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  1. Unboxing the Concepts in Newcomb’s Paradox: Causation, Prediction, Decision in Causal Knowledge Patterns.Roland Poellinger - manuscript
    In Nozick’s rendition of the decision situation given in Newcomb’s Paradox dominance and the principle of maximum expected utility recommend different strategies. While evidential decision theory seems to be split over which principle to apply and how to interpret the principles in the first place, causal decision theory seems to go for the solution recommended by dominance. As a reply to the CDT proposal by Wolfgang Spohn, who opts for “one-boxing” by employing reflexive decision graphs, I will draw on the (...)
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  2. Reversing the Norm Effect on Causal Attributions.John Schwenkler & Justin Sytsma - manuscript
    Research in the psychology of causal thinking has frequently revealed effects of normative considerations on causal attributions, where participants tend to assign causality more strongly to agents who violate a norm in bringing about an outcome. Across several experiments, we show that it is possible to reverse this norm effect when the outcome in question is good rather than bad: in these cases, participants assign causality more strongly to a norm-conforming agent than to an agent who violates a norm. We (...)
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  3. Paradoxes of causal loops in spacetime.Nicolae Sfetcu - manuscript
    There is, among some scientists and philosophers, the idea that any theory that would allow the time travel would introduce causal issues. These types of temporal paradoxes can be avoided by the Novikov self-consistency principle or by a variation in the interpretation of many worlds with interacting worlds. The world in which we live has, according to David Lewis, a Parmenidean ontology: "a manifold of events in four dimensions," and the occupants of the world are the 4-dimensional aggregates of the (...)
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  4. Ordinary causal attributions, norms, and gradability.Jan Garcia Olier & Markus Kneer -
    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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  5. The logic of counterfactuals in causal inference.Judea Pearl - manuscript
  6. Plausible Causal Reasoning: A New Approach to Causal Non-monotonic Reasoning.Patrick Marchisella - unknown - Australasian Journal of Logic 18 (4).
    Recent work by Marchisella exposed a gap in the literature on causal non-monotonic reasoning: what is needed is an approach whose primary motivation is the formal representation of the way in which humans typically reason with cause and effect. We extend the work of Marchisella, and propose a new type of causal non-monotonic reasoning, _Plausible Causal Reasoning_, which fills the gap in the literature. We propose some new principles which help characterise Plausible Causal Reasoning, and suggest a family of non-monotonic (...)
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  7. Often Trusted But Never (Properly) Tested: Evaluating Qualitative Comparative Analysis,.Michael Baumgartner & Alrik Thiem - forthcoming - Sociological Methods & Research.
    To date, hundreds of researchers have employed the method of Qualitative Comparative Analysis (QCA) for the purpose of causal inference. In a recent series of simulation studies, however, several authors have questioned the correctness of QCA in this connection. Some prominent representatives of the method have replied in turn that simulations with artificial data are unsuited for assessing QCA. We take issue with either position in this impasse. On the one hand, we argue that data-driven evaluations of the correctness of (...)
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  8. Why Your Causal Intuitions are Corrupt: Intermediate and Enabling Variables.Christopher Clarke - forthcoming - Erkenntnis:1-29.
    When evaluating theories of causation, intuitions should not play a decisive role, not even intuitions in flawlessly-designed thought experiments. Indeed, no coherent theory of causation can respect the typical person’s intuitions in redundancy (pre-emption) thought experiments, without disrespecting their intuitions in threat-and-saviour (switching / short-circuit) thought experiments. I provide a deductively sound argument for these claims. Amazingly, this argument assumes absolutely nothing about the nature of causation. I also provide a second argument, whose conclusion is even stronger: the typical person’s (...)
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  9. Causal Bayes nets and token-causation: Closing the gap between token-level and type-level.Alexander Gebharter & Andreas Hüttemann - forthcoming - Erkenntnis:1-23.
    Causal Bayes nets (CBNs) provide one of the most powerful tools for modelling coarse-grained type-level causal structure. As in other fields (e.g., thermodynamics) the question arises how such coarse-grained characterisations are related to the characterisation of their underlying structure (in this case: token-level causal relations). Answering this question meets what is called a “coherence-requirement” in the reduction debate: How are different accounts of one and the same system (or kind of system) related to each other. We argue that CBNs as (...)
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  10. Social cognition as causal inference: implications for common knowledge and autism.Jakob Hohwy & Colin Palmer - forthcoming - In John Michael & Mattia Gallotti (eds.), Social Objects and Social Cognition. Springer.
    This chapter explores the idea that the need to establish common knowledge is one feature that makes social cognition stand apart in important ways from cognition in general. We develop this idea on the background of the claim that social cognition is nothing but a type of causal inference. We focus on autism as our test-case, and propose that a specific type of problem with common knowledge processing is implicated in challenges to social cognition in autism spectrum disorder (ASD). This (...)
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  11. Is Causal Reasoning Harder Than Probabilistic Reasoning?Milan Mossé, Duligur Ibeling & Thomas Icard - forthcoming - Review of Symbolic Logic:1-26.
    Many tasks in statistical and causal inference can be construed as problems of entailment in a suitable formal language. We ask whether those problems are more difficult, from a computational perspective, for causal probabilistic languages than for pure probabilistic (or “associational”) languages. Despite several senses in which causal reasoning is indeed more complex—both expressively and inferentially—we show that causal entailment (or satisfiability) problems can be systematically and robustly reduced to purely probabilistic problems. Thus there is no jump in computational complexity. (...)
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  12. The Space of Motivations, Experience, and the Categorial Given.Jacob Rump - forthcoming - In Daniele De Santis & Danilo Manca (eds.), Wilfrid Sellars and Phenomenology: Intersections, Encounters, Oppositions. Athens, Ohio, USA: Ohio University Press.
    This paper outlines an Husserlian, phenomenological account of the first stages of the acquisition of empirical knowledge in light of some aspects of Wilfrid Sellars’ critique of the myth of the given. The account offered accords with Sellars’ in the view that epistemic status is attributed to empirical episodes holistically and within a broader normative context, but disagrees that such holism and normativity are accomplished only within the linguistic and conceptual confines of the space of reasons, and rejects the limitation (...)
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  13. Highlighting the Causal Meaning of Causal Test Questions in Contexts of Norm Violations.Jana Samland & Michael Waldmann - forthcoming - Proceedings of the Cognitive Science Society.
    Experiments have shown that prescriptive norms often influence causal inferences. The reason for this effect is still not clear. One problem of the studies is that the term ‘cause’ in the test questions is ambiguous and can refer to both the causal mechanism and the agent’s accountability. Possibly subjects interpreted the causal test question as a request to assess accountability rather than causality. Scenarios that put more stress on the causal mechanism should therefore yield no norm effect. Consequently, Experiment 1 (...)
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  14. The Chances of Choices.Reuben Stern - forthcoming - British Journal for the Philosophy of Science.
  15. The Epistemology of Causal Selection: Insights from Systems Biology.Beckett Sterner - forthcoming - In C. Kenneth Waters (ed.), Causal Reasoning in Biology. University of Minnesota Press.
    Among the many causes of an event, how do we distinguish the important ones? Are there ways to distinguish among causes on principled grounds that integrate both practical aims and objective knowledge? Psychologist Tania Lombrozo has suggested that causal explanations “identify factors that are ‘exportable’ in the sense that they are likely to subserve future prediction and intervention” (Lombrozo 2010, 327). Hence portable causes are more important precisely because they provide objective information to prediction and intervention as practical aims. However, (...)
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  16. A Causal Safety Criterion for Knowledge.Jonathan Vandenburgh - forthcoming - Erkenntnis:1-21.
    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, problems arise for using safety as a condition on knowledge: safety is not necessary for knowledge and cannot always explain the Gettier cases and cases of statistical evidence it is meant to address. In this paper, I argue for a new modal condition designed to capture the non-accidental relationship between facts and evidence required for knowledge: (...)
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  17. Philosophical Perspectives on Causal Reasoning in Biology. Minnesota Studies in Philosophy of Science. Vol. XXI.Waters C. Kenneth & Woodward James (eds.) - forthcoming - University of Minnesota Press.
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  18. Philosophical Perspectives on Causal Reasoning in Biology.C. Kenneth Waters & James Woodward (eds.) - forthcoming - University of Minnesota Press.
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  19. On Mary Shepherd's Essay upon the Relation of Cause and Effect.Jessica Wilson - forthcoming - In Eric Schliesser (ed.), Neglected Classics of Philosophy, II. Oxford University Press.
    Mary Shepherd (1777–1847) was a fierce and brilliant critic of Berkeley and Hume, who moreover offered strikingly original positive views about the nature of reality and our access to it which deserve much more attention (and credit, since she anticipates many prominent views) than they have received thus far. By way of illustration, I focus on Shepherd's 1824 Essay Upon the Relation of Cause and Effect, Controverting the Doctrine of Mr. Hume, Concerning the Nature of that Relation (ERCE). After a (...)
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  20. Why adoption of causal modeling methods requires some metaphysics.Holly Andersen - 2023 - In Federica Russo (ed.), Routledge Handbook of Causality and Causal Methods,. Routledge.
    I highlight a metaphysical concern that stands in the way of more widespread adoption of causal modeling techniques such as causal Bayes nets. Researchers in some fields may resist adoption due to concerns that they don't 'really' understand what they are saying about a system when they apply such techniques. Students in these fields are repeated exhorted to be cautious about application of statistical techniques to their data without a clear understanding of the conditions required for those techniques to yield (...)
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  21. Evidence and Inductive Inference.Nevin Climenhaga - 2023 - In Maria Lasonen-Aarnio & Clayton Littlejohn (eds.), The Routledge Handbook of the Philosophy of Evidence. Routledge. pp. 435-449.
    This chapter presents a typology of the different kinds of inductive inferences we can draw from our evidence, based on the explanatory relationship between evidence and conclusion. Drawing on the literature on graphical models of explanation, I divide inductive inferences into (a) downwards inferences, which proceed from cause to effect, (b) upwards inferences, which proceed from effect to cause, and (c) sideways inferences, which proceed first from effect to cause and then from that cause to an additional effect. I further (...)
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  22. Unification and explanation from a causal perspective.Alexander Gebharter & Christian J. Feldbacher-Escamilla - 2023 - Studies in History and Philosophy of Science Part A 99 (C):28-36.
    We discuss two influential views of unification: mutual information unification (MIU) and common origin unification (COU). We propose a simple probabilistic measure for COU and compare it with Myrvold’s (2003, 2017) probabilistic measure for MIU. We then explore how well these two measures perform in simple causal settings. After highlighting several deficiencies, we propose causal constraints for both measures. A comparison with explanatory power shows that the causal version of COU is one step ahead in simple causal settings. However, slightly (...)
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  23. What Killed Your Plant? Profligate Omissions and Weak Centering.Johannes Himmelreich - 2023 - Erkenntnis 88 (4):1683-1703.
    This paper is on the problem of profligate omissions. The problem is that counterfactual definitions of causation identify as a cause anything that could have prevented an effect but that did not actually occur, which is a highly counterintuitive result. Many solutions of this problem appeal to normative, epistemic, pragmatic, or metaphysical considerations. These existing solutions are in some sense substantive. In contrast, this paper concentrates on the semantics of counterfactuals. I propose to replace Strong Centering with Weak Centering. This (...)
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  24. Human vision reconstructs time to satisfy causal constraints.Christos Bechlivanidis, Marc J. Buehner, Emma C. Tecwyn, D. A. Lagnado, Christoph Hoerl & Teresa McCormack - 2022 - Psychological Science 33 (2):224-235.
    The goal of perception is to infer the most plausible source of sensory stimulation. Unisensory perception of temporal order, however, appears to require no inference, since the order of events can be uniquely determined from the order in which sensory signals arrive. Here we demonstrate a novel perceptual illusion that casts doubt on this intuition: in three studies (N=607) the experienced event timings are determined by causality in real-time. Adult observers viewed a simple three-item sequence ACB, which is typically remembered (...)
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  25. Process tracing : defining the undefinable.Christopher Clarke - 2022 - In Harold Kincaid & Jeroen van Bouwel (eds.), The Oxford Handbook of Philosophy of Political Science. Oxford University Press.
    A good definition of process tracing should highlight what is distinctive about process tracing as a methodology of causal inference. I look at eight criteria that are used to define process tracing in the methodological literature, and I dismiss all eight criteria as unhelpful (some because they are too restrictive, and others because they are vacuous). In place of these criteria, I propose four alternative criteria, and I draw a distinction between process tracing for the ultimate aim of testing a (...)
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  26. Language shapes children’s attitudes: Consequences of internal, behavioral, and societal information in punitive and nonpunitive contexts.James P. Dunlea & Larisa Heiphetz - 2022 - Journal of Experimental Psychology: General 151 (6):1233-1251.
    Research has probed the consequences of providing people with different types of information regarding why a person possesses a certain characteristic. However, this work has largely examined the consequences of different information subsets (e.g., information focusing on internal versus societal causes). Less work has compared several types of information within the same paradigm. Using the legal system as an example domain, we provided children (N=198 6- to 8-year-olds) with several types of information—including information highlighting internal moral character, internal biological factors, (...)
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  27. There is Cause to Randomize.Cristian Larroulet Philippi - 2022 - Philosophy of Science 89 (1):152 - 170.
    While practitioners think highly of randomized studies, some philosophers argue that there is no epistemic reason to randomize. Here I show that their arguments do not entail their conclusion. Moreover, I provide novel reasons for randomizing in the context of interventional studies. The overall discussion provides a unified framework for assessing baseline balance, one that holds for interventional and observational studies alike. The upshot: practitioners’ strong preference for randomized studies can be defended in some cases, while still offering a nuanced (...)
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  28. 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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  29. 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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  30. How interventionist accounts of causation work in experimental practice and why there is no need to worry about supervenience.Tudor M. Baetu - 2021 - Synthese 199 (1-2):4601-4620.
    It has been argued that supervenience generates unavoidable confounding problems for interventionist accounts of causation, to the point that we must choose between interventionism and supervenience. According to one solution, the dilemma can be defused by excluding non-causal determinants of an outcome as potential confounders. I argue that this solution undermines the methodological validity of causal tests. Moreover, we don’t have to choose between interventionism and supervenience in the first place. Some confounding problems are effectively circumvented by experimental designs routinely (...)
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  31. 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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  32. The Fate of Explanatory Reasoning in the Age of Big Data.Frank Cabrera - 2021 - Philosophy and Technology 34 (4):645-665.
    In this paper, I critically evaluate several related, provocative claims made by proponents of data-intensive science and “Big Data” which bear on scientific methodology, especially the claim that scientists will soon no longer have any use for familiar concepts like causation and explanation. After introducing the issue, in Section 2, I elaborate on the alleged changes to scientific method that feature prominently in discussions of Big Data. In Section 3, I argue that these methodological claims are in tension with a (...)
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  33. Causal Blame.Eugene Chislenko - 2021 - American Philosophical Quarterly 58 (4):347-58.
    We blame faulty brakes for a car crash, or rain for our bad mood. This “merely causal” blame is usually seen as uninteresting. I argue that it is crucial for understanding the interpersonal blame with which we target ourselves and each other. The two are often difficult to distinguish, in a way that plagues philosophical discussions of blame. And interpersonal blame is distinctive, I argue, partly in its causal focus: its attention to a person as cause. I argue that this (...)
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  34. 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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  35. 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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  36. What Caused the Bhopal Gas Tragedy? The Philosophical Importance of Causal and Pragmatic Details.Brian J. Hanley - 2021 - Philosophy of Science 88 (4):616-637.
    In cases in which many causes together bring about an effect, it is common to select some as particularly important. Philosophers since Mill have been pessimistic about analyzing this reasoning because of its variability and the multifarious causal and pragmatic details of how it works. I argue Mill was right to think these details matter but wrong that they preclude philosophical analysis of causal selection. I show that analyzing the pragmatic details of scientific debates about the important causes of the (...)
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  37. Norms Affect Prospective Causal Judgments.Paul Henne, Kevin O’Neill, Paul Bello, Sangeet Khemlani & Felipe De Brigard - 2021 - Cognitive Science 45 (1):e12931.
    People more frequently select norm-violating factors, relative to norm- conforming ones, as the cause of some outcome. Until recently, this abnormal-selection effect has been studied using retrospective vignette-based paradigms. We use a novel set of video stimuli to investigate this effect for prospective causal judgments—i.e., judgments about the cause of some future outcome. Four experiments show that people more frequently select norm- violating factors, relative to norm-conforming ones, as the cause of some future outcome. We show that the abnormal-selection effects (...)
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  38. Much Ado About Nothing: The Mental Representation of Omissive Relations.Sangeet Khemlani, Paul Bello, Gordon Briggs, Hillary Harner & Christina Wasylyshyn - 2021 - Frontiers in Psychology 11:609658.
    When the absence of an event causes some outcome, it is an instance of omissive causation. For instance, not eating lunch may cause you to be hungry. Recent psychological proposals concur that the mind represents causal relations, including omissive causal relations, through mental simulation, but they disagree on the form of that simulation. One theory states that people represent omissive causes as force vectors; another states that omissions are representations of contrasting counterfactual simulations; a third argues that people think about (...)
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  39. COVID-19 and the selection problem in national cause-of-death statistics.B. I. B. Lindahl - 2021 - History and Philosophy of the Life Sciences 43 (2):1-5.
    The World Health Organization has issued international instructions for certification and classification (coding) of the coronavirus disease (COVID-19) as cause of death. Central to these instructions is the selection of the underlying cause of death for a public health preventive purpose. This article focuses on two rules for this selection: (1) that a death due to COVID-19 should be counted independently of pre-existing conditions that are suspected of triggering a severe course of COVID-19 and (2) that COVID-19 should not be (...)
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  40. Causes with material continuity.Lauren N. Ross - 2021 - Biology and Philosophy 36 (6):1-17.
    Recent philosophical work on causation has focused on distinctions across types of causal relationships. This paper argues for another distinction that has yet to receive attention in this work. This distinction has to do with whether causal relationships have “material continuity,” which refers to the reliable movement of material from cause to effect. This paper provides an analysis of material continuity and argues that causal relationships with this feature are associated with a unique explanatory perspective, are studied with distinct causal (...)
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  41. The Communicative Functions of Metaphors Between Explanation and Persuasion.Maria Grazia Rossi & Fabrizio Macagno - 2021 - In Fabrizio Macagno & Alessandro Capone (eds.), Inquiries in philosophical pragmatics. Theoretical developments. Cham, Switzerland: Springer. pp. 171-191.
    In the literature, the pragmatic dimension of metaphors has been clearly acknowledged. Metaphors are regarded as having different possible uses, especially 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 chapter, we will address this issue focusing on the classical distinction between the explanatory and persuasive uses of metaphors, which is, however, complex to draw at an analytical level and often (...)
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  42. 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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  43. Feeling the past: beyond causal content.Gerardo Viera - 2021 - Estudios de Filosofía (Universidad de Antioquia) 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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  44. Causal inference in biomedical research.Tudor M. Baetu - 2020 - Biology and Philosophy 35 (4):1-19.
    Current debates surrounding the virtues and shortcomings of randomization are symptomatic of a lack of appreciation of the fact that causation can be inferred by two distinct inference methods, each requiring its own, specific experimental design. There is a non-statistical type of inference associated with controlled experiments in basic biomedical research; and a statistical variety associated with randomized controlled trials in clinical research. I argue that the main difference between the two hinges on the satisfaction of the comparability requirement, which (...)
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  45. Evidence and explanation in Cicero's On Divination.Frank Cabrera - 2020 - Studies in History and Philosophy of Science Part A 82 (C):34-43.
    In this paper, I examine Cicero’s oft-neglected De Divinatione, a dialogue investigating the legitimacy of the practice of divination. First, I offer a novel analysis of the main arguments for divination given by Quintus, highlighting the fact that he employs two logically distinct argument forms. Next, I turn to the first of the main arguments against divination given by Marcus. Here I show, with the help of modern probabilistic tools, that Marcus’ skeptical response is far from the decisive, proto-naturalistic assault (...)
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  46. Causation in Psychology.John Campbell - 2020 - Harvard University Press.
    "A blab droid is a robot with a body shaped like a pizza box, a pair of treads, and a smiley face. Guided by an onboard video camera, it roams hotel lobbies and conference centers, asking questions in the voice of a seven-year-old. "Can you help me?" "What is the worst thing you've ever done?" "Who in the world do you love most?" People pour their hearts out in response. This droid prompts the question of what we can hope from (...)
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  47. Averaging causal estimators in high dimensions.Matthew Cefalu & Joseph Antonelli - 2020 - Journal of Causal Inference 8 (1):92-107.
    There has been increasing interest in recent years in the development of approaches to estimate causal effects when the number of potential confounders is prohibitively large. This growth in interest has led to a number of potential estimators one could use in this setting. Each of these estimators has different operating characteristics, and it is unlikely that one estimator will outperform all others across all possible scenarios. Coupling this with the fact that an analyst can never know which approach is (...)
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  48. Causal Reasoning and Meno’s Paradox.Melvin Chen & Lock Yue Chew - 2020 - 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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  49. How do medical researchers make causal inferences?Olaf Dammann, Ted Poston & Paul Thagard - 2020 - In Kevin McCain & Kostas Kampourakis (eds.), What is scientific knowledge? An introduction to contemporary epistemology of science. London, UK: Routledge.
    Bradford Hill (1965) highlighted nine aspects of the complex evidential situation a medical researcher faces when determining whether a causal relation exists between a disease and various conditions associated with it. These aspects are widely cited in the literature on epidemiological inference as justifying an inference to a causal claim, but the epistemological basis of the Hill aspects is not understood. We offer an explanatory coherentist interpretation, explicated by Thagard's ECHO model of explanatory coherence. The ECHO model captures the complexity (...)
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  50. A Process Model of Causal Reasoning.Zachary J. Davis & Bob Rehder - 2020 - Cognitive Science 44 (5):e12839.
    How do we make causal judgments? Many studies have demonstrated that people are capable causal reasoners, achieving success on tasks from reasoning to categorization to interventions. However, less is known about the mental processes used to achieve such sophisticated judgments. We propose a new process model—the mutation sampler—that models causal judgments as based on a sample of possible states of the causal system generated using the Metropolis–Hastings sampling algorithm. Across a diverse array of tasks and conditions encompassing over 1,700 participants, (...)
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