The overwhelming majority of those who theorize about implicit biases posit that these biases are caused by some sort of association. However, what exactly this claim amounts to is rarely specified. In this paper, I distinguish between different understandings of association, and I argue that the crucial senses of association for elucidating implicit bias are the cognitive structure and mental process senses. A hypothesis is subsequently derived: if associations really underpin implicit biases, then implicit biases should be modulated by counterconditioning (...) or extinction but should not be modulated by rational argumentation or logical interventions. This hypothesis is false; implicit biases are not predicated on any associative structures or associative processes but instead arise because of unconscious propositionally structured beliefs. I conclude by discussing how the case study of implicit bias illuminates problems with popular dual-process models of cognitive architecture. (shrink)

This chapter presents a typology of the different kinds of inductive inferences we can draw from our evidence, based on the explanatory relationship between evidence and conclusion. Drawing on the literature on graphical models of explanation, I divide inductive inferences into (a) downwards inferences, which proceed from cause to effect, (b) upwards inferences, which proceed from effect to cause, and (c) sideways inferences, which proceed first from effect to cause and then from that cause to an additional effect. I further (...) distinguish between direct and indirect forms of downwards and upwards inferences. I then show how we can subsume canonical forms of inductive inference mentioned in the literature, such as inference to the best explanation, enumerative induction, and analogical inference, under this typology. Along the way, I explore connections with probability and confirmation, epistemic defeat, the relation between abduction and enumerative induction, the compatibility of IBE and Bayesianism, and theories of epistemic justification. (shrink)

In this paper, I argue that theories of perception that appeal to Helmholtz’s idea of unconscious inference (“Helmholtzian” theories) should be taken literally, i.e. that the inferences appealed to in such theories are inferences in the full sense of the term, as employed elsewhere in philosophy and in ordinary discourse. -/- In the course of the argument, I consider constraints on inference based on the idea that inference is a deliberate acton, and on the idea that inferences (...) depend on the syntactic structure of representations. I argue that inference is a personal-level but sometimes unconscious process that cannot in general be distinguished from association on the basis of the structures of the representations over which it’s defined. I also critique arguments against representationalist interpretations of Helmholtzian theories, and argue against the view that perceptual inference is encapsulated in a module. (shrink)

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

The following quotation from Rosenbaum (1995) expresses a commonly held view about the problem of potential confounders, and how they can be dealt with. (We will take a “confounder” of treatment and response to be a variable that is a cause of both treatment and response.).

How is that when scientists need some piece of mathematics through which to frame their theory, it is there to hand? What has been called 'the unreasonable effectiveness of mathematics' sets a challenge for philosophers. Some have responded to that challenge by arguing that mathematics is essentially anthropocentric in character, whereas others have pointed to the range of structures that mathematics offers. Otavio Bueno and Steven French offer a middle way, which focuses on the moves that have to be made (...) in both the mathematics and the relevant physics in order to bring the two into appropriate relation. This relation can be captured via the inferential conception of the applicability of mathematics, which is formulated in terms of immersion, inference, and interpretation. In particular, the roles of idealisations and of surplus structure in science and mathematics respectively are brought to the fore and captured via an approach to models and theories that emphasize the partiality of the available information: the partial structures approach. The discussion as a whole is grounded in a number of case studies drawn from the history of quantum physics, and extended to contest recent claims that the explanatory role of certain mathematical structures in scientific practice supports a realist attitude towards them. The overall conclusion is that the effectiveness of mathematics does not seem unreasonable at all once close attention is paid to how it is actually applied in practice. (shrink)

In this book, Reiss argues in favor of a tight fit between evidence, concept and purpose in our causal investigations in the sciences. There is no doubt that the sciences employ a vast array of techniques to address causal questions such as controlled experiments, randomized trials, statistical and econometric tools, causal modeling and thought experiments. But how do these different methods relate to each other and to the causal inquiry at hand? Reiss argues that there is no "gold standard" in (...) settling causal issues against which other methods can be measured. Rather, the various methods of inference tend to be good only relative to certain interpretations of the word "cause", and each interpretation, in turn, helps to address some salient purpose but not others. The main objective of this book is to explore the metaphysical and methodological consequences of this view in the context of numerous cases studies from the natural and social sciences. (shrink)

The aim of this book is to present the fundamental theoretical results concerning inference rules in deductive formal systems. Primary attention is focused on: admissible or permissible inference rules the derivability of the admissible inference rules the structural completeness of logics the bases for admissible and valid inference rules. There is particular emphasis on propositional non-standard logics (primary, superintuitionistic and modal logics) but general logical consequence relations and classical first-order theories are also considered. The book is (...) basically self-contained and special attention has been made to present the material in a convenient manner for the reader. Proofs of results, many of which are not readily available elsewhere, are also included. The book is written at a level appropriate for first-year graduate students in mathematics or computer science. Although some knowledge of elementary logic and universal algebra are necessary, the first chapter includes all the results from universal algebra and logic that the reader needs. For graduate students in mathematics and computer science the book is an excellent textbook. (shrink)

This book deals with a neglected episode in the history of logic and theories of cognition: the way in which conceptions of inference changed during the seventeenth century. The author focuses on the work of Descartes, contrasting his construal of inference as an instantaneous grasp in accord with the natural light of reason, with the Aristotelian view of inference as a discursive process. Gaukroger offers a new interpretation of Descartes`s contribution to the question, revealing it to be (...) a significant advance over humanist and late Scholastic conceptions. He argues that Descartes's account played a pivotal role in the development of our understanding of the nature of inference. (shrink)

Order of information plays a crucial role in the process of updating beliefs across time. In fact, the presence of order effects makes a classical or Bayesian approach to inference difficult. As a result, the existing models of inference, such as the belief-adjustment model, merely provide an ad hoc explanation for these effects. We postulate a quantum inference model for order effects based on the axiomatic principles of quantum probability theory. The quantum inference model explains order (...) effects by transforming a state vector with different sequences of operators for different orderings of information. We demonstrate this process by fitting the quantum model to data collected in a medical diagnostic task and a jury decision-making task. To further test the quantum inference model, a new jury decision-making experiment is developed. Using the results of this experiment, we compare the quantum inference model with two versions of the belief-adjustment model, the adding model and the averaging model. We show that both the quantum model and the adding model provide good fits to the data. To distinguish the quantum model from the adding model, we develop a new experiment involving extreme evidence. The results from this new experiment suggest that the adding model faces limitations when accounting for tasks involving extreme evidence, whereas the quantum inference model does not. Ultimately, we argue that the quantum model provides a more coherent account for order effects that was not possible before. (shrink)

This work has been selected by scholars as being culturally important and is part of the knowledge base of civilization as we know it. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and (...) made generally available to the public. To ensure a quality reading experience, this work has been proofread and republished using a format that seamlessly blends the original graphical elements with text in an easy-to-read typeface. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. (shrink)

Discussions about the nature of essence and about the inference problem for non-Humean theories of nomic modality have largely proceeded independently of each other. In this article I argue that the right conclusions to draw about the inference problem actually depend significantly on how best to understand the nature of essence. In particular, I argue that this conclusion holds for the version of the inference problem developed and defended by Alexander Bird. I argue that Bird’s own argument (...) that this problem is fatal for David Armstrong’s influential theory of the laws of nature but not for dispositional essentialism is seriously flawed. In place of this argument, I develop an argument that whether Bird’s inference problem raises serious difficulties for Armstrong’s theory depends on the answers to substantial questions about how best to understand essence. The key consequence is that considerations about the nature of essence have significant, underappreciated implications for Armstrong’s theory. (shrink)

By a valid inference is here understood an inference that succeeds in its aim to justify its conclusion given that its premisses are already justified. For an inference to be valid it is thus not enough that the sentence asserted in the conclusion is a logical consequence of the sentences asserted in the premisses. A proof is understood as a succession of valid inferences that is closed (i.e. all its assumptions are discharged and all its free variables (...) are bound by some of the inferences). On the other hand, in mathematics the justification of an assertion has traditionally been taken to consist in a proof of it, which gives rise to an explanatory circle.In an attempt to avoid this circle, I have in previous works tried to explain the notion of ground for an assertion without referring to valid inferences. However, it turns out that the resulting notion of ground has unwanted consequences like the notion of proof in the so-called BHK-interpretation of intuitionistic logic. For instance, one is guaranteed a ground or a proof of an implication A → B as soon as there is in fact no ground or proof of A, regardless of whether one really knows this fact, and hence without having a real justification of the assertion of the implication.In the absence of a non-circular explanation of the notions of valid inference and proof, I suggest that we should try to formulate a number of principles of how these two epistemic notions depend on each other. A more careful explanation of the validity of an inference results in what I call a heuristic idea about the validity of inference, which is used as a guide to formulate precise principles. One such principle generalizes Gentzen’s idea that his introduction rules define the meaning of the logical constants. Another principle generalizes a previously noted property of Gentzen’s elimination rules that I have called that of satisfying the inversion principle. It results in a notion that I call non-creativity, which implies validity. (shrink)

Memes are hypothetical cultural units passed on by imitation; although nonbiological, they undergo Darwinian selection like genes. Cognitive study of multimodular human minds undermines memetics: unlike in genetic replication, high-fidelity transmission of cultural information is the exception, not the rule. Constant, rapid 'mutation' of information during communication generates endlessly varied creations that nevertheless adhere to modular input conditions. The sort of cultural information most susceptible to modular processing is that most readily acquired by children, most easily transmitted across individuals, most (...) apt to survive within a culture, most likely to recur in different cultures, and most disposed to cultural variation and elaboration. (shrink)

In Lehrer’s case of the superstitious lawyer, a lawyer possesses conclusive evidence for his client’s innocence, and he appreciates that the evidence is conclusive, but the evidence is causally inert with respect to his belief in his client’s innocence. This case has divided epistemologists ever since Lehrer originally proposed it in his argument against causal analyses of knowledge. Some have taken the claim that the lawyer bases his belief on the evidence as a data point for our theories to accommodate, (...) while others have denied that the lawyer has knowledge, or that he bases his belief on the evidence. In this paper, we move the dialectic forward by way of arguing that the superstitious lawyer genuinely infers his client’s innocence from the evidence. To show that the lawyer’s inference is genuine, we argue in defense of a version of a doxastic construal of the ‘taking’ condition on inference. We also provide a pared-down superstitious lawyer-style case, which displays the key features of the original case without including its complicated and distracting features. But interestingly, although we argue that the lawyer’s belief is based on his good evidence, and is also plausibly doxastically justified, we do not argue that the lawyer knows that his client is innocent. (shrink)

Certain hypotheses cannot be directly confirmed for theoretical, practical, or moral reasons. For some of these hypotheses, however, there might be a workaround: confirmation based on analogical reasoning. In this paper we take up Dardashti, Hartmann, Thébault, and Winsberg’s (in press) idea of analyzing confirmation based on analogical inference Baysian style. We identify three types of confirmation by analogy and show that Dardashti et al.’s approach can cover two of them. We then highlight possible problems with their model as (...) a general approach to analogical inference and argue that these problems can be avoided by supplementing Bayesian update with Jeffrey conditionalization. (shrink)

Some assertions give rise to the acquaintance inference: the inference that the speaker is acquainted with some individual. Discussion of the acquaintance inference has previously focused on assertions about aesthetic matters and personal tastes (e.g. 'The cake is tasty'), but it also arises with reports about how things seem (e.g. 'Tom seems like he's cooking'). 'Seem'-reports give rise to puzzling acquaintance behavior, with no analogue in the previously-discussed domains. In particular, these reports call for a distinction between (...) the specific acquaintance inference (that the speaker is acquainted with a specific individual) and the general acquaintance inference (that the speaker is acquainted with something or other of relevance). We frame a novel empirical generalization -- the specific with stage-level generalization -- that systematizes the observed behavior, in terms of the semantics of the embedded 'like'-clause. We present supporting experimental work, and explain why the generalization makes sense given the evidential role of 'seem'-reports. Finally, we discuss the relevance of this result for extant proposals about the semantics of 'seem'-reports. More modestly, it fills a gap in previous theories by identifying which reports get which of two possible interpretations; more radically, it suggests a revision of the kind of explanation that should be given for the acquaintance behavior in question. (shrink)

Explanationist accounts of rational legal proof view trials as a competition between explanations. Such accounts are often criticized for being underdeveloped. One question in need of further attention is when guilt is proven beyond a reasonable doubt in criminal trials. This article defends an inference to the best explanation -based approach on which guilt is only established BARD if the best guilt explanation in a case is substantially more plausible than any innocence explanation, and there is no good reason (...) to presume that we have overlooked evidence or alternative explanations that could realistically have exonerated the defendant. This is a comparative account, which I argue is better suited for arriving at accurate verdicts than the non-comparative ‘no plausible alternative’ account that many explanationists tacitly assume. Furthermore, this account is not susceptible to the most important arguments against IBE in criminal trials or to arguments against other, non-explanationist interpretations of the BARD standard. I use a case study to illustrate how this account provides meaningful guidance for decision makers in criminal trials. (shrink)

The underconsideration argument against inference to the best explanation and scientific realism holds that scientists are not warranted in inferring that the best theory is true, because scientists only ever conceive of a small handful of theories at one time, and as a result, they may not have considered a true theory. However, antirealists have not developed a detailed alternative account of why explanatory inference nevertheless appears so central to scientific practice. In this paper, I provide new defences (...) against some recent objections to the underconsideration argument, while also developing an account of explanatory inference that both survives these criticisms and does not entail realism. (shrink)

In previous work, we studied four well known systems of qualitative probabilistic inference, and presented data from computer simulations in an attempt to illustrate the performance of the systems. These simulations evaluated the four systems in terms of their tendency to license inference to accurate and informative conclusions, given incomplete information about a randomly selected probability distribution. In our earlier work, the procedure used in generating the unknown probability distribution (representing the true stochastic state of the world) tended (...) to yield probability distributions with moderately high entropy levels. In the present article, we present data charting the performance of the four systems when reasoning in environments of various entropy levels. The results illustrate variations in the performance of the respective reasoning systems that derive from the entropy of the environment, and allow for a more inclusive assessment of the reliability and robustness of the four systems. (shrink)

In this classic work of philosophy, Thilly provides a comprehensive overview of inductive reasoning and its role in scientific inquiry. With clear examples and lucid prose, Thilly's text remains an essential resource for anyone seeking to understand the nature of knowledge and the scientific method. This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work is in the "public domain in the United States of (...) America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant. (shrink)

The Bayesian brain hypothesis, as formalized by the free-energy principle, is ascendant in cognitive science. But, how does the Bayesian brain obtain prior beliefs? Veissière and colleagues argue that sociocultural interaction is one important source. We offer a complementary model in which “interoceptive self-inference” guides the estimation of expected uncertainty both in ourselves and in our social conspecifics.

Some theorists, ranging from W. James to contemporary psychologists, have argued that forgetting is the key to proper functioning of memory. The authors elaborate on the notion of beneficial forgetting by proposing that loss of information aids inference heuristics that exploit mnemonic information. To this end, the authors bring together 2 research programs that take an ecological approach to studying cognition. Specifically, they implement fast and frugal heuristics within the ACT-R cognitive architecture. Simulations of the recognition heuristic, which relies (...) on systematic failures of recognition to infer which of 2 objects scores higher on a criterion value, demonstrate that forgetting can boost accuracy by increasing the chances that only 1 object is recognized. Simulations of the fluency heuristic, which arrives at the same inference on the basis of the speed with which objects are recognized, indicate that forgetting aids the discrimination between the objects' recognition speeds. (shrink)

Several authors have claimed that mechanisms play a vital role in distinguishing between causation and mere correlation in the social sciences. Such claims are sometimes interpreted to mean that without mechanisms, causal inference in social science is impossible. The author agrees with critics of this proposition but explains how the account of how mechanisms aid causal inference can be interpreted in a way that does not depend on it. Nevertheless, he shows that this more charitable version of the (...) account is still unsuccessful as it stands. Consequently, he advances a proposal for shoring up the account, which is founded on the possibility of acquiring knowledge of social mechanisms by linking together norms or practices found in a society. Key Words: causality • social mechanisms • interpretation • anthropology. (shrink)

Originally published in 1952. This book is a critical survey of the views of scientific inference that have been developed since the end of World War I. It contains some detailed exposition of ideas – notably of Keynes – that were cryptically put forward, often quoted, but nowhere explained. Part I discusses and illustrates the method of hypothesis. Part II concerns induction. Part III considers aspects of the theory of probability that seem to bear on the problem of induction (...) and Part IV outlines the shape of this problem and its solution take if transformed by the present approach. (shrink)

There is an important disagreement in contemporary epistemology over the possibility of non-epistemic reasons for belief. Many epistemologists argue that non-epistemic reasons cannot be good or normative reasons for holding beliefs: non-epistemic reasons might be good reasons for a subject to bring herself to hold a belief, the argument goes, but they do not offer any normative support for the belief itself. Non-epistemic reasons, as they say, are just the wrong kind of reason for belief. Other epistemologists, however, argue that (...) there can be cases where non-epistemic reasons directly offer normative support for the beliefs a subject holds. -/- My aim in this paper is to remove an apparent obstacle for the view that there can be non-epistemic normative reasons for belief, by showing that the existence of non-epistemic reasons for belief does not conflict with epistemic standards for the assessment of inference. More specifically, I aim to show that the following principles are compatible: -/- Epistemic Norm of Inference (ENI): Necessarily, for all subjects, S, and inferences, I: I is a good inference for S only if S can gain a (doxastically) epistemically justified belief in I’s conclusion on the basis of I’s premises. -/- Non-Epistemic Reasons for Belief (NERB): Possibly, for some subject, S, reason, R, and belief, B: R is a good (i.e., normative) reason for S to hold B, and R is not an epistemic reason for B. -/- Guidance: For all subjects S, potential reasons R, and beliefs/actions φ: In order for R to count as a normative reason for S to φ, it must be possible for S to take R into account as relevant to the determination of whether S ought to φ. -/- One might naturally think that these principles conflict, for if there are non-epistemic reasons for belief, then they must guide deliberation, and in guiding deliberation, they would violate epistemic standards. The aim of this paper is to show that no such conflict need arise. -/- Section 2 of the paper proceeds to set out the concept of an inference, and to sketch an epistemic framework for the assessment of inferences and arguments. Section 3 sets out the distinction between normative and motivating reasons, and briefly defends the view that there can be non-epistemic reasons for beliefs. Section 4 shows that non-epistemic reasons for belief are compatible with epistemic standards for inference, because any time a reason R is a good non-epistemic reason for a subject S to hold a belief B, there is an epistemically good inference available to S which takes R as a premise and which concludes with the meta-belief that S ought to hold B. So the paper employs a level-connecting principle between normative reasons for φ-ing and epistemic reasons for believing that one ought to φ. The paper ends with clarifications of that level-connecting principle, and responses to three objections. (shrink)

Standards and norms for reasoning function, in part, to manage epistemic risk. Properly used, modal qualifiers like presumably have a role in systematically managing epistemic risk by flagging and tracking type-specific epistemic merits and risks of the claims they modify. Yet, argumentation-theoretic accounts of presumption often define it in terms of modalities of other kinds, thereby failing to recognize the unique risk profile of each. This paper offers a stipulative account of presumption, inspired by Ullmann-Margalit, as an inferentially generated modal (...) qualifier, “presumably, p,” distinguishing it from other, particularly epistemic modalities, e.g., standing commitments, assumptions, assertions, suppositions, hypotheses, and defeasible claims. By avoiding the tranching of inferential instruments of qualitatively different bona fides and risk profiles, this account provides a more accurate risk-rating system that better manages epistemic risk in inference, as well as contributing to the normative theory of the operation of presumption in reasoning and argument. (shrink)