How Probabilistic Causation Can Account for the Use of Mechanistic Evidence

In a recent article in this journal, Federica Russo and Jon Williamson argue that an analysis of causality in terms of probabilistic relationships does not do justice to the use of mechanistic evidence to support causal claims. I will present Ronald Giere’s theory of probabilistic causation, and show that it can account for the use of mechanistic evidence (both in the health sciences—on which Russo and Williamson focus—and elsewhere). I also review some other probabilistic theories of causation (of Suppes, Eells, and Humphreys) and show that they cannot account for the use of mechanistic evidence. I argue that these theories are also inferior to Giere’s theory in other respects.     

A Computational Theory of Learning Causal Relationships

I present a cognitive model of the human ability to acquire causal relationships. I report on experimental evidence demonstrating that human learners acquire accurate causal relationships more rapidly when training examples are consistent with a general theory of causality. This article describes a learning process that uses a general theory of causality as background knowledge. The learning process, which I call theory-driven learning (TDL), hypothesizes causal relationships consistent both with observed data and the general theory of causality. TDL accounts for data on both the rate at which human learners acquire causal relationships, and the types of causal relationships they acquire. Experiments with TDL demonstrate the advantage of TDL for acquiring causal relationships over similarity-based approaches to learning: Fewer examples are required to learn an accurate relationship.     

Interpreting Causality in the Health Sciences

We argue that the health sciences make causal claims on the basis of evidence both of physical mechanisms, and of probabilistic dependencies. Consequently, an analysis of causality solely in terms of physical mechanisms or solely in terms of probabilistic relationships, does not do justice to the causal claims of these sciences. Yet there seems to be a single relation of cause in these sciences—pluralism about causality will not do either. Instead, we maintain, the health sciences require a theory of causality that unifies its mechanistic and probabilistic aspects. We argue that the epistemic theory of causality provides the required unification.     

Stochastic independence,causal independence,and shieldability

The aim of the paper is to explicate the concept of causal independence between sets of factors and Reichenbach's screening-off-relation in probabilistic terms along the lines of Suppes' probabilistic theory of causality (1970). The probabilistic concept central to this task is that of conditional stochastic independence. The adequacy of the explication is supported by proving some theorems about the explicata which correspond to our intuitions about the explicanda.I am indebted to the referee for his most valuable report and to the editor for taking more trouble than usual, I fear.     

Probabilistic Causation in Branching Time

A probabilistic and counterfactual theory of causality is developed within the framework of branching time. The theory combines ideas developed by James Fetzer, Donald Nute, Patrick Suppes, Ming Xu, John Pollock, David Lewis and Mellor among others.     

Deviant Causal Chains and Hallucinations: A Problem for the Anti-causalist

The causal theory of perception is opposed by anti-causalists, who claim that the notion of causality is not part of our ordinary concept of perception, and sometimes raise the possibility of deviant causal chain counter-examples in an attempt to undermine the causal theory. I argue that such examples in fact cause more difficulties for anti-causalist accounts of perception. Anti-causalists are unable to explain how the examples can be recognized as deviant, and why such cases are incompatible with perception. They have a general problem in providing a satisfactory account of hallucination. A comparison with certain complex cases of illusion suggests that our grasp of the concept of perception does indeed involve some kind of understanding of the kinds of causal chains appropriate to genuine perception.     

The causal explanatory functions of medical diagnoses

Diagnoses in medicine are often taken to serve as explanations of patients’ symptoms and signs. This article examines how they do so. I begin by arguing that although some instances of diagnostic explanation can be formulated as covering law arguments, they are explanatory neither in virtue of their argumentative structures nor in virtue of general regularities between diagnoses and clinical presentations. I then consider the theory that medical diagnoses explain symptoms and signs by identifying their actual causes in particular cases. While I take this to be largely correct, I argue that for a diagnosis to function as a satisfactory causal explanation of a patient’s symptoms and signs, it also needs to be supplemented by understanding the mechanisms by which the identified cause produces the symptoms and signs. This mechanistic understanding comes not from the diagnosis itself, but rather from the theoretical framework within which the physician operates.     

A generalized probabilistic theory of causal relevance

I advance a new theory of causal relevance, according to which causal claims convey information about conditional probability functions. This theory is motivated by the problem of disjunctive factors, which haunts existing probabilistic theories of causation. After some introductory remarks, I present in Section 3 a sketch of Eells's (1991) probabilistic theory of causation, which provides the framework for much of the discussion. Section 4 explains how the problem of disjunctive factors arises within this framework. After rejecting three proposed solutions, I offer in Section 6 a new approach to causation that avoids the problem. Decision-theoretic considerations also support the new approach. Section 8 develops the consequences of the new theory for causal explanation. The resulting theory of causal explanation incorporates the new insights while respecting important work on scientific explanation by Salmon (1971), Railton (1981), and Humphreys (1989). My conclusions are enumerated in Section 9.I would like to thank Nuel Belnap, John Earman, Richard Gale, Paul Humphreys, Satish Iyengar, Wes Salmon, and two anonymous referees for comments and discussion. I am also indebted to the members of an audience at the Center for Philosophy of Science at the University of Pittsburgh, where some of the ideas contained in this paper were presented.     

On the edge of a paradigm shift: Quantum nonlocality and the breakdown of peaceful coexistence

I present a thought experiment in quantum mechanics and tease out some of its implications for the doctrine of “peaceful coexistence”, which, following Shimony, I take to be the proposition that quantum mechanics does not force us to revise or abandon the relativistic picture of causality. I criticize the standard arguments in favour of peaceful coexistence on the grounds that they are question‐begging, and suggest that the breakdown of Lorentz‐invariant relativity as a principle theory would be a natural development, given the general trend of physics in this century.     

A theory of causality: Causality=interaction (as defined by a suitable quantum field theory)

In this paper I put forward a suggestion for identifying causality in micro-systems with the specific quantum field theoretic interactions that occur in such systems. I first argue — along the lines of general transference theories — that such a physicalistic account is essential to an understanding of causation; I then proceed to sketch the concept of interaction as it occurs in quantum field theory and I do so from both a formal and an informal point of view. Finally, I present reasons for thinking that only a quantum field theoretic account can do the job — in particular I rely on a theorem by D. Currie and to the effect that interaction cannot be described in (a Hamiltonian formulation of) Classical Mechanics. Throughout the paper I attempt to suggest that the widespread scepticism about the ability of quantum theory to support a theory of causality is mistaken and rests on several misunderstandings.     

<Emphasis Type="Italic">Recursive Ontology</Emphasis>: A Systemic Theory of Reality

The article introduces recursive ontology, a general ontology which aims to describe how being is organized and what are the processes that drive it. In order to answer those questions, I use a multidisciplinary approach that combines the theory of levels, philosophy and systems theory. The main claim of recursive ontology is that being is the product of a single recursive process of generation that builds up all of reality in a hierarchical fashion from fundamental physical particles to human societies. To support this assumption, I provide the general laws and the basic principles of recursive ontology as well as a semi-formalised model of the theory based on a recursive generative grammar. Recursive ontology not only actively promotes a multidisciplinary investigation of reality, but also can be used as a general framework to develop future domain-specific theories.     

Temporal Relations vs. Logical Reduction: A Phenomenal Theory of Causality

Kant, in various parts of his treatment of causality, refers to determinism or the principle of sufficient reason as an inescapable principle. In fact, in the Second Analogy we find the elements to reconstruct a purely phenomenal determinism as a logical and tautological truth. I endeavour in this article to gather these elements into an organic theory of phenomenal causality and then show, in the third section, with a specific argument which I call the “paradox of phenomenal observation”, that this phenomenal determinism is the only rational approach to causality because any logico-reductivistic approach, such as the Humean one, would destroy the temporal order and so the very possibility to talk of a causal relation. I also believe that, all things said, Kant did not achieve a much greater comprehension of the problem than Hume did, in his theory of causality, for he did not free a phenomenal approach from the impasse of reductivism as his reflections on “simultaneous causation” and “vanishing quantities” indeed show, and this I will argue in Sect. 4 of this article.

The role of contrast in causal and explanatory claims

Following Dretske (1977), there has been a considerable body of literature on the role of contrastive stress in causal claims. Following van Fraassen (1980), there has been a considerable body of literature on the role of contrastive stress in explanations and explanation-requesting why-questions. Amazingly, the two bodies of literature have remained almost entirely disjoint. With an understanding of the contrastive nature of ordinary causal claims, and of the linguistic roles of contrastive stress, it is possible to provide a unified account of both phenomena. I provide such an account from within the framework of a probabilistic theory of causation. Relations of screening-off, long familiar to researchers in probabilistic causality, play a central role in this account.I would like to thank the following people for comments upon earlier drafts of this paper: Frank Arntzenius, Eric Barnes, Nuel Belnap, Alex Byrne, John Carroll, Fiona Cowie, Alan Hájek, David Hilbert, Carl Hoefer, Marc Lange, Wes Salmon, Cindy Stern, Nigel Thomas, and Jim Woodward.     

Dual-process theories of reasoning: The test of development

Dual-process theories have become increasingly influential in the psychology of reasoning. Though the distinction they introduced between intuitive and reflective thinking should have strong developmental implications, the developmental approach has rarely been used to refine or test these theories. In this article, I review several contemporary dual-process accounts of conditional reasoning that theorize the distinction between the two systems of reasoning as a contrast between heuristic and analytic processes, probabilistic and mental model reasoning, or emphasize the role of metacognitive processes in reflective reasoning. These theories are evaluated in the light of the main developmental findings. It is argued that a proper account of developmental phenomena requires the integration of the main strengths of these three approaches. I propose such an integrative theory of conditional understanding and argue that the modern dual-process framework could benefit from earlier contributions that made the same distinction between intuition and reflective thinking, such as Piaget’s theory.     

THE RELEVANCE OF EMERGENCE THEORY IN THE SCIENCE–RELIGION DIALOGUE

In this article, I call into question the relevance of emergence theories as presently used by thinkers in the science–religion discussion. Specifically, I discuss theories of emergence that have been used by both religious naturalists and proponents of panentheism. I argue for the following conclusions: (1) If we take the background theory to be metaphysical realism, then there seems to be no positive connection between the reality of emergent properties and the validity of providing reality with a religious interpretation, though one could perhaps construe an argument for the positive ontological status of emergence as a negative case for a religious worldview. (2) To be considered more plausible, religious naturalism should interpret religious discourse from the perspective of pragmatic realism. (3) Panentheistic models of divine causality are unable to avoid ontological dualism. (4) It is not obvious that emergent phenomena and/or properties are nonreducible in the ontological sense of the terms; indeed, the tension between weak and strong emergence makes it difficult for the emergentist to make ontological judgments. My general conclusion is that the concept of emergence has little metaphysical significance in the dialogue between science and theology.     

Learning a theory of causality

The very early appearance of abstract knowledge is often taken as evidence for innateness. We explore the relative learning speeds of abstract and specific knowledge within a Bayesian framework and the role for innate structure. We focus on knowledge about causality, seen as a domain-general intuitive theory, and ask whether this knowledge can be learned from co-occurrence of events. We begin by phrasing the causal Bayes nets theory of causality and a range of alternatives in a logical language for relational theories. This allows us to explore simultaneous inductive learning of an abstract theory of causality and a causal model for each of several causal systems. We find that the correct theory of causality can be learned relatively quickly, often becoming available before specific causal theories have been learned--an effect we term the blessing of abstraction. We then explore the effect of providing a variety of auxiliary evidence and find that a collection of simple perceptual input analyzers can help to bootstrap abstract knowledge. Together, these results suggest that the most efficient route to causal knowledge may be to build in not an abstract notion of causality but a powerful inductive learning mechanism and a variety of perceptual supports. While these results are purely computational, they have implications for cognitive development, which we explore in the conclusion.     

A probabilistic theory of second order causation

Larry Wright and others have advanced causal accounts of functional explanation, designed to alleviate fears about the legitimacy of such explanations. These analyses take functional explanations to describe second order causal relations. These second order relations are conceptually puzzling. I present an account of second order causation from within the framework of Eells' probabilistic theory of causation; the account makes use of the population-relativity of causation that is built into this theory.     

Relativistic Causality in Algebraic Quantum Field Theory

This paper surveys the issue of relativistic causality within the framework of algebraic quantum field theory (AQFT). In doing so, we distinguish various notions of causality formulated in the literature and study their relationships, and thereby we offer what we hope to be a useful taxonomy. We propose that the most direct expression of relativistic causality in AQFT is captured not (as has sometimes been claimed) by the spectrum condition but rather by the axiom of local primitive causality, in that it entails a form of local determinism for quantum fields which generalizes the constraint of no superluminal propagation of classical field theories to relativistic quantum field theory. We discuss the status of the axiom of micro-causality by locating its place within a large family of separability/independence/locality conditions developed for AQFT and also by relating it to so-called no-signalling theorems. And we also provide a critical survey of attempts to understand the implications for relativistic causality of the distant correlations endemic to the states in models of AQFT satisfying the standard axioms, and we provide an assessment of attempts to employ Reichenbach's common cause principle in AQFT to defuse worries that these distant correlations implicate direct causal connections between relatively spacelike events.