Causal Reasoning

Edited by Alexander Gebharter (Ludwig Maximilians Universität, München)
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  1. Is Causal Reasoning Harder Than Probabilistic Reasoning?Milan Mossé, Duligur Ibeling & Thomas Icard - forthcoming - Review of Symbolic Logic:1-24.
  2. Getting Counterfactuals Right: The Perspective of the Causal Reasoner.Elena Popa - 2022 - Synthese 200 (1):1-18.
    This paper aims to bridge philosophical and psychological research on causation, counterfactual thought, and the problem of backtracking. Counterfactual approaches to causation such as that by Lewis have ruled out backtracking, while on prominent models of causal inference interventionist counterfactuals do not backtrack. However, on various formal models, certain backtracking counterfactuals end up being true, and psychological evidence shows that people do sometimes backtrack when answering counterfactual questions in causal contexts. On the basis of psychological research, I argue that while (...)
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  3. The Nonidentity Problem is an Artifact of Faulty Causal Reasoning.Peter Gildenhuys - 2021 - Revista Portuguesa de Filosofia 77 (4):1339-1354.
    This paper argues that the nonidentity problem is really an artifact of faulty causal reasoning. In order to solve the nonidentity problem, we must determine that an agent causes a loss of happiness to another agent by means of an action that also causes the victim to exist. Woodward’s test for actual causation yields just this result. Equally crucial to solving the problem is the recognition that harms must be intentional and that intentionality is a function of norm-violation; this latter (...)
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  4. The Communicative Functions of Metaphors Between Explanation and Persuasion.Fabrizio Macagno & Maria Grazia Rossi - 2021 - In Fabrizio Macagno & Alessandro Capone (eds.), Inquiries in philosophical pragmatics. Theoretical developments. Cham, Switzerland: pp. 171-191.
    In the literature, the pragmatic dimension of metaphors has been clearly acknowledged. Metaphors are regarded as having different possible uses, and in particular, they are commonly viewed as instruments for pursuing persuasion. However, an analysis of the specific conversational purposes that they can be aimed at achieving in a dialogue and their adequacy thereto is still missing. In this paper, we will address this issue focusing on the distinction between the explanatory and persuasive goal. The difference between explanation and persuasion (...)
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  5. Ordinary Causal Attributions, Norms, and Gradability.Jan Garcia Olier & Markus Kneer - manuscript
    There is a large literature exploring the effect of norms on the attribution of causation. Empirical research on this so-called “norm effect” has predominantly focused on two data points: A situation in which an agent violates a salient norm, and one in which there is no violation of a salient norm. Since the phenomenon is understood in bivalent terms (norm infraction vs. no norm infraction), most explanations thereof have the same structure. In this paper, we report several studies (total N=479) (...)
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  6. Abductive, Causal, and Counterfactual Conditionals Under Incomplete Probabilistic Knowledge.Niki Pfeifer & Lena Tulkki - 2017 - In G. Gunzelmann, A. Howes, T. Tenbrink & E. Davelaar (eds.), Proceedings of the 39th Cognitive Science Society Meeting. pp. 2888-2893.
    We study abductive, causal, and non-causal conditionals in indicative and counterfactual formulations using probabilistic truth table tasks under incomplete probabilistic knowledge (N = 80). We frame the task as a probability-logical inference problem. The most frequently observed response type across all conditions was a class of conditional event interpretations of conditionals; it was followed by conjunction interpretations. An interesting minority of participants neglected some of the relevant imprecision involved in the premises when inferring lower or upper probability bounds on the (...)
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  7. Applying Evidential Pluralism to the Social Sciences.Yafeng Shan & Jon Williamson - 2021 - European Journal for Philosophy of Science 11 (4):1-27.
    Evidential Pluralism maintains that in order to establish a causal claim one normally needs to establish the existence of an appropriate conditional correlation and the existence of an appropriate mechanism complex, so when assessing a causal claim one ought to consider both association studies and mechanistic studies. Hitherto, Evidential Pluralism has been applied to medicine, leading to the EBM+ programme, which recommends that evidence-based medicine should systematically evaluate mechanistic studies alongside clinical studies. This paper argues that Evidential Pluralism can also (...)
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  8. Feeling the Past: Beyond Causal Content.Gerardo Viera - 2021 - Estudios de Filosofía 64:173-188.
    Memories often come with a feeling of pastness. The events we remember strike us as having occurred in our past. What accounts for this feeling of pastness? In his recent book, Memory: A self-referential account, Jordi Fernández argues that the feeling of pastness cannot be grounded in an explicit representation of the pastness of the remembered event. Instead, he argues that the feeling of pastness is grounded in the self-referential causal content of memory. In this paper, I argue that this (...)
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  9. Causal, Teleological and Evolutionary Explanation.David L. Thompson - manuscript
    Explanation is a human activity. Teleological, causal, and evolutionary explanations are all valid forms of responding to particular puzzlements. Reductionism incorrectly assumes there is one absolute explanation. While causal explanation appeals primarily to necessity, evolutionary explanation is based largely on contingency.
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Causal Modeling
  1. Molinism: Explaining Our Freedom Away.Nevin Climenhaga & Daniel Rubio - 2022 - Mind 131 (522):459-485.
    Molinists hold that there are contingently true counterfactuals about what agents would do if put in specific circumstances, that God knows these prior to creation, and that God uses this knowledge in choosing how to create. In this essay we critique Molinism, arguing that if these theses were true, agents would not be free. Consider Eve’s sinning upon being tempted by a serpent. We argue that if Molinism is true, then there is some set of facts that fully explains both (...)
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  2. Causal Modeling Semantics for Counterfactuals with Disjunctive Antecedents.Giuliano Rosella & Jan Sprenger - manuscript
    This paper applies Causal Modeling Semantics (CMS, e.g., Galles and Pearl 1998; Pearl 2000; Halpern 2000) to the evaluation of the probability of counterfactuals with disjunctive antecedents. Standard CMS is limited to evaluating (the probability of) counterfactuals whose antecedent is a conjunction of atomic formulas. We extend this framework to disjunctive antecedents, and more generally, to any Boolean combinations of atomic formulas. Our main idea is to assign a probability to a counterfactual ( A ∨ B ) > C at (...)
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  3. A New Halpern-Pearl Definition of Actual Causality by Appealing to the Default World.Fan Zhu - forthcoming - Axiomathes:1-20.
    Halpern and Hitchcock appealed to the normality of witness worlds to solve the problem of isomorphism in the Halpern-Pearl definition of actual causality. This paper first proposes a new isomorphism counterexample, called “bogus permission,” to show that their approach is unsuccessful. Then, to solve the problem of isomorphism, I propose a new improvement over the Halpern-Pearl definition by introducing default worlds. Finally, I demonstrate that my new definition can resolve more potential counterexamples than similar approaches in the current literature, including (...)
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  4. How to Trace a Causal Process.J. Dmitri Gallow - manuscript
    According to the theory developed here, we may trace out the processes emanating from a cause in such a way that any consequence lying along one of these processes counts as an effect of the cause. This theory gives intuitive verdicts in a diverse range of problem cases from the literature. Its claims about causation will never be retracted when we include additional variables in our model. And it validates some plausible principles about causation, including Sartorio's 'Causes as Difference Makers' (...)
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  5. Structural Decision Theory.Tung-Ying Wu - 2021 - Philosophy of Science 88 (5):951-960.
    Judging an act’s causal efficacy plays a crucial role in causal decision theory. A recent development appeals to the causal modeling framework with an emphasis on the analysis of intervention based on the causal Bayes net for clarifying what causally depends on our acts. However, few writers have focused on exploring the usefulness of extending structural causal models to decision problems that are not ideal for intervention analysis. The thesis concludes that structural models provide a more general framework for rational (...)
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  6. Causation and the Problem of Disagreement.Enno Fischer - 2021 - Philosophy of Science 88 (5):773-783.
    This article presents a new argument for incorporating a distinction between default and deviant values into the formalism of causal models. The argument is based on considerations about how causal reasoners should represent disagreement over causes, and it is defended against an objection that has been raised against earlier arguments for defaults.
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  7. Correction to: Causal Sufficiency and Actual Causation.Sander Beckers - 2021 - Journal of Philosophical Logic 50 (6):1375-1375.
    A Correction to this paper has been published: https://doi.org/10.1007/s10992-021-09632-6.
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  8. Realism Without Interphenomena: Reichenbach’s Cube, Sober’s Evidential Realism, and Quantum.Florian J. Boge - 2021 - International Studies in the Philosophy of Science 33 (4):231-246.
    In ‘Reichenbach's cubical universe and the problem of the external world’, Elliott Sober attempts a refutation of solipsism à la Reichenbach. I here contrast Sober's line of argument with observati...
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  9. Robustness and Modularity.Trey Boone - forthcoming - British Journal for the Philosophy of Science.
    Functional robustness refers to a system’s ability to maintain a function in the face of perturbations to the causal structures that support performance of that function. Modularity, a crucial element of standard methods of causal inference and difference-making accounts of causation, refers to the independent manipulability of causal relationships within a system. Functional robustness appears to be at odds with modularity. If a function is maintained despite manipulation of some causal structure that supports that function, then the relationship between that (...)
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  10. A Logical Theory of Causality.Alexander Bochman - 2021 - Cambridge, Massachusetts: MIT Press.
    "The first book that provides a systematic and rigorous logical theory of causality"--.
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  11. Interventionism and Over-Time Causal Analysis in Social Sciences.Tung-Ying Wu - 2022 - Philosophy of the Social Sciences 52 (1-2):3-24.
    The interventionist theory of causation has been advertised as an empirically informed and more nuanced approach to causality than the competing theories. However, previous literature has not yet analyzed the regression discontinuity (hereafter, RD) and the difference-in-differences (hereafter, DD) within an interventionist framework. In this paper, I point out several drawbacks of using the interventionist methodology for justifying the DD and RD designs. However, I argue that the first step towards enhancing our understanding of the DD and RD designs from (...)
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  12. Measuring the Biases That Matter: The Ethical and Causal Foundations for Measures of Fairness in Algorithms.Jonathan Herington & Bruce Glymour - 2019 - Proceedings of the Conference on Fairness, Accountability, and Transparency 2019:269-278.
    Measures of algorithmic bias can be roughly classified into four categories, distinguished by the conditional probabilistic dependencies to which they are sensitive. First, measures of "procedural bias" diagnose bias when the score returned by an algorithm is probabilistically dependent on a sensitive class variable (e.g. race or sex). Second, measures of "outcome bias" capture probabilistic dependence between class variables and the outcome for each subject (e.g. parole granted or loan denied). Third, measures of "behavior-relative error bias" capture probabilistic dependence between (...)
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  13. Actual Causation.Enno Fischer - 2021 - Dissertation, Leibniz Universität Hannover
    In this dissertation I develop a pluralist theory of actual causation. I argue that we need to distinguish between total, path-changing, and contributing actual causation. The pluralist theory accounts for a set of example cases that have raised problems for extant unified theories and it is supported by considerations about the various functions of causal concepts. The dissertation also analyses the context-sensitivity of actual causation. I show that principled accounts of causal reasoning in legal inquiry face limitations and I argue (...)
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  14. Causal Counterfactuals Without Miracles or Backtracking.J. Dmitri Gallow - manuscript
    If the laws are deterministic, then standard theories of counterfactuals are forced to reject at least one of the following conditionals: 1) had you chosen differently, there would not have been a violation of the laws of nature; and 2) had you chosen differently, the initial conditions of the universe would not have been different. On the relevant readings---where we hold fixed factors causally independent of your choice---both of these conditionals appear true. And rejecting either one leads to trouble for (...)
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  15. Causal Sufficiency and Actual Causation.Sander Beckers - 2021 - Journal of Philosophical Logic 50 (6):1341-1374.
    Pearl opened the door to formally defining actual causation using causal models. His approach rests on two strategies: first, capturing the widespread intuition that X = x causes Y = y iff X = x is a Necessary Element of a Sufficient Set for Y = y, and second, showing that his definition gives intuitive answers on a wide set of problem cases. This inspired dozens of variations of his definition of actual causation, the most prominent of which are due (...)
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  16. An Interventionist’s Guide to Exotic Choice.Reuben Stern - 2021 - Mind 130 (518):537-566.
    In this paper, I use interventionist causal models to identify some novel Newcomb problems, and subsequently use these problems to refine existing interventionist treatments of causal decision theory. The new Newcomb problems that make trouble for existing interventionist treatments involve so-called ‘exotic choice’—that is, decision-making contexts where the agent has evidence about the outcome of her choice. I argue that when choice is exotic, the interventionist can adequately capture causal decision-theoretic reasoning by introducing a new interventionist approach to updating on (...)
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  17. Causal Feature Learning for Utility-Maximizing Agents.David Kinney & David Watson - 2020 - In International Conference on Probabilistic Graphical Models. pp. 257–268.
    Discovering high-level causal relations from low-level data is an important and challenging problem that comes up frequently in the natural and social sciences. In a series of papers, Chalupka etal. (2015, 2016a, 2016b, 2017) develop a procedure forcausal feature learning (CFL) in an effortto automate this task. We argue that CFL does not recommend coarsening in cases where pragmatic considerations rule in favor of it, and recommends coarsening in cases where pragmatic considerations rule against it. We propose a new technique, (...)
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  18. Three Concepts of Actual Causation.Enno Fischer - forthcoming - British Journal for the Philosophy of Science.
    I argue that we need to distinguish between three concepts of actual causation: total, path-changing, and contributing actual causation. I provide two lines of argument in support of this account. First, I address three thought experiments that have been troublesome for unified accounts of actual causation, and I show that my account provides a better explanation of corresponding causal intuitions. Second, I provide a functional argument: if we assume that a key purpose of causal concepts is to guide agency, we (...)
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  19. The Causal Structure of Natural Kinds.Olivier Lemeire - 2021 - Studies in History and Philosophy of Science Part A 85:200-207.
    One primary goal for metaphysical theories of natural kinds is to account for their epistemic fruitfulness. According to cluster theories of natural kinds, this epistemic fruitfulness is grounded in the regular and stable co- occurrence of a broad set of properties. In this paper, I defend the view that such a cluster theory is insufficient to adequately account for the epistemic fruitfulness of kinds. I argue that cluster theories can indeed account for the projectibility of natural kinds, but not for (...)
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  20. Running Up the Flagpole to See If Anyone Salutes: A Response to Woodward on Causal and Explanatory Asymmetries.Katrina Elliott & Marc Lange - forthcoming - Theoria : An International Journal for Theory, History and Fundations of Science.
    Does smoke cause fire or does fire cause smoke? James Woodward’s “Flagpoles anyone? Causal and explanatory asymmetries” argues that various statistical independence relations not only help us to uncover the directions of causal and explanatory relations in our world, but also are the worldly basis of causal and explanatory directions. We raise questions about Woodward’s envisioned epistemology, but our primary focus is on his metaphysics. We argue that any alleged connection between statistical (in)dependence and causal/explanatory direction is contingent, at best. (...)
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  21. Homeostatic Property Cluster Theory Without Homeostatic Mechanisms: Two Recent Attempts and Their Costs.Yukinori Onishi & Davide Serpico - 2022 - Journal for General Philosophy of Science / Zeitschrift für Allgemeine Wissenschaftstheorie (N/A):61-82.
    The homeostatic property cluster theory is widely influential for its ability to account for many natural-kind terms in the life sciences. However, the notion of homeostatic mechanism has never been fully explicated. In 2009, Carl Craver interpreted the notion in the sense articulated in discussions on mechanistic explanation and pointed out that the HPC account equipped with such notion invites interest-relativity. In this paper, we analyze two recent refinements on HPC: one that avoids any reference to the causes of the (...)
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  22. The Counteridentical Account of Explanatory Identities.Isaac Wilhelm - 2021 - Journal of Philosophy 118 (2):57-78.
    Many explanations rely on identity facts. In this paper, I propose an account of how identity facts explain: roughly, the fact that A is identical to B explains another fact whenever that other fact depends, counterfactually, on A being identical to B. As I show, this account has many virtues. It avoids several problems facing accounts of explanatory identities, and when precisified using structural equations, it can be used to defend interventionist accounts of causation against an objection.
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  23. Causal Inference From Noise.Nevin Climenhaga, Lane DesAutels & Grant Ramsey - 2021 - Noûs 55 (1):152-170.
    "Correlation is not causation" is one of the mantras of the sciences—a cautionary warning especially to fields like epidemiology and pharmacology where the seduction of compelling correlations naturally leads to causal hypotheses. The standard view from the epistemology of causation is that to tell whether one correlated variable is causing the other, one needs to intervene on the system—the best sort of intervention being a trial that is both randomized and controlled. In this paper, we argue that some purely correlational (...)
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  24. Correlation Isn’T Good Enough: Causal Explanation and Big Data. [REVIEW]Frank Cabrera - 2021 - Metascience 30 (2):335-338.
    A review of Gary Smith and Jay Cordes: The Phantom Pattern Problem: The Mirage of Big Data. New York: Oxford University Press, 2020.
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  25. Causal Complexity, Conditional Independence, and Downward Causation.James Woodward - 2020 - Philosophy of Science 87 (5):857-867.
    This article defends the notion of downward causation, relating it to a notion of conditional independence.
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  26. Bayesian Networks and Causal Ecumenism.David Kinney - forthcoming - Erkenntnis:1-26.
    Proponents of various causal exclusion arguments claim that for any given event, there is often a unique level of granularity at which that event is caused. Against these causal exclusion arguments, causal ecumenists argue that the same event or phenomenon can be caused at multiple levels of granularity. This paper argues that the Bayesian network approach to representing the causal structure of target systems is consistent with causal ecumenism. Given the ubiquity of Bayesian networks as a tool for representing causal (...)
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  27. A Causal Safety Criterion for Knowledge.Jonathan Vandenburgh - manuscript
    Safety purports to explain why cases of accidentally true belief are not knowledge, addressing Gettier cases and cases of belief based on statistical evidence. However, numerous examples suggest that safety fails as a condition on knowledge: a belief can be safe even when one's evidence is clearly insufficient for knowledge and knowledge is compatible with the nearby possibility of error, a situation ruled out by the safety condition. In this paper, I argue for a new modal condition designed to capture (...)
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  28. Causal Structures in Language and Thought.Eleonore Neufeld - 2020 - Dissertation, University of Southern California
    This dissertation defends the view that concepts encode causal information and, for the first time, applies this view to a range of topics in the philosophy of language and social philosophy. In my first chapter (“Cognitive Essentialism and the Structure of Concepts”), I survey the current empirical and theoretical literature on causal-essentialist theories of concepts. In my second chapter (“Meaning Externalism and Causal Model Theory”), I propose an account of natural kind concepts according to which they encode statistical information of (...)
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  29. The Structure of Epistemic Probabilities.Nevin Climenhaga - 2020 - Philosophical Studies 177 (11):3213-3242.
    The epistemic probability of A given B is the degree to which B evidentially supports A, or makes A plausible. This paper is a first step in answering the question of what determines the values of epistemic probabilities. I break this question into two parts: the structural question and the substantive question. Just as an object’s weight is determined by its mass and gravitational acceleration, some probabilities are determined by other, more basic ones. The structural question asks what probabilities are (...)
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  30. Cyclic and Multilevel Causation in Evolutionary Processes.Jonathan Warrell & Mark Gerstein - 2020 - Biology and Philosophy 35 (5):1-36.
    Many models of evolution are implicitly causal processes. Features such as causal feedback between evolutionary variables and evolutionary processes acting at multiple levels, though, mean that conventional causal models miss important phenomena. We develop here a general theoretical framework for analyzing evolutionary processes drawing on recent approaches to causal modeling developed in the machine-learning literature, which have extended Pearls do-calculus to incorporate cyclic causal interactions and multilevel causation. We also develop information-theoretic notions necessary to analyze causal information dynamics in our (...)
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  31. Quantifying Proportionality and the Limits of Higher-Level Causation and Explanation.Alexander Gebharter & Markus Ilkka Eronen - 2021 - British Journal for the Philosophy of Science.
    Supporters of the autonomy of higher-level causation (or explanation) often appeal to proportionality, arguing that higher-level causes are more proportional than their lower-level realizers. Recently, measures based on information theory and causal modeling have been proposed that allow one to shed new light on proportionality and the related notion of specificity. In this paper we apply ideas from this literature to the issue of higher vs. lower-level causation (and explanation). Surprisingly, proportionality turns out to be irrelevant for the question of (...)
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  32. Stochastic Causality.Domenico Costantini, Maria Carla Galavotti & Patrick Suppes (eds.) - 2001 - CSLI.
    A collection of articles originally presented at two conferences, the first at Ventura Hall, Stanford, in April 1998; and the second at the University of Bologna in September 1999.
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  33. Causal Reasoning and Meno’s Paradox.Melvin Chen & Lock Yue Chew - forthcoming - AI and Society:1-9.
    Causal reasoning is an aspect of learning, reasoning, and decision-making that involves the cognitive ability to discover relationships between causal relata, learn and understand these causal relationships, and make use of this causal knowledge in prediction, explanation, decision-making, and reasoning in terms of counterfactuals. Can we fully automate causal reasoning? One might feel inclined, on the basis of certain groundbreaking advances in causal epistemology, to reply in the affirmative. The aim of this paper is to demonstrate that one still has (...)
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  34. Predicting Motor Imagery Performance From Resting-State EEG Using Dynamic Causal Modeling.Minji Lee, Jae-Geun Yoon & Seong-Whan Lee - 2020 - Frontiers in Human Neuroscience 14.
  35. Causal Models and the Logic of Counterfactuals.Jonathan Vandenburgh - manuscript
    Causal models provide a framework for making counterfactual predictions, making them useful for evaluating the truth conditions of counterfactual sentences. However, current causal models for counterfactual semantics face limitations compared to the alternative similarity-based approach: they only apply to a limited subset of counterfactuals and the connection to counterfactual logic is not straightforward. This paper argues that these limitations arise from the theory of interventions where intervening on variables requires changing structural equations rather than the values of variables. Using an (...)
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  36. On the Concept and Conservation of Critical Natural Capital.C. Tyler DesRoches - 2020 - International Studies in the Philosophy of Science (N/A):1-22.
    Ecological economics is an interdisciplinary science that is primarily concerned with developing interventions to achieve sustainable ecological and economic systems. While ecological economists have, over the last few decades, made various empirical, theoretical, and conceptual advancements, there is one concept in particular that remains subject to confusion: critical natural capital. While critical natural capital denotes parts of the environment that are essential for the continued existence of our species, the meaning of terms commonly associated with this concept, such as ‘non-substitutable’ (...)
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  37. A Tale of Two Deficits: Causality and Care in Medical AI.Melvin Chen - 2020 - Philosophy and Technology 33 (2):245-267.
    In this paper, two central questions will be addressed: ought we to implement medical AI technology in the medical domain? If yes, how ought we to implement this technology? I will critically engage with three options that exist with respect to these central questions: the Neo-Luddite option, the Assistive option, and the Substitutive option. I will first address key objections on behalf of the Neo-Luddite option: the Objection from Bias, the Objection from Artificial Autonomy, the Objection from Status Quo, and (...)
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  38. Search Versus Knowledge in Human Problem Solving: A Case Study in Chess.Matej Guid, Dayana Hristova & Ivan Bratko - 2006 - In Lorenzo Magnani & Claudia Casadio (eds.), Model Based Reasoning in Science and Technology. Logical, Epistemological, and Cognitive Issues. Springer Verlag.
    This paper contributes to the understanding of human problem solving involved in mental tasks that require exploration among alternatives. Examples of such tasks are theorem proving and classical games like chess. De Groot’s largely used model of chess players’ thinking conceptually consists of two stages: detection of general possibilities, or “motifs”, that indicate promising ideas the player may try to explore in a given chess position, and calculation of concrete chess variations to establish whether any of the motifs can indeed (...)
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  39. Free Will, Control, and the Possibility to Do Otherwise From a Causal Modeler’s Perspective.Alexander Gebharter, Maria Sekatskaya & Gerhard Schurz - forthcoming - Erkenntnis:1-18.
    Strong notions of free will are closely connected to the possibility to do otherwise as well as to an agent's ability to causally influence her environment via her decisions controlling her actions. In this paper we employ techniques from the causal modeling literature to investigate whether a notion of free will subscribing to one or both of these requirements is compatible with naturalistic views of the world such as non-reductive physicalism to the background of determinism and indeterminism. We argue that (...)
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  40. Normative commitments, causal structure, and policy disagreement.Georgie Statham - 2020 - Synthese 197 (5):1983-2003.
    Recently, there has been a large amount of support for the idea that causal claims can be sensitive to normative considerations. Previous work has focused on the concept of actual causation, defending the claim that whether or not some token event c is a cause of another token event e is influenced by both statistical and prescriptive norms. I focus on the policy debate surrounding alternative energies, and use the causal modelling framework to show that in this context, people’s normative (...)
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  41. The Compatibility of Differential Equations and Causal Models Reconsidered.Wes Anderson - 2020 - Erkenntnis 85 (2):317-332.
    Weber argues that causal modelers face a dilemma when they attempt to model systems in which the underlying mechanism operates according to some set of differential equations. The first horn is that causal models of these systems leave out certain causal effects. The second horn is that causal models of these systems leave out time-dependent derivatives, and doing so distorts reality. Either way causal models of these systems leave something important out. I argue that Weber’s reasons for thinking causal modeling (...)
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