Mechanistic Explanation Research Papers - Academia.edu (original) (raw)

“Realization” is a technical term that is used by metaphysicians, philosophers of mind, and philosophers of science to denote some dependence relation that is thought to obtain between higher-level properties and lower-level properties. It is said that mental properties are realized by physical properties; functional and computational properties are realized by first-order properties that occupy certain causal/functional roles; dispositional properties are realized by categorical properties; so on and so forth. Given this wide usage of the term “realization”, it would be right to think that there might be different dependence relations that this term denotes in different cases. Any relation that is aptly picked out by this term can be taken to be a realization relation. The aim of this state-of-the-field article is to introduce the central questions about the concept of realization, and provide formulations of a number of realization relations. In doing so, I identify some theoretical roles realization relations should play, and discuss some theories of realization in relation to these theoretical roles.

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- Metaphysics, Philosophy of Mind, Philosophy of Science, Philosophy of Psychology

Recent findings in different areas of psychology and cognitive science have brought the discussion of the unconscious mind back to center stage. However, the unconscious mind worry remains: What renders unconscious phenomena mental? In the present paper, I will suggest a new strategy for answering this question. This strategy rests on the idea that categorizing unconscious phenomena as “mental” should come out as scientifically useful relative to the explanatory goals of unconscious mind research. I will argue that this is the case if by categorizing an unconscious phenomenon as “mental” one picks out explanatorily relevant similarities between that phenomenon and a corresponding paradigmatically mental phenomenon, i.e., a conscious one. Explanatory relevance is spelled out in terms of the mechanistic norms of scientific explanation.

- by William Bechtel
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- Psychology, Cognitive Psychology, Philosophy of Mind, Philosophy of Science
- by Gianluca Pozzoni
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- Sociology, Social Movements, Social Theory, Political Economy

The central task of cognitive neuroscience to map cognitive capacities to neural mechanisms faces three interlocking conceptual problems that together frame the problem of cognitive ontology. First, they must establish which tasks elicit which cognitive capacities, and specifically when different tasks elicits the same capacity. To address this operationalization

- by Marc Slors
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- Cognitive Psychology, Cognitive Science, Mechanistic Explanation

Consciousness is a virtual-reality display, created by an internal executive agent, which human beings experience as the self. This display serves to monitor and manage the state of the organism in relation to the world. Conscious experience serves a different function than unconscious processing. It is therefore not superfluous but has limited causal powers within the organism: the causality of agency, rather than the passive (efficient) causality of physics.

- by Dan Bruiger
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- Cognitive Psychology, Neuropsychology, Evolutionary Psychology, Epistemology

The notion of reduction continues to play a key role in philosophy of mind and philosophy of cognitive science. Supporters of reductionism claim that psychological properties or explanations reduce to neural properties or explanations, while antireductionists claim that such reductions are not possible. In this book, I apply recent developments in philosophy of science, particularly the mechanistic explanation paradigm and the interventionist theory of causation, to reassess the traditional approaches to reduction in philosophy of mind. I then elaborate and defend a pluralistic framework for philosophy of mind, and show how reductionist ideas can be incorporated into it. This leads to a novel synthesis of pluralism and reductionism that I call pluralistic physicalism.

- by Markus Eronen
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- Cognitive Science, Philosophy of Mind, Philosophy of Science, Mental Causation

Social mechanisms and mechanism-based explanation have attracted considerable attention in the social sciences and the philosophy of science during the past two decades. The idea of mechanistic explanation has proved to be a useful tool for criticizing existing research practices and meta-theoretical views on the nature of the social-scientific enterprise. Many definitions of social mechanisms have been articulated, and have been used to support a wide variety of methodological and theoretical claims. It is impossible to cover all of these in one chapter, so I will merely highlight some of the most prominent and philosophically interesting ideas.

The quest to provide a fundamental understanding and explanation of reality is an ambitious one. Perhaps it is too ambitious. The possible restrictions for such an enterprise to be successful must be inquired in order to determine the issue. Section 1 explores one’s understanding in reaching (scientific) conclusions: to what extent does a successful account testify to understanding? Section 2 focuses on the other side of such an account: does it provide an explanation in a more fundamental sense than pointing out causes of phenomena, or is it restricted to such a task? A critical stance vis-à-vis the (scientific) enterprise of unearthing reality’s structure remains necessary in order not to confuse a consistent and productive theory with one that demonstrates an understanding and explanation in the sense of this article.

- by Jasper Doomen
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- History of Science and Technology, Physics, Theoretical Physics, Quantum Physics
- by Angela Sinaga
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- Education, Translation Studies, Teacher Education, Educational Research

Cognitive sociology has been split into cultural and interdisciplinary traditions that position themselves differently in relation to the cognitive sciences and make incompatible assumptions about cognition. This article provides an analysis and assessment of the cognitive and methodological assumptions of these two traditions from the perspective of the mechanistic theory of explanation. We argue that while the cultural tradition of cognitive sociology has provided important descriptions about how human cognition varies across cultural groups and historical periods, it has not opened up the black box of cognitive mechanisms that produce and sustain this variation. This means that its explanations for the described phenomena have remained weak. By contrast, the interdisciplinary tradition of cognitive sociology has sought to integrate cognitive scientific concepts and methods into explanatory research on how culture influences action and how culture is stored in memory. Although we grant that interdisciplinary cognitive sociologists have brought many fresh ideas, concepts and methods to cultural sociology from the cognitive sciences, they have not always clarified their assumptions about cognition and their models have sketched only a few specific cognitive mechanisms through which culture influences action, meaning that they have not yet provided a comprehensive explanatory understanding of the interactions between culture, cognition and action.

- by Tuukka Kaidesoja and +1
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- Social Theory, Cultural Sociology, Theory Of Mechanisms, Sociological Theory

ABSTRACT: The free-energy principle states that all systems that minimize their free energy resist a tendency to physical disintegration. Originally proposed to account for perception , learning, and action, the free-energy principle has been applied to the evolution, development, morphology, anatomy and function of the brain, and has been called a postulate, an unfalsifiable principle, a natural law, and an imperative. While it might afford a theoretical foundation for understanding the relationship between environment , life, and mind, its epistemic status is unclear. Also unclear is how the free-energy principle relates to prominent theoretical approaches to life science phenomena, such as organicism and mechanism. This paper clarifies both issues, and identifies limits and prospects for the free-energy principle as a first principle in the life sciences.

- by Cory Wright
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- Ergodic Theory, Autopoiesis, Biology, Theory Of Mechanisms

I discuss whether there are some lessons for philosophical inquiry over the nature of simulation to be learnt from the practical methodology of reengineering. I will argue that reengineering serves a similar purpose as simulations in theoretical science such as computational neuroscience or neurorobotics, and that the procedures and heuristics of reengineering help to develop solutions to outstanding problems of simulation.

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation(s) for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a (conditionally) optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions.

- by Luciano Floridi
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- Computer Science, Artificial Intelligence, Information Technology, Game Theory

The question at issue in this dissertation is the epistemic role played by ecological generalizations and models. I investigate and analyze such properties of generalizations as lawlikeness, invariance, and stability, and I ask which of these properties are relevant in the context of scientific explanations. I will claim that there are generalizable and reliable causal explanations in ecology by generalizations, which are invariant and stable. An invariant generalization continues to hold or be valid under a special change called an intervention that changes the value of its variables. Whether a generalization remains invariant during its interventions is the criterion that determines whether it is explanatory. A generalization can be invariant and explanatory regardless of its lawlike status. Stability deals with a generality that has to do with holding of a generalization in possible background conditions. The more stable a generalization, the less dependent it is on background conditions to remain true. Although it is invariance rather than stability of generalizations that furnishes us with explanatory generalizations, there is an important function that stability has in this context of explanations, namely, stability furnishes us with extrapolability and reliability of scientific explanations. I also discuss non-empirical investigations of models that I call robustness and sensitivity analyses. I call sensitivity analyses investigations in which one model is studied with regard to its stability conditions by making changes and variations to the values of the model s parameters. As a general definition of robustness analyses I propose investigations of variations in modeling assumptions of different models of the same phenomenon in which the focus is on whether they produce similar or convergent results or not. Robustness and sensitivity analyses are powerful tools for studying the conditions and assumptions where models break down and they are especially powerful in pointing out reasons as to why they do this. They show which conditions or assumptions the results of models depend on.

- by Jani Raerinne
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- Philosophy of Biology, Robustness Analysis, Sensitivity Analysis, Causality
- by Petri Ylikoski
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- Philosophy of Social Science, Individualism, Reductionism, Mechanistic Explanation

Kaplan and Craver claim that all explanations in neuroscience appeal to
mechanisms. They extend this view to the use of mathematical models in
neuroscience and propose a constraint such models must meet in order to be
explanatory. I analyze a mathematical model used to provide explanations in
dynamical systems neuroscience and indicate how this explanation cannot be
accommodated by the mechanist framework. I argue that this explanation is
well characterized by Batterman’s account of minimal model explanations
and that it demonstrates how relationships between explanatory models in
neuroscience and the systems they represent is more complex than has been
appreciated.

- by Lauren N. Ross
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- Philosophy of Science, Dynamical Systems, Complex Systems, Explanation

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.

- by Petri Ylikoski
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- Philosophy of Science, Explanation, Mechanistic Explanation

Ist der Ansatz der mechanistischen Erklärung (ME) ein ausschließlich reduktiver Ansatz? Hat er reduktive Komponenten oder muss er als völliger Gegenentwurf zum Reduktionismus aufgefasst werden? Die Antworten hängen davon ab, wie Reduktionismus und Reduktion verstanden werden und wie die Vertreter von (ME) ihren Ansatz beschreiben. Während in einigen Publikationen William Bechtels und seiner Kollegen (Bechtel 2001; Bechtel 2007; Bechtel & Hamilton 2007) der mechanistische Erklärungsansatz durchaus als ein reduktionistischer Ansatz verstanden wird, so ist dies bei den Arbeiten von Carl Craver und einen Kollegen (v.a. Machamer, Darden & Craver 2000; Craver 2005; Craver 2007) und auch bei neueren Publikationen von William Bechtel und Kollegen (Bechtel & Abrahamsen 2008; Bechtel 2009; Bechtel 2010) nicht der Fall. Im Folgenden wird anhand der angeführten Texte gezeigt, inwiefern (ME) als reduktiver Ansatz aufgefasst werden kann. Danach wird beschrieben, inwieweit (ME) dem Reduktionismus entgegengesetzt ist. Schließlich werden mit Ernest Nagel, dem Begründer der klassischen Reduktion, die verbleibenden reduktiven Komponenten von (ME) beleuchtet. Genauer: die reduktive Sicht der Vereinheitlichung“, die Craver (2007) angreift und der er für die Neurowissenschaften eine alternative Form von Vereinheitlichung entgegensetzt, kann im Sinne von Nagel (1961) rehabilitiert werden. Damit wird die Nagel-Reduktion in Teilen als mit (ME) kompatibel erachtet.

- by Bettina Gutsche
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- Explanation, Reductionism, Mechanistic Explanation

The purpose of this chapter is to sketch the history of mechanistic models of the mental, as related to the technological project of trying to build mechanical minds, and discuss the uses of such models in psychological and cognitive explanations. Initially, they were supposed to show that mechanisms can in principle explain the mental. Today, efforts in cognitive science are focused on building more and more biologically and physically plausible models of mental mechanisms.

Are we free in wanting what we want to do? Could we ever have acted differently from how we actually acted? A growing number of scholars and especially philosophers believe the answer to these questions is No. Over the past century, confidence in free will has been decreasing proportionally to the increasing willingness to acknowledge that humans are natural beings. Natural scientists, neuroscientists and metaphysicians are sceptical that free will is anything but a self-misunderstanding based on ignorance of natural facts.
In my talk I want to argue the opposite. Free will scepticism rests upon deeply mistaken metaphysical assumptions about nature, namely on outdated mechanistic views that neglect the fundamentally processual character of those beings whose agency and free will is at stake: living beings. Cutting-edge research especially in systems biology suggests that free will, far from being ruled out by our biological condition, is an integral part of human nature; and not only of the human. Humans, like many other organisms, are, in a sense to be explained further, naturally free. I will demonstrate how empirical insights from biology underpin and radicalise recent endeavours in metaphysics to acknowledge the biological roots of human agency and free will.

ABSTRACT: Wesley Salmon’s version of the ontic conception of explanation is a main historical root of contemporary work on mechanistic explanation. This paper examines and critiques the philosophical merits of Salmon’s version, and argues that his conception’s most fundamental construct is either fundamentally obscure, or else reduces to a non-ontic conception of explanation. Either way, the ontic conception is a misconception.

- by Cory Wright
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- Metaphysics, Philosophy of Science, History of Philosophy of Science, Causation

Any successful account of the metaphysics of mechanistic causation must satisfy at least five key desiderata. In this paper, I lay out these five desiderata and explain why existing accounts of the metaphysics of mechanistic causation fail to satisfy them. I then present an alternative account which does satisfy the five desiderata. According to this alternative account, we must resort to a type of ontological entity that is new to metaphysics, but not to science: constraints. In this paper, I explain how a constraints-based metaphysics fits best with the emerging consensus on the nature of mechanistic explanation.

Mechanisms are said to consist of two kinds of components, entities and activities. In the first half of this chapter, I examine what entities and activities are, how they relate to well-known ontological categories, such as processes or dispositions, and how entities and activities relate to each other (e.g., can one be reduced to the other or are they mutually dependent?). The second part of this chapter analyzes different criteria for individuating the components of mechanisms and discusses how real the boundaries of mechanisms are.

- by Marie I. Kaiser
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- Philosophy of Biology, Mechanistic Explanation, Boundaries, Mechanism

This paper explores several paths by which the extended cognition (EC) thesis may overcome the coupling-constitution fallacy. In so doing, I address a couple of shortcomings in the contemporary literature. First, on the dimension of first-wave EC, I argue that constitutive arguments based on functional parity suffer from either a threat of cognitive bloat or an impasse with respect to determining the correct level of grain in the attribution of causal-functional roles. Second, on the dimension of second-wave EC, I argue that especially the complementarity approach suffers from a similar sort of dilemma as first-wave EC: an inability to justify just what entails the ontological claim of EC over the scaffolding claim of weaker approaches in cognitive science. In this paper I show that two much more promising explanations by which to ground the ontological claim of EC are available, both starting from an exploration of the coordination dynamics between environmental resources and neural resources. On the one hand, I argue that second-wave EC based on cognitive integration, with its focus on bodily manipulations constrained by cognitive norms, is capable of resolving the coupling-constitution fallacy. On the other hand, I argue that the framework of cognitive integration can be supplemented by philosophical accounts of mechanistic explanation, because such accounts enable us to explain the emergence of higher-level cognitive properties due to a system's organization-dependent structure.

- by Michael Kirchhoff
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- Philosophy of Mind, Philosophy of Science, Distributed Cognition, Extended Mind
- by Luana Poliseli
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- Philosophy of Science, Heuristics, Interdisciplinarity, Collaboration

The mechanistic framework traditionally comes bundled with a multi-level view. Some ascribe ontological weight to these levels, whereas others claim that characterising a higher-level entity and the corresponding lower-level mechanism are only different descriptions of the same thing. The goal of this paper is to develop a consistent metaphysical picture that can underly the latter position. According to this flat view, mechanistic wholes are modules that together with their parts are embedded in the same network of interacting units. The flat view preserves the original virtues of the mechanistic approach and is able to avoid the problems associated with the multi-level view.

- by Peter Fazekas
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- Reductionism, Mechanistic Explanation

Autonomist accounts of cognitive science suggest that cognitive model building and theory construction (can or should) proceed independently of findings in neuroscience. Common functionalist justifications of autonomy rely on there being relatively few constraints between neural structure and cognitive function (e.g., Weiskopf, 2011). In contrast, an integrative mechanistic perspective stresses the mutual constraining of structure and function (e.g., Piccinini & Craver, 2011; Povich, 2015). In this paper, I show how model-based cognitive neuroscience (MBCN) epitomizes the integrative mechanistic perspective and concentrates the most revolutionary elements of the cognitive neuroscience revolution (Boone & Piccinini, 2016). I also show how the prominent subset account of functional realization supports the integrative mechanistic perspective I take on MBCN and use it to clarify the intralevel and interlevel components of integration.

- by Mark Povich
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- Neuroscience, Psychology, Cognitive Psychology, Cognitive Science

Explanation in biology has long been characterized as being different from explanation in other scientific disciplines, in particular from explanation in physics. One of the reasons was the existence in biology of explanation types that were unheard of in the physical sciences: teleological and functional explanations, historical and evolutionary explanations. More recently, owing in part to the rise of molecular biology, biological explanations have been depicted as mechanisms. This profusion of explanatory patterns is typical of biology. The aim of the present volume Explanation in Biology. An Enquiry into the Diversity of Explanatory Patterns in the Life Sciences is to shed some new light on the diversity of explanation models in biology. In this introductory chapter, we recall the general philosophical context of scientific explanation as it has unfolded in the past seven decades, and highlight the specific issues that models of explanation have faced in biology. We then show how the different essays gathered in this collective volume tackle aspects of this important debate.

- by Christophe Malaterre and +1
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- Philosophy of Science, History and Philosophy of Biology, Mechanistic Explanation, Scientific explanation
- by Totte Harinen
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- Philosophy of Science, Causation, Mechanistic Explanation

Radical enactivism and similar embodied and enactive approaches to the mind deny that cognition is fundamentally representational, skull-bound, and mechanistic in its organisation. In this paper, I argue that modellers may still adopt a mechanistic strategy to produce explanations that are compatible with radical enactivism. This argument is scaffolded by a multi-agent model of the true slime mould Physarum polycephalum.

I argue (1) that what (ontic) New Mechanistic philosophers of science call mechanisms would be material Gestalten, and (2) that Merleau-Ponty’s engagement with Gestalt theory can help us frame a standing challenge against ontic conceptions of mechanisms. In short, until the (ontic) New Mechanist can provide us with a plausible account of the organization of mechanisms as an objective feature of mind-independent ontic structures in the world which we might discover – and no ontic Mechanist has done so – it is more conservative to claim that mechanistic organization is instead a mind-dependent aspect of our epistemic strategies of mechanistic explanation.

- by Ben Sheredos
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- Philosophy, Philosophy of Science, Philosophy of Biology, Phenomenology

In this paper, an account of theoretical integration in cognitive (neuro)science from the mechanistic perspective is defended. It is argued that mechanistic patterns of integration can be better understood in terms of constraints on representations of mechanisms, not just on the space of possible mechanisms, as previous accounts of integration had it. This way, integration can be analyzed in more detail with the help of constraint-satisfaction account of coherence between scientific representations. In particular, the account has resources to talk of idealizations and research heuristics employed by researchers to combine separate results and theoretical frameworks. The account is subsequently applied to an example of successful integration in the research on hippocampus and memory, and to a failure of integration in the research on mirror neurons as purportedly explanatory of sexual orientation.

- by Marcin Miłkowski
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- Cognitive Science, Interdisciplinarity, Mirror Neurons, Long Term Potentiation

This paper advances three related arguments showing that the ontic conception of explanation (OC), which is often adverted to in the mechanistic literature, is inferentially and conceptually incapacitated, and in ways that square poorly with scientific practice. Firstly, the main argument that would speak in favor of OC is invalid, and faces several objections. Secondly, OC's superimposition of ontic explanation and singular causation leaves it unable to accommodate scientifically important explanations. Finally, attempts to salvage OC by reframing it in terms of 'ontic constraints' just concedes the debate to the epistemic conception of explanation. Together, these arguments indicate that the epistemic conception is more or less the only game in town.

- by Cory Wright
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- Philosophy of Science, Causation, General Philosophy of Science, Explanation

The idea of levels of organization plays a central role in the philosophy of the life sciences. In this article, I first examine the explanatory goals that have motivated accounts of levels of organization. I then show that the most state-of-the-art and scientifically plausible account of levels of organization, the account of levels of mechanism proposed by Bechtel and Craver, is fundamentally problematic. Finally, I argue that the explanatory goals can be reached by adopting a deflationary approach, where levels of organization give way to more well-defined and fundamental notions, such as scale and composition.

In recent times philosophers of mathematics have generated great interest in explanations in mathematics. They have focused their attention on mathematical practice and searched for special cases that seem to own some kind of explanatory power. In this debate two main views can be identified, namely noneism and someism: the first is the view that no proof is explanatory, whereas the second is the view that some proofs are explanatory while others are not. The present paper aims to discuss this second view. I point out the main difficulties involved in this kind of research and I focus on Frans and Weber's mechanistic model. I argue that someism is a troublesome view whereas another view that I call allism seems to work better, i.e. the view that all proofs are explanatory, at least in some sense. I further claim that Frans and Weber's account can be reconsidered in a new light so that it turns out to be a proper allist model able to reveal some kind of explanatory degree in a proof.

In this chapter, we describe several representative epochs in the history of neuroscience in which understandings of the mechanisms of learning and memory phenomena were advanced. We use these historical developments to highlight unique features of mechanistic explanations in neuroscience and to explore some of the challenges associated with providing mechanistic explanations of cognitive phenomena.

- by Catherine Stinson and +1
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- History and Philosophy of Neuroscience, Philosophy of Neuroscience, Mechanistic Explanation

There is a vast literature within philosophy of artificial intelligence that focuses on the architecture of cognition, yet hardly touches on epistemological questions. There is also a growing body of work in philosophy of science about models and simulations that hardly mentions examples from cognitive science. Here these discussions are connected. Insights developed in the models and simulations literature about the importance of idealization provide a way of understanding the neural implausibility of connectionist networks. Insights from neurocognitive modeling shed light on how relevant similarities between models and targets are picked out, how inferences from models to targets are justified, and on the metaphysical status of models.

- by Catherine Stinson
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- Connectionist Modeling, Mechanistic Explanation

Daniel Dennett (1996) has disputed David Chalmers’ (1995) assertion that there is a “hard problem of consciousness” worth solving in the philosophy of mind. In this paper I defend Chalmers against Dennett on this point: I argue that there is a hard problem of consciousness, that it is distinct in kind from the so-called easy problems, and that it is vital for the sake of honest and productive research in the cognitive sciences to be clear about the difference. But I have my own rebuke for Chalmers on the point of explanation. Chalmers (1995, 1996) proposes to “solve” the hard problem of consciousness by positing qualia as fundamental features of the universe, alongside such ontological basics as mass and space-time. But this is an inadequate solution: to posit, I will urge, is not to explain. To bolster this view, I borrow from an account of explanation by which it must provide “epistemic satisfaction” to be considered successful (Rowlands, 2001; Campbell, 2009), and show that Chalmers’ proposal fails on this account. I conclude that research in the science of consciousness cannot move forward without greater conceptual clarity in the field.

- by Brian D . Earp
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- Genetics, Psychology, Clinical Psychology, Cognitive Psychology