Counterfactual Dependence Research Articles

Counterfactual power and genuine choice

AbstractThe article introduces a distinction between weak and strong counterfactual power and shows that as far as the metaphysical aspect of choice is concerned, T. Merricks's examples do not undermine the proposition that strong counterfactual power over a fact suffices for having a genuine choice about that fact. This is relevant to debates about logical fatalism, theological incompatibilism and nomological (determinism) incompatibilism. If strong counterfactual power is sufficient for having a choice, then in each of the main arguments for the mentioned stances, the negation of the argument's conclusion entails the negation of its key premise. It is further argued that those key premises cannot be justified by the fixity of the past because the latter holds only to the extent warranted by the asymmetry of counterfactual dependence between the past and the future. Therefore, the pastness of such facts as that propositions about our acts were true before we were born, and that God believed then that we would perform those acts, does not provide any reason to believe that we do not have a choice about those facts. Fatalists and incompatibilists assume in their arguments something that has yet to be justified.

Identifying roles of formulas in inconsistency under Priest's minimally inconsistent logic of paradox

It has been increasingly recognized that identifying roles of formulas of a knowledge base in the inconsistency of that base can help us better look inside the inconsistency. However, there are few approaches to identifying such roles of formulas from a perspective of models in some paraconsistent logic, one of typical tools used to characterize inconsistency in semantics. In this paper, we characterize the role of each formula in the inconsistency arising in a knowledge base from informational as well as causal aspects in the framework of Priest's minimally inconsistent logic of paradox. At first, we identify the causal responsibility of a formula for the inconsistency based on the counterfactual dependence of the inconsistency on the formula under some contingency in semantics. Then we incorporate the change on semantic information in the framework of causal responsibility to develop the informational responsibility of a formula for the inconsistency to capture the contribution made by the formula for the inconsistent information. This incorporation makes the informational responsibility interpretable from the point of view of causality, and capable of catching the role of a formula in inconsistent information concisely. In addition, we propose notions of naive and quasi naive responsibilities as two auxiliaries to describe special relations between inconsistency and formulas in semantic sense. Some intuitive and interesting properties of the two kinds of responsibilities are also discussed.

Nashian game theory is incompatible with quantum physics

We suggest to look at quantum measurement outcomes not through the lens of probability theory, but instead through decision theory. We introduce an original game-theoretical framework, model and algorithmic procedure where measurement scenarios are multiplayer games with a structure all observers agree on. Measurement axes and, newly, measurement outcomes are modeled as decisions with nature being an action-minimizing economic agent. We translate physical notions of causality, correlation, counterfactuals, and contextuality to particular aspects of game theory. We investigate the causal consistency of dynamic games with imperfect information from the quantum perspective and conclude that counterfactual dependencies should be distinguished from causation and correlation as a separate phenomenon of its own. Most significantly, we observe that game theory based on Nash equilibria stands in contradiction with a violation of Bell inequalities. Hence, we propose that quantum physics should be analyzed with non-Nashian game theory, the inner workings of which we demonstrate using our proposed model.

On the Role of Erotetic Constraints in Noncausal Explanations

Abstract In noncausal explanations, some noncausal facts (such as mathematical, modal, or metaphysical) are used to explain some physical facts. However, precisely because these explanations abstract away from causal facts, they face two challenges: (1) it is not clear why one rather than the other noncausal explanantia would be relevant for the explanandum; and (2) why would standing in a particular explanatory relation (e.g., “counterfactual dependence,” “constraint,” “entailment,” “constitution,” and “grounding”), and not in some other, be explanatory. I develop an explanatory relevance account that is based on erotetic constraints and show how it addresses these two challenges.

Frameworks in Historiography: Explanation, Scenarios, and Futures

Abstract In this paper, I analyze how frameworks shape historiographical explanations. I argue that, in order to identify a sequence of events as relevant to a historical outcome, assumptions about the workings of the relevant domain have to be made. By extending Lakatosian considerations, I argue that these assumptions are provided by a framework that contains a set of factors and intertwined principles that (supposedly) govern how a historical phenomenon works. I connect frameworks with a counterfactual account of historical explanation. Frameworks enable us to explain the past by providing a backbone of explanatory patterns of counterfactual dependency. I conclude by noting that both counterfactual scenarios and scenarios of the future require frameworks and, therefore, historiographical explanation generates a set of possible futures. Analyzing these possible futures enables us to reveal the theoretical commitments of historiography.

God’s Foreknowledge, Human Freedom, and the Asymmetry of Openness

The paper defends a compatibilist solution to the problem of the relationship between divine and human freedom. It is argued that the asymmetry of ability constituted by our ability to foreknowledge influence the future and our inability to control the past results from the asymmetry of openness between fixed past and open future interpreted in terms of the asymmetry of counterfactual dependence. Therefore, if the asymmetry of openness is not true of some types of facts, then we may be able to control them even if they are facts about the past. It turns out that widely shared accounts of the nature and source of God’s foreknowledge entail that the asymmetry of openness does not apply to God’s past beliefs about future contingencies. Thus, it is unjustified to claim that we are unable to now do anything such that, if we were to do it, God’s past beliefs would have been different.

Backwards Time Travel and Backwards Causation

Is it possible to travel back in time? Objections against backwards time travel frequently focus on the impossibility of changing the past. However, there is a deeper problem for backwards time travel. It seems that if backwards time travel were possible, the time traveler could causally affect the past, even if she could not alter the past. Is it possible to causally affect the past? David Lewis famously argues that backwards causation is possible as long as we understand causal dependence in terms of counterfactual dependence rather than temporal precedence. In this paper, I argue that this Lewisian line of reasoning is untenable. Lewis counterfactual theory of causation faces the so-called problem of effects. To solve this problem, he either has to reintroduce temporal precedence back into the definition of causation or stipulate that the closest possible world needs to be historically the same as the actual one. Either way, the possibility of backwards causation is immediately ruled out.

Explanatory Asymmetry in Non-Causal Explanation

The problem of explanatory asymmetry remains a serious challenge for non-causal accounts of explanation. This paper proposes a novel solution, and it does so by appealing to the theoretical context in which an explanation is offered. The paper develops the problem of explanatory asymmetry for non-causal dependency accounts of explanation, focusing specifically on Alexander Reutlinger’s Counterfactual Theory of Explanation and recent work by Marc Lange and Lina Jansson. It defends the idea that nomological possibility with respect to a global theory is the right constraint on explanation, and it shows how this breaks the apparent symmetry in counterfactual dependence that is the source of the problem. This solution appeals to theoretical context, and the paper develops and defends the version of contextualism in explanation that is required.

Investment Decisions under Almost Complete Causal Ignorance

This article investigates investment decision making under conditions of almost complete causal ignorance. Using two basic notions of causal dependence, probabilistic and counterfactual dependence, as building blocks, a formal notion of causal distance is presented that gives decision makers the ability to quantitatively assess the proximity that different causal graphs have to each other. The latter are directed acyclic graphs that can also be used to represent causal relations among economic events. Once the causal distance of each graph in a set of causal graphs is determined, it is possible to select the graph with the shortest total distance to the other graphs. This in turn allows decision makers to select a course of action that will be beneficial regardless of the particular set of causal relations that is actually driving observed economic events. The article describes how causal distance values can be used formally within an optimization to facilitate portfolio construction.

Heritability and Etiology: Heritability estimates can provide causally relevant information

Can heritability estimates provide causal information? This paper argues for an affirmative answer: since a non-nil heritability estimate satisfies certain characteristic properties of causation (i.e., association, manipulability, and counterfactual dependence), it increases the probability that the relation between genotypic variance and phenotypic variance is (at least partly) causal. Contrary to earlier proposals in the literature, the argument does not assume the correctness of any particular conception of the nature of causation, rather focusing on properties that are characteristic of causal relationships. The argument is defended against Lewontin's (1974) locality objection and Kaplan and Turkheimer's (2021) recent critique of Genome-Wide Association Studies (GWAS).

Micro-level model explanation and counterfactual constraint

Relationships of counterfactual dependence have played a major role in recent debates of explanation and understanding in the philosophy of science. Usually, counterfactual dependencies have been viewed as the explanantia of explanation, i.e., the things providing explanation and understanding. Sometimes, however, counterfactual dependencies are themselves the targets of explanations in science. These kinds of explanations are the focus of this paper. I argue that “micro-level model explanations” explain the particular form of the empirical regularity underlying a counterfactual dependency by representing it as a physical necessity on the basis of postulated microscopic entities. By doing so, micro-level models rule out possible forms the regularity (and the associated counterfactual) could have taken. Micro-model explanations, in other words, constrain empirical regularities and their associated counterfactual dependencies. I introduce and illustrate micro-level model explanations in detail, contrast them to other accounts of explanation, and consider potential problems.

Fictional mechanism explanations: clarifying explanatory holes in engineering science

This paper discusses a class of mechanistic explanations employed in engineering science where the activities and organization of nonstandard entities (voids, cracks, pits…) are cited as core factors responsible for failures. Given the use of mechanistic language by engineers and the manifestly mechanistic structure of these explanations, I consider several interpretations of these explanations within the new mechanical framework (among others: voids should be considered as shorthand expressions for other entities, voids should be reduced to lower-level mechanisms, or the explanations are simply abstract mechanistic explanations). I argue that these interpretations fail to solve several philosophical problems and propose an account of fictional mechanism explanations instead. According to this account, fictional mechanism explanations provide descriptions of fictional mechanisms that enable the tracking of counterfactual dependencies of the physical system they model by capturing system constraints. Engineers use these models to learn about and understand properties of materials, to build computational simulations of their behaviour, and to design new materials.

Procedure for assessing the quality of explanations in failure analysis

Abstract This paper outlines a procedure for assessing the quality of failure explanations in engineering failure analysis. The procedure structures the information contained in explanations such that it enables to find weak points, to compare competing explanations, and to provide redesign recommendations. These features make the procedure a good asset for critical reflection on some areas of the engineering practice of failure analysis and redesign. The procedure structures relevant information contained in an explanation by means of structural equations so as to make the relations between key elements more salient. Once structured, the information is examined on its potential to track counterfactual dependencies by offering answers to relevant what-if-things-had-been-different questions. This criterion for explanatory goodness derives from the philosophy of science literature on scientific explanation. The procedure is illustrated by applying it to two case studies, one on Failure Analysis in Mechanical Engineering (a broken vehicle shaft) and one on Failure Analysis in Civil Engineering (a collapse in a convention center). The procedure offers failure analysts a practical tool for critical reflection on some areas of their practice while offering a deeper understanding of the workings of failure analysis (framing it as an explanatory practice). It, therefore, allows to improve certain aspects of the explanatory practices of failure analysis and redesign, but it also offers a theoretical perspective that can clarify important features of these practices. Given the programmatic nature of the procedure and its object (assessing and refining explanations), it extends work on the domain of computational argumentation.

Conditionals and the hierarchy of causal queries.

Recent studies indicate that indicative conditionals like "If people wear masks, the spread of Covid-19 will be diminished" require a probabilistic dependency between their antecedents and consequents to be acceptable (Skovgaard-Olsen et al., 2016). But it is easy to make the slip from this claim to the thesis that indicative conditionals are acceptable only if this probabilistic dependency results from a causal relation between antecedent and consequent. According to Pearl (2009), understanding a causal relation involves multiple, hierarchically organized conceptual dimensions: prediction, intervention, and counterfactual dependence. In a series of experiments, we test the hypothesis that these conceptual dimensions are differentially encoded in indicative and counterfactual conditionals. If this hypothesis holds, then there are limits as to how much of a causal relation is captured by indicative conditionals alone. Our results show that the acceptance of indicative and counterfactual conditionals can become dissociated. Furthermore, it is found that the acceptance of both is needed for accepting a causal relation between two co-occurring events. The implications that these findings have for the hypothesis above, and for recent debates at the intersection of the psychology of reasoning and causal judgment, are critically discussed. Our findings are consistent with viewing indicative conditionals as answering predictive queries requiring evidential relevance (even in the absence of direct causal relations). Counterfactual conditionals in contrast target causal relevance, specifically. Finally, we discuss the implications our results have for the yet unsolved question of how reasoners succeed in constructing causal models from verbal descriptions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Challenges Facing Counterfactual Accounts of Explanation in Mathematics

ABSTRACTSome mathematical proofs explain why the theorems they prove hold. This paper identifies several challenges for any counterfactual account of explanation in mathematics (that is, any account according to which an explanatory proof reveals how the explanandum would have been different, had facts in the explanans been different). The paper presumes that countermathematicals can be nontrivial. It argues that nevertheless, a counterfactual account portrays explanatory power as too easy to achieve, does not capture explanatory asymmetry, and fails to specify why certain proofs are explanatory and others are not. Greater informativeness about counterfactual dependence can even yield less explanatory power.

Revising Carroll’s Mirror Argument

In this paper, I examine J. Carroll's “Mirror Argument” against the Humean conception of law and H. Beebee's response to this argument. I will first show that Beebee's criticism is quite plausible if it is refined slightly. Then, I will propose a revised version of the Mirror Argument which is immune to criticisms like that of Beebee's. According to the Humean conception of law, I will argue, we should accept the existence of counterfactual dependence relation where there should not be such relation.

Counterfactual Contamination

ABSTRACT Many defend the thesis that when someone knows p, they couldn’t easily have been wrong about p. But the notion of easy possibility in play is relatively under-theorized. One structural idea in the literature, the principle of Counterfactual Closure (CC), connects easy possibility with counterfactuals: if it easily could have happened that p, and if p were the case then q would be the case, then it follows that it easily could have happened that q. We first argue that, while CC is false, there is a true restriction of it to cases involving counterfactual dependence on a coin flip. The failure of CC falsifies a model where the easy possibilities are counterfactually similar to actuality. Next, we show that extant normality models, where the easy possibilities are the sufficiently normal ones, are incompatible with the restricted CC thesis involving coin flips. Next, we develop a new kind of normality theory that can accommodate the restricted version of CC. This new theory introduces a principle of Counterfactual Contamination, which says, roughly, that any world is fairly abnormal if at that world very abnormal events counterfactually depend on a coin flip. Finally, we explain why coin flips and other related events have a special status. A central take-home lesson is that the correct principle in the vicinity of Safety is importantly normality-theoretic rather than (as it is usually conceived) similarity-theoretic.

De-Talibanization and the Onset of Insurgency in Afghanistan

This article examines the reasons for the rise of the Taliban and the onset of the insurgency in Afghanistan after the 2001 U.S. invasion, using counterfactual and path dependence analysis to bolster its arguments. We argue that the U.S. decision to de-Talibanize was a critical juncture, after which the rise of insurgency was far harder to prevent. The total rejection of the Taliban translated into the under-representation of Pashtuns in the Afghan government, delivering power to ethnic minorities at their expense. De-Talibanization led the United States to support strongmen to hunt the Taliban, but they were predatory, creating grievances that the Taliban exploited to recruit. Finally, de-Talibanization led many Taliban to flee to Pakistan, pushing them into the country most opposed to Afghanistan new political order. The lessons of the U.S. experience in Afghanistan suggest the necessity of a strategy for managing defeated enemies after an initial military victory.

An equivocation in the simple argument for downward causation

I argue that Kroedel's 'Simple Argument' for downward causation fails and that this failure has consequences for any attempt to establish the reality of downward causation by appealing to counterfactual theories thereof. A central premise in Kroedel's argument equivocates. On one reading, it is true but renders the argument invalid; on another, it renders the argument valid but is likely false. I dedicate most of my efforts to establishing the second of these two claims. I show that the purported physical effects of mental properties do not counterfactually depend upon the total realizers of these properties. If counterfactual dependence is necessary for causation, it follows that mental properties are not causes. If counterfactual dependence is merely sufficient for causation, it follows that no appeal to counterfactuals will by itself succeed in showing that mental properties are causes.

Do fictions explain?

I argue that fictional models, construed as models that misrepresent certain ontological aspects of their target systems, can nevertheless explain why the latter exhibit certain behaviour. They can do this by accurately representing whatever it is that that behaviour counterfactually depends on. However, we should be sufficiently sensitive to different explanatory questions, i.e., ‘why does certain behaviour occur?’ versus ‘why does the counterfactual dependency invoked to answer that question actually hold?’. With this distinction in mind, I argue that whilst fictional models can answer the first sort of question, they do so in an unmysterious way (contra to what one might initially think about such models). Moreover, I claim that the second question poses a dilemma for the defender of the idea that fictions can explain: either these models cannot answer these sorts of explanatory questions, precisely because they are fictional; or they can, but in a way that requires reinterpreting them such that they end up accurately representing the ontological basis of the counterfactual dependency, i.e., reinterpreting them so as to rob them of their fictional status. Thus, the existence of explanatory fictions does not put pressure on the idea that accurate representation of some aspect of a target system is a necessary condition on explaining that aspect.