perception and perceptual memory, the differences between format and content, and whether perception is probabilistic despite our lack of awareness of probabilistic properties. The book argues for perceptual categories that are not concepts, that perception need not be singular, that perceptual attribution and perceptual discrimination are equally fundamental, and that basic features of the mind known as “core cognition” are not a third category in between perception and cognition. The chapter on consciousness leverages these results to argue against some of the most widely accepted theories of consciousness. Although only one chapter is about consciousness, much of the rest of the book repurposes work on consciousness to isolate the scientific basis of perception. (shrink)

The endorsement of epistemically suspect (i.e., paranormal, conspiracy, and pseudoscientific) beliefs is widespread and has negative consequences. Therefore, it is important to understand the reasoning processes – such as lower analytic thinking and susceptibility to cognitive biases – that might lead to the adoption of such beliefs. In two studies, I constructed and tested a novel questionnaire on epistemically suspect beliefs (Study 1, N = 263), and used it to examine probabilistic reasoning biases and belief bias in syllogistic (...) reasoning as predictors of the endorsement of those beliefs, while accounting for analytic thinking and worldview variables (Study 2, N = 397). Probabilistic reasoning biases, analytic thinking, religious faith, and political liberalism consistently predicted various epistemically suspect beliefs, whereas the effect of syllogistic belief bias was largely restricted to pseudoscientific beliefs. Further research will be needed to examine the role the biased evaluation of evidence plays in the endorsement of epistemically suspect beliefs. (shrink)

The endorsement of epistemically suspect (i.e., paranormal, conspiracy, and pseudoscientific) beliefs is widespread and has negative consequences. Therefore, it is important to understand the reasoning processes – such as lower analytic thinking and susceptibility to cognitive biases – that might lead to the adoption of such beliefs. In two studies, I constructed and tested a novel questionnaire on epistemically suspect beliefs (Study 1, N = 263), and used it to examine probabilistic reasoning biases and belief bias in syllogistic (...) reasoning as predictors of the endorsement of those beliefs, while accounting for analytic thinking and worldview variables (Study 2, N = 397). Probabilistic reasoning biases, analytic thinking, religious faith, and political liberalism consistently predicted various epistemically suspect beliefs, whereas the effect of syllogistic belief bias was largely restricted to pseudoscientific beliefs. Further research will be needed to examine the role the biased evaluation of evidence plays in the endorsement of epistemically suspect beliefs. (shrink)

The feature-matching approach pioneered by Amos Tversky remains a groundwork for psychological models of similarity and categorization but is rarely explicitly justified considering recent advances in thinking about cognition. While psychologists often view similarity as an unproblematic foundational concept that explains generalization and conceptual thought, long-standing philosophical problems challenging this assumption suggest that similarity derives from processes of higher-level cognition, including inference and conceptual thought. This paper addresses three specific challenges to Tversky’s approach: (i) the feature-selection problem, (ii) the (...) problem of cognitive implausibility, and (iii) the problem of unprincipled tweaking. It subsequently supports key insights from Tversky’s account based on recent developments in Bayesian modeling of cognition. A novel computational view of similarity as inference is proposed that addresses each challenge by considering the contrast class as constitutive of similarity and selecting for highly informative features. In so doing, this view illustrates the ongoing promise of the feature-matching approach in explaining perception, generalization and conceptual thought by grounding them in principles of probabilistic inference. (shrink)

In What is a Law of Nature? (1983) David Armstrong promotes a theory of laws according to which laws of nature are contingent relations of necessitation between universals. The metaphysics Armstrong develops uses deterministic causal laws as paradigmatic cases of laws, but he thinks his metaphysics explicates other sorts of laws too, including probabilistic laws, like that of the half-life of radium being 1602 years. Bas van Fraassen (1987) gives seven arguments for why Armstrong’s theory of laws is incapable (...) of explicating probabilistic laws. The main thrust of the arguments is that Armstrong’s metaphysical apparatus serves to drive up the initial probability values stated by probabilistic laws. Armstrong replies .. (shrink)

Crupi et al. (Think Reason 14:182–199, 2008) have recently advocated and partially worked out an account of the conjunction fallacy phenomenon based on the Bayesian notion of confirmation. In response, Schupbach (2009) presented a critical discussion as following from some novel experimental results. After providing a brief restatement and clarification of the meaning and scope of our original proposal, we will outline Schupbach’s results and discuss his interpretation thereof arguing that they do not actually undermine our point of view if (...) properly construed. Finally, we will foster such a claim by means of some novel data. (shrink)

ABSTRACTThe probabilistic truth table task involves assessing the probability of "If A then C" conditional sentences. Previous studies have shown that a majority of participants assess this probability as the conditional probability P while a substantial minority responds with the probability of the conjunction A and C. In an experiment involving 96 participants, we investigated the impact on the rate of conjunctive responses of the context in which the task is framed. We show that a context intended to lead (...) participants to consider all the possible cases elicited more conjunctive responses than a context assumed not to have this effect. These results suggest that the step of inferring the probability can distort our assessment of participants' interpretation of conditional sentences. This might compromise the validity of the probabilistic task in studying conditional reasoning. (shrink)

Reasoning about social groups and their associated markers was investigated as a particular case of human reasoning about cue-category relationships. Assertions that reasoning involving cues and associated categories elicits specific probabilistic assumptions are supported by the results of three experiments. This phenomenon remains intact across the use of categorical syllogisms, conditional syllogisms, and the use of social groups that vary in their perceived cohesiveness, or entitativity. Implications are discussed for various theories of reasoning, and additional aspects of social group/coalitional (...) reasoning are also discussed. (shrink)

The materialist critics argue that insuperable difficulties are encountered by the hypothesis that immaterial mental events such as thinking can act in any way on material structures such as neurons of the cerebral cortex, as is diagrammed in Fig. 8. Such a presumed action is alleged to be incompatible with the conservation laws of physics, in particular of the First Law of Thermodynamics. This objection would certainly be sustained by 19th century physicists and by neuroscientists and philosophers who are (...) still ideologically in the physics of the 19th century, not recognizing the revolution wrought by quantum physicists in the 20th century. Unfortunately it is rare for a quantum physicist to dare an intrusion into the brain-mind problem. But in a recent book the quantum physicist Margenau (1984) makes a fundamental contribution. It is a remarkable transformation from 19th century physics to be told (p. 22): "that some fields, such as the probability field of quantum mechanics carry neither energy nor matter." He goes on (p. 96) to state: "In very complicated physical systems such as the brain, the neurons and sense organs, whose constituents are small enough to be governed by probabilistic quantum laws, the physical organ is always poised for a multitude of possible changes, each with a definite probability; if one change takes place that requires energy, or more or less energy than another, the intricate organism furnishes it automatically. Hence, even if the mind has anything to do with the change, that is if there is a mind-body interaction, the mind would not be called upon to furnish energy." In summary (p. 97) Margenau states that: "The mind may be regarded as a field in the accepted physical sense of the term. But it is a nonmaterial field; its closest analogue is perhaps a probability field. It cannot be compared with the simpler nonmaterial fields that require the presence of matter (e.g. gravity) nor does it necessarily have a definite position in space. And so far as present evidence goes it is not an energy field in any physical sense, nor is it required to contain energy in order to account for all known phenomena in which mind interacts with brain". In formulating more precisely the dualist hypothesis of mind-brain interaction, the initial statement is that the whole world of mental events (World 2) has an existence as autonomous as the world of matter-energy (World I ) (Fig. 1). The present interactionist hypothesis does not relate to these ontological problems, but merely to the mode of action of mental events on neural events, that is of the nature of the downward arrows across the frontier in Fig. 8. Following Margenau (1984) the hypothesis is that mind-brain interaction is analogous to a probability field of quantum mechanics, which has neither mass nor energy, yet can cause effective action at microsites. More specifically it is proposed that the mental concentration involved in intentions (Figs. 7, 8) or attention (Fig. 4) or planned thinking (Figs. 5, 6) can cause neural events by a process analogous to the probability fields of quantum mechanics. -/- We can ask: what neural events could be appropriate recipients for mental fields that are analogous to quantal probability fields? Already we may have the answer in recent discoveries on the nature of the synaptic mechanism whereby one nerve cell communicates with another. (shrink)

Suppose a theory T entails hypotheses H and $$H'$$, neither of which entails the other. A number of authors have argued that a piece of evidence E “indirectly confirms” H when E confirms either T or $$H'$$. But there has been a protracted and unsettled debate about whether indirect confirmation is a sound inference procedure. Skeptics argue that the procedure employs conditions of confirmation that jointly lead to absurdity. Proponents argue that this criticism is unfounded or that its import is (...) exaggerated. I will argue that no side has the story quite right, and some have the story quite wrong. Indirect confirmation, as characterized above, is unsound, and a good chunk of this paper will be concerned with showing why most extant defenses of the procedure err. On the other hand, when certain probabilistic (in)dependence relations hold between T, H, and $$H'$$, indirect confirmation can work, for reasons that trace back to Reichenbach’s principle of the common cause. I illustrate these matters with some contemporary and historical examples, with a particular focus on Kepler’s use of data about mars’s elliptical orbit to justify a claim about earth’s. (shrink)

Political conspiracy theories—e.g., unsupported beliefs about the nefarious machinations of one’s cunning, powerful, and evil opponents—are adopted enthusiastically by a great many people of widely varying political orientations. In many cases, these theories posit that there exists a small group of individuals who have intentionally but secretly acted to cause economic problems, political strife, and even natural disasters. This group is often held to exist “in the shadows,” either because its membership is unknown, or because “the real nature” of its (...) members’ allegiances, motives, and methods has been concealed from the public at large. Paradigmatic examples of these political conspiracy theories include anti-Semitic beliefs of the sort associated with The Protocols of the Elder of Zion, the “Red Scare” of the 1950s, claims about the “New World Order,” and many others. -/- Why do these theories attract so many adherents? In this essay, I’ll attempt to spread some light on this issue by applying Kahneman and Tversky’s highly influential work on reasoning under uncertainty. I’ll proceed by first providing a brief introduction to Kahneman and Tversky’s work on reasoning under uncertainty, and the way in which this relates to standard economic and philosophic accounts of rational behavior, as well as philosophical ideas about the role of intuition. Next, I’ll move onto some specific interconnected aspects of this work that are relevant to understanding conspiracy theories, including errors involving probabilistic reasoning (“Prospect Theory”), those involving the inappropriate use of heuristics, and those related to the “framing” of certain outcomes as losses from a baseline. This essay will conclude by making two related points. First, some of the most important reasoning errors committed by adherents of conspiracy theories are errors that many of us regularly commit. Given that self-awareness of these errors provides only minimal protection from committing them, this suggests that many of use may be more vulnerable to conspiratorial reasoning than we may like to believe. Second, in the light of this danger, I will outline a few steps that might be taken to help inoculate ourselves against the appeal of these theories, and to help respond to the conspiratorial arguments of others. (shrink)

Pharmacogenetics and pharmacogenomics are related facets of cutting edge therapeutic research in a field that relates pharmacological properties to the genetic characteristics of human beings. An optimistic interpretation suggests that “One-Size-Fits-All” therapeutics, whose effects can only be predicted in probabilistic terms, will give way eventually to individual tailor-made therapies with entirely predictable properties in each patient. Yet the concept of anticipating individual pharmacotherapeutic response appears to disregard some of the fundamental limitations of causal understanding in the biological world of (...) structure–action relationships. It is not simply a problem of confronting complexity – which might be overcome in time with advances in biotechnology and computing power – but the inescapable paradox of the genetic characteristics of individuals within the human species. The aleatory process of evolution ensures that with the exception of monozygotic twins, every human being is genetically unique. At the same time there appears to be more in common than divides. Pharmacogenomics provides a climate in which to explore and better understand the variable causal relationships between genetic element, protein and therapeutic or toxic actions, but can only do so in abstraction. Thus␣predictive power may be enhanced but is ultimately constrained by insuperable probabilistic considerations. (shrink)