The aim of the article is to present a model of causal relations that is based on what is known about human causal reasoning and that forms guidelines for implementations in robots. I argue for two theses concerning human cognition. The first is that human causal cognition, in contrast to that of other animals, is based on the understanding of the forces that are involved. The second thesis is that humans think about causality in terms of events. (...) I present a two-vector model of events, developed by Gärdenfors and Warglien, which states that an event is represented in terms of two main components – the force of an action that drives the event, and the result of its application. Apart from the causal mapping, the event model contains representations of a patient, an agent, and possibly some other roles. Agents and patients are objects (animate or inanimate) that have different properties. Following my theory of conceptual spaces, they can be described as vectors of property values. At least two spaces are needed to describe an event, an action space and a result space. The result of an event is modeled as a vector representing the change of properties of the patient before and after the event. In robotics the focus has been on describing results. The proposed model also includes the causal part of events, typically described as an action. A central part of an event category is the mapping from actions to results. This mapping contains the central information about causal relations. In applications of the two-vector model, the central problem is how the event mapping can be learned in a way that is amenable to implementations in robots. Three processes are central for event cognition: causal thinking, control of action and learning by generalization. Although it is not yet clear which is the best way to model how the mappings can be learned, they should be constrained by three corresponding mathematical properties: monotonicity (related to qualitative causal thinking); continuity (plays a key role in activities of action control); and convexity (facilitates generalization and the categorization of events). I argue that Bayesian models are not suitable for these purposes, but some more geometrically oriented approach to event mappings should be used. (shrink)

Some philosophers hold that the neuroscience of action is, in practice or in principle, incapable of touching debates in action theory and moral psychology. The role of desires in action, the existence of basic actions, and the like are topics that must be sorted out by philosophers alone: at least at present, and perhaps by the very nature of the questions. This paper examines both philosophical and empirical arguments against the relevance of neuroscience to such questions and argues that neither (...) succeeds. In practice, there is already a stable body of findings from neuroanatomy and neurophysiology that warrants attention. And as a matter of principle, the ‘causal map’ of action production derivable from these findings requires the study of action theorists and moral psychologists because every such philosopher has commitments to the shape of this causal map: commitments that might be in conflict with reality. (shrink)

It is generally accepted that farmers manage a complex farm system. In this article we seek answers to the following questions. How do farmers perceive and understand their farm system? Are they sufficiently aware of their farm system that they are able to represent it in the form of a map? The research reported describes how causal mapping was applied to sheep/beef farmers in New Zealand and shows that farmers can create maps of their farm systems in ways (...) that allow expression of both individual maps and the formation of group maps which represent the general character of farm systems. A group map was made for all the farmers studied and for subgroups using conventional, integrated, and organic management systems. The results are discussed in terms of the depth of meaning associated with individual elements of the map, map complexity and the limitations of causal mapping. Causal mapping has the potential to contribute to our knowledge of how farmers see their farm systems, and this can benefit farmers and other stakeholders concerned with the management of farms and their economic and environmental performance. (shrink)

Even though potential impacts of political and legal environments of business on ethical behavior of firms (EBOF) have been conceptually recognized, not much evidence (i.e., empirical work) has been produced to clarify their role. In this paper, using Bayesian causal maps (BCMs) methodology, relationships between legal and political environments of business and EBOF are investigated. The unique design of our study allows us to analyze these relationships based on the stages of development in 92 countries around the world. (...) The EBOF models structured through BCMs are used to explain how EBOF in a given country group are shaped by how managers perceive political, legislative, and protective environments of business in these countries. The results suggest that irregular payments and bribes are the most influential factors affecting managers’ perceptions of business ethics in relatively more advanced economies, whereas intellectual property protection is the most influential factor affecting managers’ perceptions of business ethics in less-advanced economies. The results also suggest that regardless of where the business is conducted in the world, judicial independence is the driving force behind managers’ perceptions of business ethics. In addition, the results of this study provide further support for scholars who argue that business ethics is likely to vary among countries based on their socio-economic factors. In addition to its managerial implications, the study provides directions for policy makers to improve the ethical conduct of businesses in their respective countries. (shrink)

We propose that children employ specialized cognitive systems that allow them to recover an accurate “causal map” of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or “Bayes nets”. Children’s causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest (...) that 2- to 4-year-old children construct new causal maps and that their learning is consistent with the Bayes net formalism. (shrink)

Two-dimensional coupled map lattices have global stability properties that depend on the coupling between individual maps and their neighborhood. The action of the neighborhood on individual maps can be implemented in terms of ‘‘causal’’ coupling (to spatially distant past states) or ‘‘non-causal’’ coupling (to spatially distant simultaneous states). In this contribution we show that globally stable behavior of coupled map lattices is facilitated by causal coupling, thus indicating a surprising relationship between stability and causality. The (...) influence of causal versus non-causal coupling for synchronous and asynchronous updating as a function of coupling strength and for different neighborhoods is analyzed in detail. r 2004 Elsevier B.V. All rights reserved. (shrink)

A central argument for non-reductive accounts of group agency is that complex social entities are capable of exerting causal influence independently of and superseding the causal efficacy of the individuals constituting them. A prominent counter is that non-reductionists run into an insuperable dilemma between identity and redundancy – with identity undermining independent higher-level efficacy and redundancy leading to overdetermination or exclusion. This paper argues that critics of non-reductionism can manage with a simpler and more persuasive reductio strategy called (...) mapping: allow that group agents are causally efficacious in their own right and chart how their causal efficacy is carried out; how it relates to the causal efficacy of individual determiners; how it connects to the causal relevance of background structural factors. The focus exclusively on whether groups are or are not causally efficacious black-boxes implementation, while close attention to how causation is wired increases the visibility of individualist arguments and countenances structure-oriented explanations. (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)

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)

Though causality seems to have a natural place in chemical thought, the analysis of the underlying causal concepts requires attention to two different research styles. In Part One I attempt a classification and critical analysis of several philosophical accounts of causal concepts which appear to be very diverse. I summarize this diversity which ranges from causality as displayed in regular concomitances of types of events to causality as the activity of agents. Part Two is concerned with the analysis (...) of contrasting chemical discourses, comparing the classical atomist style of Boyle, and Lavoisier and von Liebig with the later energeticist style of van’t Hoff and Hinshelwood. In detail different clusters of causal concepts can be abstracted from these discursive styles, yet they all approximate the Realist format for causal discourse. By way of summary I make an attempt to map the vernacular distinctions of Part Two onto the philosophical territory of Part One. The argument is rounded off with a brief analysis of a chemical publication of 2008. (shrink)

Using a unique data set of causal usage drawn from research articles published between 2006–2008 in the American Journal of Sociology and American Sociological Review, this article offers an empirical assessment of causality in American sociology. Testing various aspects of what we consider the conventional wisdom on causality in the discipline, we find that “variablistic” or “covering law” models are not the dominant way of making causal claims, research methods affect but do not determine causal usage, and (...) the use of explicit causal language and the concept of “mechanisms” to make causal claims is limited. Instead, we find that metaphors and metaphoric reasoning are fundamental for causal claims-making in the discipline. On this basis, we define three dominant causal types used in sociology today, which we label the Probabilistic, Initiating and Conditioning types. We theorize this outcome as demonstrating the primary role that cognitive models play in providing inference-rich metaphors that allow sociologists to map causal relationships on to empirical processes. (shrink)

Real causal systems are complicated. Despite this, causal learning research has traditionally emphasized how causal relations can be induced on the basis of idealized events, i.e. those that have been mapped to binary variables and abstracted from time. For example, participants may be asked to assess the efficacy of a headache-relief pill on the basis of multiple patients who take the pill (or not) and find their headache relieved (or not). In contrast, the current study examines learning (...) via interactions with continuous dynamic systems, systems that include continuous variables that interact over time (and that can be continuously observed in real time by the learner). To explore such systems, we develop a new framework that represents a causal system as a network of stationary Gauss--Markov (``\OU'') processes and show how such \textit{OU networks} can express complex dynamic phenomena such as feedback loops and oscillations. To assess adult's abilities to learn such systems, we conducted an experiment in which participants were asked to identify the causal relationships of a number of OU networks, potentially carrying out multiple, temporally-extended interventions. We compared their judgments to a normative model for learning OU networks as well as a range of alternative and heuristic learning models from the literature. We found that, although participants exhibited substantial learning of such systems, they committed certain systematic errors. These successes and failures were best accounted for by a model that describes people as focusing on pairs of variables, rather than evaluating the evidence with respect to the full space of possible structural models. We argue that our approach provides both a principled framework for exploring the space of dynamic learning environments as well as new algorithmic insights into how people interact successfully with a continuous causal world. (shrink)

The pervasive use of computer simulations in the sciences brings novel epistemological issues discussed in the philosophy of science literature since about a decade. Evolutionary biology strongly relies on such simulations, and in relation to it there exists a research program (Artificial Life) that mainly studies simulations themselves. This paper addresses the specificity of computer simulations in evolutionary biology, in the context (described in Sect. 1) of a set of questions about their scope as explanations, the nature of validation processes (...) and the relation between simulations and true experiments or mathematical models. After making distinctions, especially between a weak use where simulations test hypotheses about the world, and a strong use where they allow one to explore sets of evolutionary dynamics not necessarily extant in our world, I argue in Sect. 2 that (weak) simulations are likely to represent in virtue of the fact that they instantiate specific features of causal processes that may be isomorphic to features of some causal processes in the world, though the latter are always intertwined with a myriad of different processes and hence unlikely to be directly manipulated and studied. I therefore argue that these simulations are merely able to provide candidate explanations for real patterns. Section 3 ends up by placing strong and weak simulations in Levins’ triangle, that conceives of simulations as devices trying to fulfil one or two among three incompatible epistemic values (precision, realism, genericity). (shrink)

Studies of primate cognition have conclusively shown that humans and apes share a range of basic cognitive abilities. As a corollary, these same studies have also focussed attention on what makes humans unique, and on when and how specifically human cognitive skills evolved. There is widespread agreement that a major distinguishing feature of the human mind is its capacity for causal reasoning. This paper argues that causal cognition originated with the use made of indirect natural signs by early (...) hominins forced to adapt to variable late Miocene and early Pliocene environments; that early hominins evolved an innate tendency to search for such signs and infer their causes; that causal inference required the existence of incipient working memory; and that causal relationships were stored through being integrated into spatial maps to create increasingly complex causal models of the world. (shrink)

This article compares causal and constitutive explanation. While scientific inquiry usually addresses both causal and constitutive questions, making the distinction is crucial for a detailed understanding of scientific questions and their interrelations. These explanations have different kinds of explananda and they track different sorts of dependencies. Constitutive explanations do not address events or behaviors, but causal capacities. While there are some interesting relations between building and causal manipulation, causation and constitution are not to be confused. Constitution (...) is a synchronous and asymmetric relation between relata that cannot be conceived as independent existences. However, despite their metaphysical differences, the same key ideas about explanation largely apply to both. Causal and constitutive explanations face similar challenges (such as the problems of relevance and explanatory regress) and both are in the business of mapping networks of counterfactual dependence—i.e. mechanisms—although the relevant counterfactuals are of a different sort. In the final section the issue of developmental explanation is discussed. It is argued that developmental explanations deserve their own place in taxonomy of explanations, although ultimately developmental dependencies can be analyzed as combinations of causal and constitutive dependencies. Hence, causal and constitutive explanation are distinct, but not always completely separate forms of explanation. (shrink)

& Carnegie Mellon University Abstract The rationality of human causal judgments has been the focus of a great deal of recent research. We argue against two major trends in this research, and for a quite different way of thinking about causal mechanisms and probabilistic data. Our position rejects a false dichotomy between "mechanistic" and "probabilistic" analyses of causal inference -- a dichotomy that both overlooks the nature of the evidence that supports the induction of mechanisms and misses (...) some important probabilistic implications of mechanisms. This dichotomy has obscured an alternative conception of causal learning: for discrete events, a central adaptive task is to induce causal mechanisms in the environment from probabilistic data and prior knowledge. Viewed from this perspective, it is apparent that the probabilistic norms assumed in the human causal judgment literature often do not map onto the mechanisms generating the probabilities. Our alternative conception of causal judgment is more congruent with both scientific uses of the notion of causation and observed causal judgments of untutored reasoners. We illustrate some of the relevant variables under this conception, using a framework for causal representation now widely adopted in computer science and, increasingly, in statistics. We also review the formulation and evidence for a theory of human causal induction (Cheng, 1997) that adopts this alternative conception. (shrink)

We consider a sequence of successively more restrictive definitions of abstraction for causal models, starting with a notion introduced by Rubenstein et al. (2017) called exact transformation that applies to probabilistic causal models, moving to a notion of uniform transformation that applies to deterministic causal models and does not allow differences to be hidden by the "right" choice of distribution, and then to abstraction, where the interventions of interest are determined by the map from low-level states to (...) high-level states, and strong abstraction, which takes more seriously all potential interventions in a model, not just the allowed interventions. We show that procedures for combining micro-variables into macro-variables are instances of our notion of strong abstraction, as are all the examples considered by Rubenstein et al. (shrink)

It is widely thought that causal cognition underpins technical reasoning. Here we suggest that understanding causal cognition as a thinking system that includes theory of mind (i.e., social cognition) can be a productive theoretical tool for the field of evolutionary cognitive archaeology. With this contribution, we expand on an earlier model that distinguishes seven grades of causal cognition, explicitly presenting it together with a new analysis of the theory of mind involved in the different grades. We then (...) suggest how such thinking may manifest in the archaeological or stone tool record and techno-behaviors of the last three million years or so. Our thesis is threefold: (a) theory of mind is an integral element of causal cognition; (b) generally speaking, the more advanced causal cognition is, the more it is dependent on theory of mind; and (c) the evolution of causal cognition depends more and more on mental representations of hidden variables. Ultimately, the final or seventh grade of causal cognition allows us to reason from a network of hidden variables that, amongst other things, enables the learning, manufacture, and use of complex technological systems. It also facilitates the seamless mapping of knowledge between personal (egocentric), physical, and social networks that allows for newly devised and innovative technical and social outcomes. (shrink)

Most of us create and use a panoply of non-sentential representations throughout our ordinary lives: we regularly use maps to navigate, charts to keep track of complex patterns of data, and diagrams to visualize logical and causal relations among states of affairs. But philosophers typically pay little attention to such representations, focusing almost exclusively on language instead. In particular, when theorizing about the mind, many philosophers assume that there is a very tight mapping between language and thought. Some (...) analyze utterances as the outer vocalizations of inner thoughts (e.g. Grice 1957, Devitt 2005), while others treat thought as a form of inner speech (e.g. Sellars 1956/1997, Carruthers 2002). But even philosophers who take no stand on the relative priority of language and thought still tend to individuate mental states in terms of the sentences we use to ascribe them. Indeed, Dummett (1993) claims that it is constitutive of analytic philosophy that it approaches the mind by way of language. In many ways, this linguistic model is salutary. Our thoughts are often intimately intertwined with their linguistic expression, and public language does provide a comparatively tractable proxy for, and a window into, the messier realm of thought. However, an exclusive focus on thought as it is expressed in language threatens to leave other sorts of thought unexplained, or even to blind us to their possibility. In particular, many cognitive ethologists and psychologists find it useful to talk about humans, chimpanzees, birds, rats, and even bees as employing cognitive maps. We need to make sense of this way of talking about minds as well as more familiar sentential descriptions. In what follows, I investigate the theoretical and practical possibility of non-sentential thought. Ultimately, I am most interested in the contours of distinctively human thought: what forms does human thought take, and how do those different forms interact? How does human thought compare with that of other animals? In this essay, however, I focus on a narrower and more basic theoretical question: could thought occur in maps? Many philosophers are convinced that in some important sense, thought per se must be language-like.. (shrink)

Social transmission is at the core of cultural evolutionary theory. It occurs when a demonstrator uses mental representations to produce some public displays which in turn allow a learner to acquire similar mental representations. Although cultural evolutionists do not dispute this view of social transmission, they typically abstract away from the multistep nature of the process when they speak of cultural variants at large, thereby referring both to variation and evolutionary change in mental representations as well as in their corresponding (...) public displays. This conflation suggests that differentiating each step of the transmission process is redundant. In this paper, I examine different forms of interplay between the multistep nature of social transmission and the metric spaces used by cultural evolutionists to measure cultural variation and to model cultural change. I offer a conceptual analysis of what assumptions seem to be at work when cultural evolutionists conflate the complex causal sequence of social transmission as a single space of variation in which populations evolve. To this aim, I use the framework of variation spaces, a formal framework commonly used in evolutionary biology, and I develop two theoretical concepts, ‘technique’ and ‘technical space’, for addressing cases where the complexity of social transmission defies the handy assumption of a single variation space for cultural change. (shrink)

In order to support health interventions, biomedical and population health researchers need to collect solid evidence. This article asks what type of evidence this should be and expands on previous work that focused on etiological explanations, or causal-mechanical explanations of why and how illness occurs. The article proposes adding predictive evidence to the explanatory evidence, in order to form a joint evidence set, or JES = [A,B,C,D], which consists of four different types of evidence: association [A], biology [B], confirmation (...) [C], and difference-making [D]. The article discusses explanatory coherence as a backbone for this proposal, suggests criteria for each type of evidence, and offers a rubric for multi-evidence mapping. (shrink)

The developing academic field of machine ethics seeks to make artificial agents safer as they become more pervasive throughout society. In contrast to computer ethics, machine ethics is concerned with the behavior of machines toward human users and other machines. This study aims to use an action-based ethical theory founded on the combinational aspects of deontological and teleological theories of ethics in the construction of an artificial moral agent (AMA).,The decision results derived by the AMA are acquired via fuzzy logic (...) interpretation of the relative values of the steady-state simulations of the corresponding rule-based fuzzy cognitive map (RBFCM).,Through the use of RBFCMs, the following paper illustrates the possibility of incorporating ethical components into machines, where latent semantic analysis (LSA) and RBFCMs can be used to model dynamic and complex situations, and to provide abilities in acquiring causal knowledge.,This approach is especially appropriate for data-poor and uncertain situations common in ethics. Nonetheless, to ensure that a machine with an ethical component can function autonomously in the world, research in artificial intelligence will need to further investigate the representation and determination of ethical principles, the incorporation of these ethical principles into a system’s decision procedure, ethical decision-making with incomplete and uncertain knowledge, the explanation for decisions made using ethical principles and the evaluation of systems that act based upon ethical principles.,To date, the conducted research has contributed to a theoretical foundation for machine ethics through exploration of the rationale and the feasibility of adding an ethical dimension to machines. Further, the constructed AMA illustrates the possibility of utilizing an action-based ethical theory that provides guidance in ethical decision-making according to the precepts of its respective duties. The use of LSA illustrates their powerful capabilities in understanding text and their potential application as information retrieval systems in AMAs. The use of cognitive maps provides an approach and a decision procedure for resolving conflicts between different duties.,This paper suggests that cognitive maps could be used in AMAs as tools for meta-analysis, where comparisons regarding multiple ethical principles and duties can be examined and considered. With cognitive mapping, complex and abstract variables that cannot easily be measured but are important to decision-making can be modeled. This approach is especially appropriate for data-poor and uncertain situations common in ethics. (shrink)

Fuzzy cognitive maps is a system modeling methodology which applies mostly in complex dynamic systems by describing causal relationships that exist between its parameters called concepts. Fuzzy cognitive map theories have been used in many applications but they present several drawbacks and deficiencies. These limitations are addressed and analyzed fuzzy cognitive map theories are readdressed. A new novel approach in modelling fuzzy cognitive maps is proposed to increase the knowledge of the system and overcome some of its (...) limitations. The state space approach is used for the new model to disaggregate the concepts into different categories. The disaggregation of the concepts into state concepts, input concepts and output concepts is mathematically formulated. The proposed method and the new model is used for the calculation of a building’s energy consumption and the management of its load. Simulations are performed as a case study testing the new proposed method. The problem of the high energy consumption of the building sector is studied using the new fuzzy cognitive map model. Discussions of the obtained results along with future research directions are provided. (shrink)

Wood and Spekkens argue that any causal model explaining the EPRB correlations and satisfying the no-signalling constraint must also violate the assumption that the model faithfully reproduces the statistical dependences and independences—a so-called ‘fine-tuning’ of the causal parameters. This includes, in particular, retrocausal explanations of the EPRB correlations. I consider this analysis with a view to enumerating the possible responses an advocate of retrocausal explanations might propose. I focus on the response of Näger, who argues that the central (...) ideas of causal explanations can be saved if one accepts the possibility of a stable fine-tuning of the causal parameters. I argue that in light of this view, a violation of faithfulness does not necessarily rule out retrocausal explanations of the EPRB correlations. However, when we consider a plausible retrocausal picture in some detail, it becomes clear that the causal modelling framework is not a natural arena for representing such an account of retrocausality. _1_ Causal Models, Quantum Mechanics, and Faithfulness _2_ Fine-Tuning _2.1_ Fine-tuning in a retrocausal model _3_ Possible Responses _4_ Quantum Causal Models and Retrocausality _4.1_ A more detailed retrocausal account _4.2_ A model of the EPRB probabilities _4.3_ Mapping to a causal model _5_ Conclusion. (shrink)

This essay considers Kant’s concept of the highest good from a systematic point of view. The two spheres of freedom and nature—of the practical and theoretical—need to be brought into a causal relation for the highest good to be achieved. Kant seems to offer numerous possibilities for how human beings are able to think that it is possible for the highest good to be attainable. I argue that it is only in the third Critique, however, that Kant articulates an (...) answer that also establishes freedom and nature within a larger system. The third Critique does this by positing a third, independent and mediating sphere of human experience that allows a transition between freedom and nature to be effected. This answer to the problem of the highest good is distinctive because the causal efficacy of reason in attaining its own demands is preserved. I examine Kant’s view by way of an analysis of his discussion of ‘territory’ and ‘domain’ in the Introduction to the text. (shrink)

Stable neuronal assemblies are generally regarded as neural correlates of mental representations. Their temporal sequence corresponds to the experience of a direction of time, sometimes called the psychological time arrow. We show that the stability of particular, biophysically motivated models of neuronal assemblies, called coupled map lattices, is supported by causal interactions among neurons and obstructed by non-causal or anti-causal interactions among neurons. This surprising relation between causality and stability suggests that those neuronal assemblies that are stable (...) due to causal neuronal interactions, and thus correlated with mental representations, generate a psychological time arrow. Yet this impact of causal interactions among neurons on the directed sequence of mental representations does not rule out the possibility of mentally less efficacious non-causal or anti-causal interactions among neurons. (shrink)

Formal thinking about certainty/uncertainty gained greater focus in scientific domains with the advent of particle physics and quantum mechanics. Concern with the exact predictability of events under guidance from scientific determinism led to speculation, then acknowledgement of quantum indeterminacy. But distinctions were made between what is physically indeterminate out there and what is indeterminable by human observation or in human action--over here, on the inside, right now. The implications of these insights into indeterminacy and indeterminabilities for practical and theoretical knowledge (...) span physics, philosophy, ontology, causality, and the philosophy of mind. In this book, contributors from a range of disciplines consider the concept of indeterminacy and a few varieties of indeterminability, with attention to the distinctions between the two phenomena, appropriate approaches for examining both, and the differences vis-à-vis uncertainty, vagueness, and ambiguity. (shrink)

In a series of papers, we have argued that causal cognition has coevolved with the use of various tools. Animals use tools, but only as extensions of their own bodies, while humans use tools that act at a distance in space and time. This means that we must learn new types of causal mappings between causes and effects. The aim of this article is to account for what is required for such learning of causal relations. Following a (...) proposal by Grush and Springle, we argue that learning of inverse mappings from effects to causes is central. Learning such mappings also involves constraints based on monotonicity, continuity and convexity. In order for causal thinking to extend beyond space and time, mental simulations are required that predict the effects of actions. More advanced forms of causal reasoning involve more complicated forms of simulations. (shrink)

When explaining the causes of human behavior, genes are often given a special status. They are thought to relate to an intrinsic human 'essence', and essentialist biases have been shown to skew the way in which causation is assessed. Causal reasoning in general is subject to other pre-existing biases, including beliefs about normativity and morality. In this synthesis we show how factors which influence causal reasoning can be mapped to a framework of genetic essentialism, which reveals both the (...) shared and unique factors underpinning biases in causal reasoning and genetic essentialism. This comparison identifies overlooked areas of research which could provide fruitful investigation, such as whether normative assessments of behaviors influence the way that genetic causes are ascribed or endorsed. We also outline the importance of distinguishing reasoning processes regarding genetic causal influences on one's self versus others, as different cognitive processes and biases are likely to be at play. (shrink)

We describe an augmented topological map as an alternative for the proposed bicoded map. Inverting causality, the special nature of the vertical dimension is then no longer fixed a priori and the cause of specific navigation behavior, but a consequence of the combination of the specific geometry of the experimental environment and the motor capabilities of the experimental animals.

Why was there a meltdown at the Fukushima power plant? Why do some people get cancer and not others? Why is global warming happening? Why does one person get depressed in the face of life's vicissitudes while another finds resilience? Questions like these--questions of causality--form the basis of modern scientific inquiry, posing profound intellectual and methodological challenges for researchers in the physical, natural, biomedical, and social sciences. In this groundbreaking book, noted psychiatrist and author Peter Rabins offers a conceptual framework (...) for analyzing daunting questions of causality. Navigating a lively intellectual voyage between the shoals of strict reductionism and relativism, Rabins maps a three-facet model of causality and applies it to a variety of questions in science, medicine, economics, and more. Throughout this book, Rabins situates his argument within relevant scientific contexts, such as quantum mechanics, cybernetics, chaos theory, and epigenetics. A renowned communicator of complex concepts and scientific ideas, Rabins helps readers stretch their minds beyond the realm of popular literary tipping points, blinks, and freakonomic explanations of the world. (shrink)

People implicitly associate the “past” and “future” with “front” and “back” in their minds according to their cultural attitudes toward time. As the temporal focus hypothesis proposes, future-oriented people tend to think about time according to the future-in-front mapping, whereas past-oriented people tend to think about time according to the past-in-front mapping. Whereas previous studies have demonstrated that culture exerts an important influence on people's implicit spatializations of time, we focus specifically on religion, a prominent layer of culture, as potential (...) additional influence on space-time mappings. In Experiment 1 and 2, we observed a difference between the two religious groups, with Buddhists being more past-focused and more frequently conceptualizing the past as ahead of them and the future as behind them, and Taoists more future-focused and exhibiting the opposite space-time mapping. In Experiment 3, we administered a religion prime, in which Buddhists were randomly assigned to visualize the picture of the Buddhas of the Past or the Future. Results showed that the pictorial icon of Dipamkara increased participants' tendency to conceptualize the past as in front of them. In contrast, the pictorial icon of Maitreya caused a dramatic increase in the rate of future-in-front responses. In Experiment 4, the causal effect of religion on implicit space-time mappings was replicated in atheists. Taken together, these findings provide converging evidence for the hypothesized causal role of religion for temporal focus in determining space-time mappings. (shrink)

Previous studies have shown a robust bias to express the goal path over the source path when describing events. Motivated by linguistic theory, this study manipulated the causal structure of events and measured the extent to which adults and 3.5- to 4-year-old English-speaking children included the goal and source in their descriptions. We found that both children's and adults’ encoding of the source increased for events in which the source caused the motion of the figure compared to nearly identical (...) events in which the source played no such causal role. However, a goal bias persisted overall for both causal and noncausal motion events. These findings suggest that although the goal bias in language is highly robust, properties of the source influence its likelihood of being encoded in language, thus shedding light on how properties of an event can influence the mapping of event components into language. (shrink)

forthcoming in New Essays on the Explanation of Action Abstract Philosophers influenced by Wittgenstein rejected the idea that the explanatory power of our ordinary interpretive practices is to be found in law-governed, causal relations between items to which our everyday mental terms allegedly refer. Wittgenstein and those he inspired pointed to differences between the explanations provided by the ordinary employment of mental expressions and the style of causal explanation characteristic of the hard sciences. I believe, however, that the (...) particular non-causalism espoused by the Wittgensteinians is today ill- understood. The position does not, for example, find its place on a map that charts the territory disputed by mental realists and their irrealist opponents. In this paper, I take a few steps toward reintroducing this ill-understood position by sketching my own understanding of it and explaining why it fits so uncomfortably within the contemporary metaphysical landscape. (shrink)

The nature of abstract and concrete semantics and differences between them have remained a debated issue in psycholinguistic and cognitive studies for decades. Most of the available behavioral and neuroimaging studies reveal distinctions between these two types of semantics, typically associated with a so-called “concreteness effect.” Many attempts have been made to explain these differences using various approaches, from purely theoretical linguistic and cognitive frameworks to neuroimaging experiments. In this brief overview, we will try to provide a snapshot of these (...) diverse views and relationships between them and highlight the crucial issues preventing this problem from being solved. We will argue that one potentially beneficial way forward is to identify the neural mechanisms underpinning acquisition of the different types of semantics (e.g., by using neurostimulation techniques to establish causal relationships), which may help explain the distinctions found between the processing of concrete and abstract semantics. (shrink)

Is there a problem of causal exclusion between micro- and macro-level physical properties? I argue (following Kim) that the sorts of properties that in fact are in competition are macro properties, viz., the property of a (macro-) system of 'having such-and-such macro properties' (call this a 'macro-structural property') and the property of the same system of 'being constituted by such-and-such a micro- structure' (call this a 'micro-structural property'). I show that there are cases where, for lack of reducibility, there (...) is a prima facie intra-level causal competition between the two kinds of properties. The problem can be resolved without giving up on the causal efficacy of the macro-structural properties if we understand instances of macro-structural properties to be parts of micro-structural property instances. The parthood relation between both kinds of property instances can be mapped onto the way physical theory deals with the relation of their descriptions in the framework of perturbation theory. The application of this framework to the problem of emergent properties is discussed. (shrink)

Not a day passes over society where the immediate expressions of violence are not widely propagated and subsequently witnessed through cultural or political mediums. Such depictions, accounts, scenes, have been uniquely framed as a lexis of ‘subjective violence’; reactions or evident illustrations of descent in physical form. Amidst their over-representation is a lapse of measured attention given to the pretext amounting to said outbursts. Seldom is the objective, if at all, contextualized as a catalytic toward the subjective. The following work (...) suggests that a violence exists amidst society that goes substantively under-analyzed thereby negating an ability to specifically address and, therefore, challenge its causality. While recognizing the importance of such research, a movement beyond affectual approaches of theorizing violence is needed through a complimentarily mapping of how distal relations of power influence, impact, and sustain enmity. What makes this discussion further dynamic is the ironic transparency of causation. Rather than a phenomenon of concealment, conventional dynamics of authority and influence exert control through, what could be argued to be, an invisibility of visibility. Supporting an addendum to theorizing violence may, then, enable a more holistic recognition that can assist an articulate response toward both subjective and objective expressions of violence. (shrink)

Events can be modeled through a geometric approach, representing event structures in terms of spaces and mappings between spaces. At least two spaces are needed to describe an event, an action space and a result space. In this article, we invoke general mathematical structures in order to develop this geometric perspective. We focus on three cognitive processes that are crucially involved in events: causal thinking, control of action and learning by generalization. These cognitive processes are supported by three corresponding (...) mathematical properties: monotonicity (that we relate to qualitative causal thinking and allows extrapolation); continuity (that plays a key role in our activities of action control); and convexity (that facilitates generalization and the categorization of events, and enables interpolation). We define how such properties constrain events representations and relate them to thinking about events. We discuss the relevance of the three constraints for event segmentation and explore the implications of such constraints for semantics. We conclude by a discussion that relates our approach to other accounts of events. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:51. HOW NOT TO REFUTE HUME'S THEORY OF CAUSALITY: A REPLY TO GRAY Mr. Robert Gray's alleged refutation of Hume's theory of causality does not strike me as being in reality conclusive. The essential element in his alleged refutation, if I have understood it correctly, is that when two billiard balls strike one another and stop - a paradigm of cause and effect - the striking and the stopping (...) constitute one event as opposed to two. They occupy, as a result, one and the same time, a state of affairs inconsistent with the Humean view that the cause immediately precedes the effect. But, surely, they would, if they are the same event, occupy by parity of reasoning one and the same position. For Hume's theory of space and time, as Gray describes it, implies that there is a one-to-one mapping between positions and times. If, therefore, their being the same event implies that they occupy one and the same time, it would also imply that they occupy one and the same position. And if they occupy the same position, they are not spatially contiguous, a state of affairs inconsistent with the Humean view that the cause is spatially contiguous to the effect. A Humean solution in both cases seems clear. It is to allow that the striking and stopping of the billiard balls are the same event and to seek its cause in their moving towards one another, i.e. to seek it in billiard ball A's being at A, and billiard ball B's being at B,, where both A, and B, are spatially contiguous with and immediately precede the striking and stopping of the respective billiard balls B and A. Gray resists this solution, but only because he is implicitly committed to the anti-Humean view that one and the same event can occupy two different positions at one and the same time. As a result, where A designates the 52. position where billiard ball A strikes billiard ball B and stops it and B designates the position where billiard ball B strikes billiard ball A and stops it - this being simply a re-descriptiön in Gray's view of what happens in the single event of two billiard balls striking one another and stopping - he holds that A is different from B. If A is different from B, then by relocating the cause of billiard ball A's stopping at B, we have sacrificed the spatial contiguity of cause and effect. For B will intervene between position B,, that of the cause, and A, that of the effect. And the same will hold with obvious adjustments when we relocate the cause of billiard ball B's stopping at A,. Fortunately, however, Hume need only reply that A is one and the same as B. Indeed, if he is to be consistent with his theory of space and time, this must be his reply. This reply, moreover, is necessary to Hume's explanation of how the reciprocal striking of billiard ball A and billiard ball B can exist in the first place. Such a phenomenon requires a point of contact, a point common to a part of both billiard balls. This point of contact, it should be clear, is provided by the point designated by both A and B. Robert A. Imlay University of Toronto "A Refutation of Hume's Theory of Causality," Hume Studies, Vol. II (1976), pp. 76-85.... (shrink)

Given that an analysis of disposition ascription cannot be made in terms of a simple subjunctive conditional, we present a multiply qualified conditional analysis that places disposition ascription within an implicit fundamental causal conceptual typography within which a disposition ascription is embedded, framed, and understood. By placing the multiply qualified analysis within an implicit causal matrix involving a focal cause, pathway of influence, mechanism of action, contributing/partial cause, mediator, extrinsic moderator,, intrinsic moderator, and manifestation, we show how this (...) analysis evades counterexamples and arguments raised against the simple conditional analysis. We then indicate how the causal conceptual landscape provides a roadmap for unpacking and explicating parameters of the ceteris paribus qualifier to acquit the analysis of charges of being vacuous or irredeemably vague. (shrink)

The paper investigates Aristotle's simulation of the embryo (zygote) by a gear wheel mechanism. By this technical simulation of a natural thing Aristotle pursues an epistemic end, viz. to gain information on the efficient cause of embryonal development. Aristotle verifies the conjectured, yet unknown efficient cause of this natural process by means of a distinctive mapping of the artifact onto the embryo. The paper aims to show that Aristotle, to achieve this verification, tackles a calculus of relations with a semantics (...) of causal content, providing logicocausal deductions, an ancient causal analogue of the truth-preserving calculus of relations. The elements of this Aristotelian causal calculus are those relations among the components of composite things that Aristotle holds to be causal. To these causal relations he applies various operations, set extension and set restriction, substitution, generalization and particularization, in such a way that the causal content of the relations transformed is preserved, thus affording deductions of relations from relations that are valid in respect to their causal content. The paper finally aims to show that causal calculus, working well when applied to the gear wheel mechanism and the embryo, is not sound in every application. (shrink)

This book is an empirically informed investigation of the philosophical problem of mental causation, and simultaneously a philosophical investigation of the status of cognitive scientific generalisations. If there is such a thing as mental causation, and if we can classify the mental states involved in these causes in a way useful for making predictions and giving scientific explanations, then these states will be natural kinds. The first task, then, is to show that there is an account of natural kindhood that (...) can accommodate cognitive kinds. The second task is to say how the scientific statements made using these mental kinds are not susceptible to being reduced to statements about physical kinds, and in fact require taking into account facts at many levels of explanation, including the biological and social levels. Lastly, the case will be made for Virtual Machine Functionalism being the correct account of the relationship between cognitive states and the broader physical world. (shrink)

While the past century of neuroscientific research has brought considerable progress in defining the boundaries of the human cerebral cortex, there are cases in which the demarcation of one area from another remains fuzzy. Despite the existence of clearly demarcated areas, examples of gradual transitions between areas are known since early cytoarchitectonic studies. Since multi-modal anatomical approaches and functional connectivity studies brought renewed attention to the topic, a better understanding of the theoretical and methodological implications of fuzzy boundaries in brain (...) science can be conceptually useful. This article provides a preliminary conceptual framework to understand this problem by applying philosophical theories of vagueness to three levels of neuroanatomical research. For the first two levels (cytoarchitectonics and fMRI studies), vagueness will be distinguished from other forms of uncertainty, such as imprecise measurement or ambiguous causal sources of activation. The article proceeds to discuss the implications of these levels for the anatomical study of connectivity between cortical areas. There, vagueness gets imported into connectivity studies since the network structure is dependent on the parcellation scheme and thresholds have to be used to delineate functional boundaries. Functional connectivity may introduce an additional form of vagueness, as it is an organizational principle of the brain. The article concludes by discussing what steps are appropriate to define areal boundaries more precisely. (shrink)

In this paper, we examine the extent to which the concept of emergence can be applied to questions about the nature and moral justification of territorial borders. Although the term is used with many different senses in philosophy, the concept of “weak emergence”—advocated by, for example, Sawyer (2002, 2005) and Bedau (1997)—is especially applicable, since it forces a distinction between prediction and explanation that connects with several issues in the dis-cussion of territory. In particular, we argue, weak emergentism about borders (...) allows us to distinguish between (a) using a theory of territory to say where a border should be drawn, and (b) looking at an existing border and saying whether or not it is justified (Miller, 2012; Nine, 2012; Stilz, 2011). Many authors conflate these two factors, or identify them by claiming that having one without the other is in some sense incoherent. But on our account—given the concept of emergence—one might unproblematically be able to have (b) without (a); at the very least, the distinction between these two issues is much more significant than has often been recognised, and more importantly gives us some reason to prefer “statist” as opposed to “cultural” theories of territorial borders. We conclude with some further reflections on related matters concerning, firstly, the apparent causal powers of borders, and secondly, the different ways in which borders are physically implemented (e.g., land vs. water). (shrink)

The physical environment leads to a thermal sensation that is perceived and appraised by occupants. The present study focuses on the relationship between sensation and evaluation. We asked 166 people to recall a thermal event from their recent past. They were then asked how they evaluated this experience in terms of 10 different emotions (frustrated, resigned, dislike, indifferent, angry, anxious, liking, joyful, regretful, proud). We tested whether four psychological factors (appraisal dimensions) could be used to predict the ensuing emotions, as (...) well as comfort, acceptability, and sensation. The four dimensions were: the Conduciveness of the event, who/what caused the event (Causality), who had control (Agency), and whether the event was expected (Expectations). These dimensions, except for Expectations, were good predictors of the reported emotions. Expectations, however, predicted the reported thermal sensation, its acceptability, and ensuing comfort. The more expected an event was, the more uncomfortable a person felt, and the less likely they reported a neutral thermal sensation. Together, these results support an embodied view of how subjective appraisals affect thermal experience. Overall, we show that appraisal dimensions mediate occupants' evaluation of their thermal sensation, which suggests an additional method for understanding psychological adaption. (shrink)

In this paper we develop test cases to adjudicate between dual-process and the causal mapping explanations of order effects. Using dilemmas with minimized emotional force, we explore new conditions for order effects to occur. Overall, the results support causal model theory. We produced novel evidence that order effects extend not only to cases with low emotional engagement, but also to specialized judgments about whether an action violates a rule. However, when objects are sacrificed instead of persons the order (...) effect either disappears or becomes symmetrical, contrary to previous theorizing that it is an asymmetrical transfer effect. Causal model theory needs to be developed to include interplays between the moral status of sacrificed entities and computational models of causal mapping. Symmetric order effects remain a puzzle, motivating future research. Though we do not know how to explain them yet, we discuss how symmetric order effects can influence policy decision making. (shrink)

After sketching the historical development of “emergence” and noting several recent problems relating to “emergent properties”, this essay proposes that properties may be either “emergent” or “mergent” and either “intrinsic” or “extrinsic”. These two distinctions define four basic types of change: stagnation, permanence, flux, and evolution. To illustrate how emergence can operate in a purely logical system, the Geometry of Logic is introduced. This new method of analyzing conceptual systems involves the mapping of logical relations onto geometrical figures, following either (...) an analytic or a synthetic pattern (or both together). Evolution is portrayed as a form of discontinuous change characterized by emergent properties that take on an intrinsic quality with respect to the object(s) or proposition(s) involved. Causal leaps, not continuous development, characterize the evolution of human life in a developing foetus, of a thought out of certain brain states, of a new idea (or insight) out of ordinary thoughts, and of a great person out of a set of historical experiences. The tendency to assume that understanding evolutionary change requires a step-by-step explanation of the historical development that led to the appearance of a certain emergent property is thereby discredited. (shrink)