The literature on causal discovery has focused on interventions that involve randomly assigning values to a single variable. But such a randomized intervention is not the only possibility, nor is it always optimal. In some cases it is impossible or it would be unethical to perform such an intervention. We provide an account of ‘hard' and ‘soft' interventions and discuss what they can contribute to causal discovery. We also describe how the choice of the optimal intervention(s) depends heavily on the (...) particular experimental setup and the assumptions that can be made. ‡The first author is funded by the Causal Learning Collaborative Initiative supported by the James S. McDonnell Foundation. Many aspects of this paper were inspired by discussions with members of the collaborative. †To contact the authors, please write to: Department of Philosophy, Carnegie Mellon University, Pittsburgh, PA 15213; e-mail: [email protected] and [email protected]. (shrink)

An interventionist account of causation characterizes causal relations in terms of changes resulting from particular interventions. I provide a new example of a causal relation for which there does not exist an intervention satisfying the common interventionist standard. I consider adaptations that would save this standard and describe their implications for an interventionist account of causation. No adaptation preserves all the aspects that make the interventionist account appealing. Part of the fallout is a clearer account of the difficulties in characterizing (...) so-called “soft” interventions. (shrink)

This article is an attempt to provide an example that illustrates Hans Reichenbach’s concept of coordination. Throughout Reichenbach’s career the concept of coordination played an important role in his understanding of the connection between reality and how it is scientifically described. Reichenbach never fully specified what coordination is and how exactly it works. Instead, we are left with a variety of hints and gestures, many not entirely consistent with each other and several that are subject to change over the course (...) of his career. Using the example of how to discover and construct causal variables, I will show that most of the features of coordination that Reichenbach described can be instantiated together and formulated precisely. (shrink)

Hans Reichenbach is well known for his limiting frequency view of probability, with his most thorough account given in The Theory of Probability in 1935/1949. Perhaps less known are Reichenbach's early views on probability and its epistemology. In his doctoral thesis from 1915, Reichenbach espouses a Kantian view of probability, where the convergence limit of an empirical frequency distribution is guaranteed to exist thanks to the synthetic a priori principle of lawful distribution. Reichenbach claims to have given a purely objective (...) account of probability, while integrating the concept into a more general philosophical and epistemological framework. A brief synopsis of Reichenbach's thesis and a critical analysis of the problematic steps of his argument will show that the roots of many of his most influential insights on probability and causality can be found in this early work. (shrink)

The causal Bayes net framework specifies a set of axioms for causal discovery. This article explores the set of causal variables that function as relata in these axioms. Spirtes showed how a causal system can be equivalently described by two different sets of variables that stand in a non-trivial translation-relation to each other, suggesting that there is no “correct” set of causal variables. I extend Spirtes’ result to the general framework of linear structural equation models and then explore to what (...) extent the possibility to intervene or a preference for simpler causal systems may help in selecting among sets of causal variables. (shrink)

This survey presents some of the main principles involved in discovering causal relations. They belong to a large array of possible assumptions and conditions about causal relations, whose various combinations limit the possibilities of acquiring causal knowledge in different ways. How much and in what detail the causal structure can be discovered from what kinds of data depends on the particular set of assumptions one is able to make. The assumptions considered here provide a starting point to explore further the (...) foundations of causal discovery procedures, and how they can be improved. (shrink)

Using a variety of different results from the literature, I show how causal discovery with experiments is limited unless substantive assumptions about the underlying causal structure are made. These results undermine the view that experiments, such as randomized controlled trials, can independently provide a gold standard for causal discovery. Moreover, I present a concrete example in which causal underdetermination persists despite exhaustive experimentation and argue that such cases undermine the appeal of an interventionist account of causation as its dependence on (...) other assumptions is not spelled out. (shrink)

By combining experimental interventions with search procedures for graphical causal models we show that under familiar assumptions, with perfect data, N - 1 experiments suffice to determine the causal relations among N > 2 variables when each experiment randomizes at most one variable. We show the same bound holds for adaptive learners, but does not hold for N > 4 when each experiment can simultaneously randomize more than one variable. This bound provides a type of ideal for the measure of (...) success of heuristic approached in active learning methods of casual discovery, which currently use less informative measures. (shrink)

We argue that current discussions of criteria for actual causation are ill-posed in several respects. (1) The methodology of current discussions is by induction from intuitions about an infinitesimal fraction of the possible examples and counterexamples; (2) cases with larger numbers of causes generate novel puzzles; (3) “neuron” and causal Bayes net diagrams are, as deployed in discussions of actual causation, almost always ambiguous; (4) actual causation is (intuitively) relative to an initial system state since state changes are relevant, but (...) most current accounts ignore state changes through time; (5) more generally, there is no reason to think that philosophical judgements about these sorts of cases are normative; but (6) there is a dearth of relevant psychological research that bears on whether various philosophical accounts are descriptive. Our skepticism is not directed towards the possibility of a correct account of actual causation; rather, we argue that standard methods will not lead to such an account. A different approach is required. Once upon a time a hungry wanderer came into a village. He filled an iron cauldron with water, built a fire under it, and dropped a stone into the water. “I do like a tasty stone soup” he announced. Soon a villager added a cabbage to the pot, another added some salt and others added potatoes, onions, carrots, mushrooms, and so on, until there was a meal for all. (shrink)

An interventionist account of causation characterizes causal relations in terms of changes resulting from particular interventions. We provide an example of a causal relation for which there does not exist an intervention satisfying the common interventionist standard. We consider adaptations that would save this standard and describe their implications for an interventionist account of causation. No adaptation preserves all the aspects that make the interventionist account appealing.

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)

We provide a critical assessment of the account of causal emergence presented in Erik Hoel’s 2017 article “When the map is better than the territory”. The account integrates causal and information theoretic concepts to explain under what circumstances there can be causal descriptions of a system at multiple scales of analysis. We show that the causal macro variables implied by this account result in interventions with significant ambiguity, and that the operations of marginalization and abstraction do not commute. Both of (...) these are desiderata that, we argue, any account of multi-scale causal analysis should be sensitive to. The problems we highlight in Hoel’s definition of causal emergence derive from the use of various averaging steps and the introduction of a maximum entropy distribution that is extraneous to the system under investigation. (shrink)

We consider the problems arising from using sequences of experiments to discover the causal structure among a set of variables, none of whom are known ahead of time to be an “outcome”. In particular, we present various approaches to resolve conflicts in the experimental results arising from sampling variability in the experiments. We provide a sufficient condition that allows for pooling of data from experiments with different joint distributions over the variables. Satisfaction of the condition allows for an independence test (...) with greater sample size that may resolve some of the conflicts in the experimental results. The pooling condition has its own problems, but should—due to its generality—be informative to techniques for meta-analysis. (shrink)

Bayesian models of human learning are becoming increasingly popular in cognitive science. We argue that their purported confirmation largely relies on a methodology that depends on premises that are inconsistent with the claim that people are Bayesian about learning and inference. Bayesian models in cognitive science derive their appeal from their normative claim that the modeled inference is in some sense rational. Standard accounts of the rationality of Bayesian inference imply predictions that an agent selects the option that maximizes the (...) posterior expected utility. Experimental confirmation of the models, however, has been claimed because of groups of agents that probability match the posterior. Probability matching only constitutes support for the Bayesian claim if additional unobvious and untested (but testable) assumptions are invoked. The alternative strategy of weakening the underlying notion of rationality no longer distinguishes the Bayesian model uniquely. A new account of rationality—either for inference or for decision-making—is required to successfully confirm Bayesian models in cognitive science. (shrink)

A symposium on Michael Strevens' book "Tychomancy", concerning the psychological roots and historical significance of physical intuition about probability in physics, biology, and elsewhere.

We present an algorithm to infer causal relations between a set of measured variables on the basis of experiments on these variables. The algorithm assumes that the causal relations are linear, but is otherwise completely general: It provides consistent estimates when the true causal structure contains feedback loops and latent variables, while the experiments can involve surgical or `soft' interventions on one or multiple variables at a time. The algorithm is `online' in the sense that it combines the results from (...) any set of available experiments, can incorporate background knowledge and resolves conflicts that arise from combining results from different experiments. In addition we provide a necessary and sufficient condition that determines when the algorithm can uniquely return the true graph, and can be used to select the next best experiment until this condition is satisfied. We demonstrate the method by applying it to simulated data and the flow cytometry data of Sachs et al. (shrink)

Scientific models describe natural phenomena at different levels of abstraction. Abstract descriptions can provide the basis for interventions on the system and explanation of observed phenomena at a level of granularity that is coarser than the most fundamental account of the system. Beckers and Halpern (2019), building on work of Rubenstein et al. (2017), developed an account of abstraction for causal models that is exact. Here we extend this account to the more realistic case where an abstract causal model offers (...) only an approximation of the underlying system. We show how the resulting account handles the discrepancy that can arise between low- and high-level causal models of the same system, and in the process provide an account of how one causal model approximates another, a topic of independent interest. Finally, we extend the account of approximate abstractions to probabilistic causal models, indicating how and where uncertainty can enter into an approximate abstraction. (shrink)

Oaksford & Chater (O&C) aim to provide teleological explanations of behavior by giving an appropriate normative standard: Bayesian inference. We argue that there is no uncontroversial independent justification for the normativity of Bayesian inference, and that O&C fail to satisfy a necessary condition for teleological explanations: demonstration that the normative prescription played a causal role in the behavior's existence.

We argue that the authors’ call to integrate Bayesian models more strongly with algorithmic- and implementational-level models must go hand in hand with a call for a fully developed account of algorithmic rationality. Without such an account, the integration of levels would come at the expense of the explanatory benefit that rational models provide.

We argue that current discussions of criteria for actual causation are ill-posed in several respects. (1) The methodology of current discussions is by induction from intuitions about an infinitesimal fraction of the possible examples and counterexamples; (2) cases with larger numbers of causes generate novel puzzles; (3) "neuron" and causal Bayes net diagrams are, as deployed in discussions of actual causation, almost always ambiguous; (4) actual causation is (intuitively) relative to an initial system state since state changes are relevant, but (...) most current accounts ignore state changes through time; (5) more generally, there is no reason to think that philosophical judgements about these sorts of cases are normative; but (6) there is a dearth of relevant psychological research that bears on whether various philosophical accounts are descriptive. Our skepticism is not directed towards the possibility of a correct account of actual causation; rather, we argue that standard methods will not lead to such an account. A different approach is required. (shrink)

Hans Reichenbach has been not only one of the founding fathers of logical empiricism but also one of the most prominent figures in the philosophy of science of the past century. While some of his ideas continue to be of interest in current philosophical programs, an important part of his early work has been neglected, and some of it has been unavailable to English readers. Among Reichenbach’s overlooked (and untranslated) early works, his doctoral thesis of 1915, The Concept of Probability (...) in the Mathematical Representation of Reality, deserves special attention, both for the topics covered and for its significance for a proper understanding of his intellectual trajectory. This volume anticipates most of the fundamental themes of his later philosophy. In particular, it addresses the issue of the application of probability statements to reality, as well as the relationship between probability and causality—questions that have been at the core of his research throughout his life. (shrink)

This study examines the philosophical foundations of Hegel's social theory by articulating the normative standards at work in his claim that the central social institutions of the modern era are rational or good.

The Fate of Reason is the first general history devoted to the period between Kant and Fichte, one of the most revolutionary and fertile in modern philosophy. The philosophers of this time broke with the two central tenets of the modem Cartesian tradition: the authority of reason and the primacy of epistemology. They also witnessed the decline of the Aufkldrung, the completion of Kant's philosophy, and the beginnings of post-Kantian idealism. Thanks to Beiser we can newly appreciate the influence of (...) Kant's critics on the development of his philosophy. Beiser brings the controversies, and the personalities who engaged in them, to life and tells a story that has uncanny parallels with the debates of the present. (shrink)

[1] Das Werten.--[2] Das Erkennen.--[3] Das Handeln.

This book is addressed to readers who have laid the foundation of a liberal education & are beginning the special study of law.

. This paper explores the relationship between gift giving, guanxi and corruption through a study of the relationships between UK manufacturing companies in China and their local component suppliers. The analysis is based on interviews in the China-based operations of 49 UK companies. Interviews were carried out both with senior (often expatriate) staff and with local line managers who were responsible for everyday purchasing decisions and for managing relationships with suppliers. The results suggest that gift giving is perceived to be (...) a significant problem in UK-owned companies in China. However the relationship between these payments and established understanding of gift giving within guanxi-networks appears to be weak. Gift giving appears to be associated with illicit payments, corruption and the pursuit of self-interest. Firms seek to reduce the incidence of illicit transactions by changing staff roles, instituting joint responsibilities, which include the separation of different aspects of sourcing/purchasing, ineasing the involvement of senior staff in the process and through the education of employee and suppliers. (shrink)

Through a series of provocative conversations, Frederick Luis Aldama and Herbert Lindenberger, who have written widely on literature, film, music, and art, locate a place for the discomforting and the often painfully unpleasant within aesthetics. The conversational format allows them to travel informally across many centuries and many art forms. They have much to tell one another about the arts since the advent of modernism soon after 1900—the nontonal music, for example, of the Second Vienna School, the chance-directed music (...) and dance of John Cage and Merce Cunningham, the in-your-faceness of such diverse visual artists as Francis Bacon, Pablo Picasso, Willem de Kooning, Egon Schiele, Otto Dix, and Damien Hirst. They demonstrate as well a long tradition of discomforting art stretching back many centuries, for example, in the Last Judgments of innumerable Renaissance painters, in Goya’s so-called “black” paintings, in Wagner’s Tristan chord, and in the subtexts of Shakespearean works such as King Lear and Othello. This book is addressed at once to scholars of literature, art history, musicology, and cinema. Although its conversational format eschews the standard conventions of scholarly argument, it provides original insights both into particular art forms and into individual works within these forms. Among other matters, it demonstrates how recent work in neuroscience may provide insights in the ways that consumers process difficult and discomforting works of art. The book also contributes to current aesthetic theory by charting the dialogue that goes on—especially in aesthetically challenging works—between creator, artifact, and consumer. (shrink)

A noticeable shift in focus has occurred in public discourse from What is our best course of action? to What are the true facts of the situation? At the center of these debates are questions on the proper use of evidence, Legal scholar Schauer offers clarity based on how legal systems grapple with these questions-and by drawing insights from psychology, philosophy, economics, history, and decision theory.

This chapter contains sections titled: The Aim of Hegel's Science of Society The Method of Hegel's Science of Society Comprehension versus Critique.

Imagining the Course of Life offers a rich portrait of rural life in contemporary Southeast Asia and an accessible introduction to the complexities of Theravada Buddhism as it is actually lived and experienced. It is both an ethnography of indigenous views of human development and a theoretical consideration of how any ethnopsychology is embedded in society and culture. Drawing on long-term fieldwork in a Shan village in northern Thailand, Nancy Eberhardt illustrates how indigenous theories of the life course are (...) connected to local constructions of self and personhood. In the process, she draws our attention to contrasting models in the Euro-American tradition and invites us to reconsider how we think about the trajectory of a human life. Moving beyond the entrenched categories that can hamper our understanding of other views, Imagining the Course of Life demonstrates the real-life connections between the "religious" and the "psychological." Eberhardt shows how such beliefs and practices are used, sometimes strategically, in people's constructions of themselves, in their interpretations of others' behavior, and in their attempts at social positioning. Individual chapters explore Shan ideas about the overall course of human development, from infancy to old age and beyond, and show how these ideas inform people's understanding of personhood and maturity, gender and social inequality, illness and well-being, emotions and mental health. (shrink)

This chapter attempts to unravel the differences, whether real or merely apparent, between Chomsky's linguistics and usage‐based linguistics (UBL). The principal alternative to generative grammar in the world today is a broad umbrella of approaches that fall under the general heading of UBL. UBL is the successor to a Piagetian approach to language acquisition, where experience and general learning principles shape the acquisition process. Functionalism takes the position that properties of grammatical systems are explicable in terms of properties of systems (...) that lie outside of grammar per se. The chapter discusses that the few direct references Chomsky has made to usage‐based linguistics. It presents the most important issues, one‐by‐one, that separate Chomsky's views from those of UBLists. They are the explananda of linguistic theory, grammar design and architecture, semantics, language acquisition and innately‐provided linguistic constructs, functional explanation, and the sources of data on which a linguistic theory might be constructed. (shrink)

Theories of epistemically justified belief have long assumed individualism. In its extreme, or Lockean, form individualism rules out justified belief on testimony by insisting that a subject is justified in believing a proposition only if he or she possesses first-hand justification for it. The skeptical consequences of extreme individualism have led many to adopt a milder version, attributable to Hume, on which a subject is justified in believing a proposition only if he or she is justified in believing that there (...) is testimony in favor of the proposition deriving from a reliable source. I argue that this Humean individualism also leads to skepticism in a wide range of cases; it makes it impossible for a layperson to be justified on expert testimony. In addition, I argue that the apparent motivation for the Humean view, an insistence on intellectual autonomy in justification, does not succeed in motivating it. I then explore the contours of a collectivist view of justification on testimony, with special attention to the place of a subject's intellectual autonomy in such justification. I try to bring empirical results of the psychology of persuasion to bear on the epistemological issues. (shrink)

This book locates the paradoxical process of collecting (as an activity that necessarily involves displacement and dispersal) in the ways nineteenth- and twentieth-century German-language literature (and in one case, cinema) attempts to represent ephemeral, discarded, and trivial things.