A central question in cognitive research concerns how new properties are generalized to categories. This article introduces a model of how generalizations involve a process of causal inference in which people estimate the likely presence of the new property in individual category exemplars and then the prevalence of the property among all category members. Evidence in favor of this causal‐based generalization (CBG) view included effects of an existing feature’s base rate (Experiment 1), the direction of the causal (...) relations (Experiments 2 and 4), the number of those relations (Experiment 3), and the distribution of features among category members (Experiments 4 and 5). The results provided no support for an alternative view that generalizations are promoted by the centrality of the to‐be‐generalized feature. However, there was evidence that a minority of participants based their judgments on simpler associative reasoning processes. (shrink)

C. B. Martin's finkish cases raise one of the most serious objections to conditional analyses of dispositions. David Lewis's reformed analysis is widely considered the most promising response to the objection. Despite its sophistication, however, the reformed analysis still provokes questions concerning its ability to handle finkish cases. They focus on the applicability of the analysis to 'baseless' dispositions. After sketching Martin's objection and the reformed analysis, I argue that all dispositions have causal bases which the analysis can (...) unproblematically invoke. (shrink)

Even though the talk of causal bases is commonplace in traditional and contemporary discussions about dispositions, the concept of causal bases has never been systematically investigated. This paper aims to fill this gap by developing the causal-grounding account. This account takes two roles as definitory for causal bases. First, causal bases are possible causes of disposition manifestations. Second, causal bases are metaphysical grounds of disposition instantiations. In this paper, we (...) show that the causal-grounding account (CGA) achieves crucial distinctions (for example between causal bases and manifestation conditions), captures relevant traditional features of causal bases, and can be invoked to support the causal efficacy of disposition instantiations. At the same time, CGA does not require that causal bases have to be categorical or intrinsic. This, in turn, allows us to remain neutral concerning fundamental properties, the existence of dispositional or extrinsic causal bases, multi-track dispositions, and the reducibility of dispositions. This neutrality grants the suitability of our account for different philosophical projects and discussions. (shrink)

Ontologies are some of the most central constructs in today's large plethora of knowledge technologies, namely in the context of the semantic web. As their coinage indicates, they are direct heirs to the ontological investigations in the long Western philosophical tradition, but it is not easy to make bridges between them. Contemporary ontological commitments often take causality as a central aspect for the ur-segregation of entities, especially in scientific upper ontologies; theories of causality and philosophical ontological investigations often go hand-in-hand, (...) and were essentially inseparable in medieval thought. This constitutes the foundation for a bridge, and this article analyzes the causality-based ontology of the late medieval philosopher Dietrich of Freiberg from the viewpoint of today's upper-ontology engineering. In this bridging attempt, it offers a translation into English of the first part of Dietrich's De origine (abbreviated title) that is a compromise between traditional scholarly translations of medieval Latin philosophical texts and contemporary ontology. (shrink)

The causal view of categories assumes that categories are represented by features and their causal relations. To study the effect of causal knowledge on categorization, researchers have used Bayesian causal models. Within that framework, categorization may be viewed as dependent on a likelihood computation (i.e., the likelihood of an exemplar with a certain combination of features, given the category's causal model) or as a posterior computation (i.e., the probability that the exemplar belongs to the category, (...) given its features). Across three experiments, in combination with computational modeling, we offer evidence that categorization is better accounted for by assuming that people compute posteriors and not likelihoods, though both probabilities are closely related. This result contrasts with existing analyses of causal-based categorization, which assume that likelihood computations give a good approximation of human judgments. We also find that people are able to compute likelihoods in a closely related task that elicits judgments of consistency rather than category membership judgments. Our analyses show that people do use causal probabilistic information as prescribed by a Bayesian model but that they flexibly compute likelihoods or posteriors depending on the task. We discuss our results in relation to the relevant literature on the topic. (shrink)

In this paper, I distinguish two often-conflated theses—the thesis that all dispositions are intrinsic properties and the thesis that the causal bases of all dispositions are intrinsic properties—and argue that the falsity of the former does not entail the falsity of the latter. In particular, I argue that extrinsic dispositions are a counterexample to first thesis but not necessarily to the second thesis, because an extrinsic disposition does not need to include any extrinsic property in its causal (...) basis. I conclude by drawing some general lessons about the nature of dispositions and their relation to their causal bases. (shrink)

The target article developed a dynamic systems framework that viewed the causal basis of emotion as a self-organizing process giving rise to cognitive appraisal concurrently. Commentators on the article evaluated this framework and the principles and mechanisms it incorporated. They also suggested additional principles, mechanisms, modeling strategies, and phenomena related to emotion and appraisal, in place of or extending from those already proposed. There was general agreement that nonlinear causal processes are fundamental to the psychology and neurobiology of (...) emotion. (shrink)

LEMKE has recently taken issue (see ANALYSIS 46.3, June 1986, pp. 138-44) with my claim that no counterfactual causal account of the basing relation is plausible (see ANALYSIS 45.3, June 1985, pp. 153-8). Intuitively, a counterfactual causal account claims that belief is based on evidence if and only if the evidence either causes the belief or would have caused it had the actual cause been absent. This intuitive formulation accounts only for counterfactual causes of level one: events which (...) would have been a cause had only the actual cause been absent. As I argued, there is as much support for allowing counterfactual causes having a higher cardinality: events which would have been a cause had the actual cause and some other counterfactual causes been absent. (shrink)

The epistemic basing relation is the relation which must hold between a person's belief and the adequate reasons for holding that belief if the belief is to be epistemically justified by those reasons. Although the basing relation is a fundamental component of any adequate theory of epistemic justification, it has received scant attention in the literature. In this paper, I propose a novel causal analysis of the basing relation, one which helps to characterize an intemalist element which, I shall (...) argue, is required of any successful account of epistemic justification, and which confirms current trends away from coherentist and reliabilist theories of justification. (shrink)

Causal claims in biomedical contexts are ubiquitous albeit they are not always made explicit. This paper addresses the question of what causal claims mean in the context of disease. It is argued that in medical contexts causality ought to be interpreted according to the epistemic theory. The epistemic theory offers an alternative to traditional accounts that cash out causation either in terms of “difference-making” relations or in terms of mechanisms. According to the epistemic approach, causal claims tell (...) us about which inferences (e.g., diagnoses and prognoses) are appropriate, rather than about the presence of some physical causal relation analogous to distance or gravitational attraction. It is shown that the epistemic theory has important consequences for medical practice, in particular with regard to evidence-based causal assessment. (shrink)

Kerry et al. criticize our discussion of causal knowledge in evidence-based medicine (EBM) and our assessment of the relevance of their dispositionalist ontology for EBM. Three issues need to be addressed in response: (1) problems concerning transfer of causal knowledge across heterogeneous contexts; (2) how predictions about the effects of individual treatments based on population-level evidence from RCTs are fallible; and (3) the relevance of ontological theories like dispositionalism for EBM.

With the advent of evolutionary developmental research, or EvoDevo, there is hope of discovering the roles that the genetic bases of development play in morphological evolution. Studies in EvoDevo span several levels of organismal organization. Low-level studies identify the ultimate genetic changes responsible for morphological variation and diversity. High-level studies of development focus on how genetic differences affect the dynamics of gene networks and epigenetic interactions to modify morphology. Whereas an increasing number of studies link independent acquisition of homoplastic (...) or convergent morphologies to similar changes in the genomes, homoplasies are not always found to have identical low-level genetic underpinnings. This suggests that a combination of low- and high-level approaches may be useful in understanding the relationship between genetic and morphological variation. Therefore, as an empirical and conceptual framework, we propose the causality horizon to signify the lowest level that allows linking homoplastic morphologies to similar changes in the development. A change in a system below the causality horizon cannot be generalized. In more concrete terms, homoplastic morphologies cannot be reduced to the same change in gene regulation when that change occurs below the causality horizon; rather, a higher-level mechanism should be identified. (shrink)

Abstract In this paper I consider an easier-to-read and improved to a certain extent version of the causal chance-based analysis of counterfactuals that I proposed and argued for in my A Theory of Counterfactuals. Sections 2, 3 and 4 form Part I: In it, I survey the analysis of the core counterfactuals (in which, very roughly, the antecedent is compatible with history prior to it). In section 2 I go through the three main aspects of this analysis, which are (...) the following. First, it is a causal analysis, in that it requires that intermediate events to which the antecedent event is not a cause be preserved in the main truth-condition schema. Second, it highlights the central notion to the semantics of counterfactuals on the account presented here -- the notion of the counterfactual probability of a given counterfactual, which is the probability of the consequent given the following: the antecedent, the prior history, and the preserved intermediate events. Third, it considers the truth conditions for counterfactuals of this sort as consisting in this counterfactual probability being higher than a threshold. In section 3, I re-formulate the analysis of preservational counterfactuals in terms of the notion of being a cause, which ends up being quite compact. In section 4 I illustrate this analysis by showing how it handles two examples that have been considered puzzling – Morgenbesser's counterfactual and Edgington's counterfactual. Sections 5 and on constitute Part II: Its main initial thrust is provided in section 5, where I present the main lines of the extension of the theory from the core counterfactuals (analyzed in part I) to counterfactuals (roughly) whose antecedents are not compatible with their prior history. In this part II, I elaborate on counterfactuals that don't belong to the core, and more specifically on so-called reconstructional counterfactuals (as opposed to the preservational counterfactuals, which constitute the core counterfactual-type). The heart of the analysis is formulated in terms of processes leading to the antecedent (event/state), and more specifically in terms of processes likely to have led to the antecedent, a notion which is analyzed entirely in terms of chance. It covers so-called reconstructional counterfactuals as opposed to the core, so-called preservational counterfactuals, which are analyzed in sections 2 and 3 of part I. The counterfactual probability of such reconstructional counterfactuals is determined via the probability of possible processes leading to the antecedent weighed, primarily and roughly, by the conditional probability of the antecedent given such process: The counterfactual probability is thus, very roughly, a weighted sum for all processes most likely to have led to the antecedent, diverging at a fixed time. In section 6 I explain and elaborate further on the main points in section 5. In section 7 I illustrate the reconstructional analysis. I specify counterfactuals which are so-called process-pointers, since their consequent specifies stages in processes likely to have led to their antecedent. I argue that so-called backtracking counterfactuals are process-pointers counterfactuals, which fit into the reconstructional analysis, and do not call for a separate reading. I then illustrate cases where a speaker unwittingly employs a certain counterfactual while charitably construable as intending to assert (or ‘having in mind’) another. Here I also cover the issue of how to construe what one can take as back-tracking counterfactuals, or counterfactuals of the reconstructional sort, and more specifically, which divergence point they should be taken as alluding to (prior to which the history is held fixed). Some such cases also give rise to what one can take as a dual reading of a counterfactual between preservational and reconstructional readings. Such cases may yield an ambiguity, where in many cases one construal is dominant. In section 8 I illustrate the analysis by applying it to the famous Bizet-Verdi counterfactuals. This detailed analysis of counterfactuals (designed for the indeterministic case) has three main distinctive elements: its being chance-based, its causal aspect, and the use it makes of processes most likely to have led to the antecedent-event. This analysis is couched in a very different conceptual base from, and is an alternative account to, analyses in terms of the standard notion of closeness or distance of possible worlds, which is the main feature of the Stalnaker-Lewis-type analyses of counterfactuals. This notion of closeness or distance plays no role whatsoever in the analysis presented here. (This notion of closeness has been left open by Stalnaker, and to significant extent also by Lewis's second account.) . (shrink)

Modern fundamental science tends to avoid the principle of physical causality and realism, replacing it with heuristically postulated and separated mathematical constructions that impose their own rules before being adjusted to measurement results. While it is officially accepted as the single possible kind of rigorous knowledge, we argue that another, explicitly extended kind of science can provide the causally complete picture of reality avoiding the glaring gaps, growing problems and persisting stagnation of the artificially reduced knowledge paradigm. The logic of (...) science development and especially its current state call for the urgently needed transition to the extended, causally complete kind of knowledge and related sustainable progress at superior creativity levels of self-aware, reason-based society. (shrink)

Korcz argues that deontological considerations support this view. According to him, our practice of praising and blaming people for the epistemic appropriateness of their beliefs provides us with good reason to think that meta-beliefs can establish basing relations independently of any causal relation. Korcz writes.

It is argued that in deterministic contexts evidence for causal relations states whether a boundary condition makes a difference or not to a phenomenon. In order to substantiate the analysis, I show that this difference/indifference making is the basic type of evidence required for eliminative induction in the tradition of Francis Bacon and John Stuart Mill. To this purpose, an account of eliminative induction is proposed with two distinguishing features: it includes a method to establish the causal irrelevance (...) of boundary conditions by means of indifference making, which is called strict method of agreement, and it introduces the notion of a background against which causal statements are evaluated. Causal statements thus become three-place-relations postulating the relevance or irrelevance of a circumstance C to the examined phenomenon P with respect to a background B of further conditions. To underline the importance of evidence in terms of difference/indifference making, I sketch two areas, in which eliminative induction is extensively used in natural and engineering sciences. One concerns exploratory experiments, the other engineering design methods. Given that a method is discussed that has been used for centuries, I make no claims to novelty in this paper, but hope that the combined discussion of several topics that are still somewhat underrepresented in the philosophy of science literature is of some merit. (shrink)

A theory of causality based upon physical processes is developed. Causal processes are distinguished from pseudo-processes by means of a criterion of mark transmission. Causal interactions are characterized as those intersections of processes in which the intersecting processes are mutually modified in ways which persist beyond the point of intersection. Causal forks of three kinds (conjunctive, interactive, and perfect) are introduced to explicate the principle of the common cause. Causal forks account for the production of order (...) and modifications of order; causal processes account for the propagation of causal influence. (shrink)

Using the flexibility of recently developed methods for causal discovery based on Boolean satisfiability solvers, we encode a variety of assumptions that weaken the Faithfulness assumption. The encoding results in a number of SAT-based algorithms whose asymptotic correctness relies on weaker conditions than are standardly assumed. This implementation of a whole set of assumptions in the same platform enables us to systematically explore the effect of weakening the Faithfulness assumption on causal discovery. An important effect, suggested by simulation (...) results, is that adopting weaker assumptions greatly alleviates the problem of conflicting constraints and substantially shortens solving time. As a result, SAT-based causal discovery is potentially more scalable under weaker assumptions. (shrink)

This thesis provides an account of acquaintance with abstract objects. The notion of acquaintance is integral to theorising on reference and singular thought, since it is generally taken to be the relation that must exist between a subject and an object, in order for the subject to refer to, and entertain singular thoughts about the object. The most common way of understanding acquaintance is as a form of causal connection. However, this implies a problem. We seem to be able (...) to refer and have singular thoughts about abstract objects. But given that abstract objects are causally inert, this would mean that we are unable to become acquainted with them. This problem shall be the focus of this thesis. I first argue that these traditional causal interpretations of acquaintance are lacking. Instead, I show that acquaintance is dependent to some degree on factors internal to the subject, namely the skills that they possess. From doctors to sommeliers to mathematicians (and possibly even philosophers!) – these subjects seem to succeed in becoming acquainted with certain objects precisely in virtue of their respective skills. Thus, building off from Evans’ The Varieties of Reference, I present a novel account of acquaintance, which I term as Skill-based Acquaintance (SBA). On SBA, a subject is said to be acquainted with an object when they possess discriminating knowledge of that object, gained through the use of their capacities and skills. The SBA account is applied to virtual (Ch.3), fictional (Ch.4), and mathematical objects (Ch.5), as well as God (Ch.6). SBA is successful in explaining how subjects can indeed become acquainted with these problematic categories of objects - some of which are abstract – thus being able to refer and entertain singular thoughts about them. Overall, then, SBA is shown to have greater explanatory power than competing accounts and should thus be preferred. (shrink)

Fusion validity assessments employ structural equation models to investigate whether an existing scale functions in accordance with theory. Fusion validity parallels criterion validity by depending on correlations with non-scale variables but differs from criterion validity because it requires at least one theorized effect of the scale, and because both the scale and scaled-items are included in the model. Fusion validity, like construct validity, will be most informative if the scale is embedded in as full a substantive context as theory permits. (...) Appropriate scale functioning in a comprehensive theoretical context greatly enhances a scale’s validity. Inappropriate scale functioning questions the scale but the scale’s theoretical embedding encourages detailed diagnostic investigations potentially challenging specific items, the procedure used to calculate scale values, or aspects of the theory, but also possibly recommends incorporating additional items into the scale. The scaled items should have survived prior content and methodological assessments but the items may or may not reflect a common factor because items having diverse causal backgrounds can sometimes fuse to form a unidimensional entity. Though items reflecting a common cause can be assessed for fusion validity, we illustrate fusion validity in the more challenging context of a scale comprised of diverse items and embedded in a complicated theory. Specifically we consider the Leadership scale from the Alberta Context Tool with care aides working in Canadian long-term care homes. (shrink)

Accurate identification of legal provisions is crucial for adjudicating criminal cases, but the complexity and volume of legal texts pose significant challenges for legal professionals. This paper addresses these challenges by introducing a novel legal provision selection framework that transforms the task from a simple classification problem into a sophisticated system combining semantic matching with causal relationship learning. Leveraging large language models, our approach enhances the understanding and interpretation of legal language, by extracting nuanced features from legal texts for (...) deeper contextual comprehension. Additionally, integrating causal learning aligns with the inherent causality in legal reasoning, improving model interpretability and mitigating data bias. Our method demonstrates superior accuracy and robustness through extensive experiments on the CAIL2018 dataset and its subsets. This research significantly advances legal AI applications, promoting efficiency and fairness in the criminal justice system by providing precise and reliable legal provision selection. (shrink)

Unmeasured confounding is an important threat to the validity of observational studies. A common way to deal with unmeasured confounding is to compute bounds for the causal effect of interest, that is, a range of values that is guaranteed to include the true effect, given the observed data. Recently, bounds have been proposed that are based on sensitivity parameters, which quantify the degree of unmeasured confounding on the risk ratio scale. These bounds can be used to compute an E-value, (...) that is, the degree of confounding required to explain away an observed association, on the risk ratio scale. We complement and extend this previous work by deriving analogous bounds, based on sensitivity parameters on the risk difference scale. We show that our bounds can also be used to compute an E-value, on the risk difference scale. We compare our novel bounds with previous bounds through a real data example and a simulation study. (shrink)

Causal modelling provides a powerful set of tools for identifying causal structure from observed correlations. It is well known that such techniques fail for quantum systems, unless one introduces 'spooky' hidden mechanisms. Whether one can produce a genuinely quantum framework in order to discover causal structure remains an open question. Here we introduce a new framework for quantum causal modelling that allows for the discovery of causal structure. We define quantum analogues for core features of (...) classical causal modelling techniques, including the causal Markov condition and faithfulness. Based on the process matrix formalism, this framework naturally extends to generalised structures with indefinite causal order. (shrink)

Causality in Macroeconomics examines causality while taking macroeconomics seriously. A pragmatic and realistic philosophy is joined to a macroeconomic foundation that refines Herbert Simon's well-known work on causal order to make a case for a structural approach to causality. The structural approach is used to understand modern rational expectations models, regime switching models, Granger causality, vector autoregressions, the Lucas critique, and concept exogeneity. Techniques of causal inference based on patterns of stability and instability in the face of identified (...) regime changes are developed and illustrated in two empirical case studies. (shrink)

In ‘An argument against causal decision theory’, Jack Spencer shows that standard formulations of causal decision theory run afoul of his Guaranteed Principle. In the sequential choice problem he employs to make this case, the transgression stems from an awkward discrepancy between how causalists typically value present vs future acts. This note suggests a version of causal decision theory that avoids this incongruity and so respects the Guaranteed Principle in Spencer’s problem. However, this formulation, and hence symmetric (...) appraisal of present and future acts, is also shown to be insufficient to secure causalist satisfaction of the Guaranteed Principle in general. (shrink)

The causal nature of evolution is one of the central topics in the philosophy of biology. The issue concerns whether equations used in evolutionary genetics point to some causal processes or purely phenomenological patterns. To address this question the present article builds well-defined causal models that underlie standard equations in evolutionary genetics. These models are based on minimal and biologically plausible hypotheses about selection and reproduction, and generate statistics to predict evolutionary changes. The causal reconstruction of (...) the evolutionary principles shows adaptive evolution as a genuine causal process, where fitness and selection are both causes of evolution. 1 Introduction2 The Philosophical Puzzle3 Causal Models4 Causal Foundations of Evolutionary Genetics4.1 Univariate quantitative genetics model4.1.1 The causal graph4.1.2 Structural equations4.1.3 Deriving evolutionary transition functions4.2 One-locus population genetics model5 Evolution as a Causal Process5.1 Selection as a causal process5.2 Causes of evolutionary change6 Conclusion. (shrink)

The basis of Islamic alchemy and matter theory is found in the works of Jābir ibn Ḥayyān (d. 200/815). Jābir developed an element theory similar to Aristotle’s system. Still, he interpreted matter and substance differently by transferring the basis of the theory from elements to qualities. In Jābir’s system, qualities are more often expressed by the term “natures” (ṭabā’iʻ). In Jābir’s thought, four na- tures precede the four elements, and due to the combination of two different natures with the sub- (...) stance each time, four distinct elements with different qualities occur. In Jābir, the “primary bodies” of the natural world are no longer the four Empedoclean elements but the “four natures”; air, water, earth, and fire are made up of these natures. Thus, Jābir gave the four primary Aristotelian qualities the role of genuine elements by making them tangible, independent, and corporeal entities. According to Jābir, the operation of transforming (transmutation) of ajsād (‘bodies’) such as iron, copper, tin, and lead, which is the primary purpose of the Art of alchemy, into silver and gold is carried out within the framework of the science of mīzān. The core of this transformation is based on an idea of causality in which the four natures and their specific proportions and measures are at the center. With the idea of causality that allows chemical transformation, Jābir also succeeded in extending the possibility of transformation in alchemy from the inorganic world to the organic world to an extensive range of entities. This study will discuss Jābir’s thoughts on body, substance, and experimental causality by ex- amining Jābir’s corpus through primary sources. (shrink)

In this volume, Ozgur Koca offers a comprehensive survey of Islamic accounts of causality and freedom from the medieval to the modern era, as well as contemporary relevance. His book is an invitation for Muslims and non-Muslims to explore a rich, but largely forgotten, aspect of Islamic intellectual history. Here, he examines how key Muslim thinkers, such as Ibn Sina, Ghazali, Ibn Rushd, Ibn Arabi, Suhrawardi, Jurjani, Mulla Sadra and Nursi, among others, conceptualized freedom in the created order as an (...) extension of their perception of causality. Based on this examination, Koca identifies and explores some of the major currents in the debate on causality and freedom. He also discusses the possible implications of Muslim perspectives on causality for contemporary debates over religion and science. (shrink)

Information about the structure of a causal system can come in the form of observational data—random samples of the system's autonomous behavior—or interventional data—samples conditioned on the particular values of one or more variables that have been experimentally manipulated. Here we study people's ability to infer causal structure from both observation and intervention, and to choose informative interventions on the basis of observational data. In three causal inference tasks, participants were to some degree capable of distinguishing between (...) competing causal hypotheses on the basis of purely observational data. Performance improved substantially when participants were allowed to observe the effects of interventions that they performed on the systems. We develop computational models of how people infer causal structure from data and how they plan intervention experiments, based on the representational framework of causal graphical models and the inferential principles of optimal Bayesian decision‐making and maximizing expected information gain. These analyses suggest that people can make rational causal inferences, subject to psychologically reasonable representational assumptions and computationally reasonable processing constraints. (shrink)

Causal reasoning is an aspect of learning, reasoning, and decision-making that involves the cognitive ability to discover relationships between causal relata, learn and understand these causal relationships, and make use of this causal knowledge in prediction, explanation, decision-making, and reasoning in terms of counterfactuals. Can we fully automate causal reasoning? One might feel inclined, on the basis of certain groundbreaking advances in causal epistemology, to reply in the affirmative. The aim of this paper is (...) to demonstrate that one still has good skeptical grounds for resisting any conclusions in favour of the automation of causal reasoning. If by causal reasoning is meant the entirety of the process through which we discover causal relationships and make use of this knowledge in prediction, explanation, decision-making, and reasoning in terms of counterfactuals, then one relies besides on tacit knowledge, as might be constituted by or derived from the epistemic faculty virtues and abilities of the causal reasoner, the value systems and character traits of the causal reasoner, the implicit knowledge base available to the causal reasoner, and the habits that sustain our causal reasoning practices. While certain aspects of causal reasoning may be axiomatized and formalized and algorithms may be implemented to approximate causal reasoning, one has to remain skeptical about whether causal reasoning may be fully automated. This demonstration will involve an engagement with Meno’s Paradox. (shrink)

This paper presents a drastically revised version of the theory of causality, based on analyses of causal processes and causal interactions, advocated in Salmon (1984). Relying heavily on modified versions of proposals by P. Dowe, this article answers penetrating objections by Dowe and P. Kitcher to the earlier theory. It shows how the new theory circumvents a host of difficulties that have been raised in the literature. The result is, I hope, a more satisfactory analysis of physical causality.

Event-causal libertarians maintain that an agent’s freely bringing about a choice is reducible to states and events involving him bringing about the choice. Agent-causal libertarians demur, arguing that free will requires that the agent be irreducibly causally involved. Derk Pereboom and Meghan Griffith have defended agent-causal libertarianism on this score, arguing that since on event-causal libertarianism an agent’s contribution to his choice is exhausted by the causal role of states and events involving him, and since (...) these states and events leave it open which decision he will make, he does not settle which decision occurs, and thus “disappears.” My aim is to explain why this argument fails. In particular, I demonstrate that event-causal libertarians can dismantle the argument by enriching the reductive base in their analysis of free will to include a state that plays the functional role of the self-determining agent and with which the agent is identified. (shrink)

A new approach for defining causality and such related notions as degree of responsibility, degrees of blame, and causal explanation. Causality plays a central role in the way people structure the world; we constantly seek causal explanations for our observations. But what does it even mean that an event C "actually caused" event E? The problem of defining actual causation goes beyond mere philosophical speculation. For example, in many legal arguments, it is precisely what needs to be established (...) in order to determine responsibility. The philosophy literature has been struggling with the problem of defining causality since Hume. In this book, Joseph Halpern explores actual causality, and such related notions as degree of responsibility, degree of blame, and causal explanation. The goal is to arrive at a definition of causality that matches our natural language usage and is helpful, for example, to a jury deciding a legal case, a programmer looking for the line of code that cause some software to fail, or an economist trying to determine whether austerity caused a subsequent depression. Halpern applies and expands an approach to causality that he and Judea Pearl developed, based on structural equations. He carefully formulates a definition of causality, and building on this, defines degree of responsibility, degree of blame, and causal explanation. He concludes by discussing how these ideas can be applied to such practical problems as accountability and program verification. Technical details are generally confined to the final section of each chapter and can be skipped by non-mathematical readers. (shrink)