The Crux of Crucial Experiments: Duhem's Problems and Inference to the Best Explanation

Going back at least to Duhem, there is a tradition of thinking that crucial experiments are impossible in science. I analyse Duhem's arguments and show that they are based on the excessively strong assumption that only deductive reasoning is permissible in experimental science. This opens the possibility that some principle of inductive inference could provide a sufficient reason for preferring one among a group of hypotheses on the basis of an appropriately controlled experiment. To be sure, there are analogues to Duhem's problems that pertain to inductive inference. Using a famous experiment from the history of molecular biology as an example, I show that an experimentalist version of inference to the best explanation (IBE) does a better job in handling these problems than other accounts of scientific inference. Furthermore, I introduce a concept of experimental mechanism and show that it can guide inferences from data within an IBE-based framework for induction. Introduction Duhem on the Logic of Crucial Experiments ‘The Most Beautiful Experiment in Biology' Why Not Simple Elimination? Severe Testing An Experimentalist Version of IBE 6.1Physiological and experimental mechanisms 6.2Explaining the data 6.3IBE and the problem of untested auxiliaries 6.4IBE-turtles all the way down Van Fraassen's ‘Bad Lot' Argument IBE and Bayesianism Conclusion

Griffiths' psychoevolutionary theory of basic emotions: is the automatic appraisal mechanism informationally encapsulated?

Màster en Filosofia Analítica (APhil), Facultat Filosofía, Universitat de Barcelona, Curs: 2013-2014, Director/Tutor: David PinedaGriffiths argues that a system which triggers the emotional response, named automatic appraisal mechanism (AAM), is informationally encapsulated (Griffiths, 1997). After proposing a clarification of the AAM using Shea's taxonomy (Shea, 2013), I will claim that Griffiths' inference to the best explanation in favor of the informational encapsulation of the AAM is not compelling. I will present empirical evidence (Paquette et al., 2003) that is incompatible with the thesis of the informational encapsulation of the AAM in order to cast doubts on Griffiths' explanation, and I will propose an alternative one. My alternative explanation will be that the AAM is synchronically impenetrable, and I will affirm that it is preferable over Griffiths' one because is less theoretically demanding, and moreover in accordance with empirical evidence that shows the possibility of diachronic cognitive penetration of the AAM. I will conclude by claiming that this revision can provide also a better account of the irrationality of recalcitrant emotions

Informational Virtues, Causal Inference, and Inference to the Best Explanation

Frank Cabrera argues that informational explanatory virtues—specifically, mechanism, precision, and explanatory scope—cannot be confirmational virtues, since hypotheses that possess them must have a lower probability than less virtuous, entailed hypotheses. We argue against Cabrera’s characterization of confirmational virtue and for an alternative on which the informational virtues clearly are confirmational virtues. Our illustration of their confirmational virtuousness appeals to aspects of causal inference, suggesting that causal inference has a role for the explanatory virtues. We briefly explore this possibility, delineating a path from Mill’s method of agreement to Inference to the Best Explanation (IBE)

Explanation and Ontological Reasoning

Philosophical work on explanation has focused on the following two topics: theories of explanation, intended to enumerate necessary and sufficient conditions for explanation, and inference to the best explanation as the strongest form of justification for ontological or metaphysical claims. I critically examine the most important philosophical work in both of these areas and defend my own conclusions about the connections between explanation and ontology. I argue that all of our inferences about the nature of the world, in ontology or metaphysics, presuppose criteria for acceptable explanation. I first examine the metaphysics of Plato, Aristotle, and Leibniz, arguing that their metaphysical reasoning was guided by assumptions about the nature of explanation. I also survey some recent work in ontology and find inference to the best explanation offered as the strongest available method of defending existence claims. To conclude this discussion, I offer an original argument for the thesis that all reasoning about existence claims, being nondeductive, presupposes some criteria for acceptable explanations, or a theory of explanation. Carl Hempel and Wesley Salmon have been two of the most influential philosophers offering theories of explanation, and I examine their work with the intention of discovering ontological or metaphysical assumptions shaping their theories of explanation. I argue that Hempel's theory rests on deterministic assumptions, and I argue the Salmon's theory of causality, which he admits supports his theory of explanation, is subject to empiricist criticisms. Theories of explanation typically rest on assumptions about the nature of the world, I argue, and I explain why this is so with an original theory of explanation connecting it to the psychological phenomenon of understanding. We rely on understanding in the identification of explanations, and understanding requires establishing a metaphysical context for an explanandum-event. I end by indicating the possibility of generating vicious justificatory circles through the reciprocal relationship of support between explanation and ontology, and I argue that vicious circles can be avoided only by grounding all ontological reasoning in a fundamental explanatory task of giving order to experience through a system of categorie

Beyond the Limits of Imagination: Abductive inferences from imagined phenomena

The present paper proposes a route to modal claims that allows us to infer to certain possibilities even if they are sensorily unimaginable and beyond the evidential capacity of stipulative imagining. After a brief introduction, Sect. 2 discusses imaginative resistance to help carve a niche for the kinds of inferences about which this essay is chiefly concerned. Section 3 provides three classic examples, along with a discussion of their similarities and differences. Section 4 recasts the notion of potential explanation in Lipton’s (Inference to the best explanation, Routledge, Abingdon, 2004) in order to accommodate inferences to possibility claims; Sect. 5 then attempts to characterise a principle underlying such inferences. Section 6 concludes by discussing how the proposal relates to other modal epistemologies, with emphasis on the potential of such inferences to produce genuinely new ideas

Kevin McCain and Ted Poston’s Best Explanations

In this critical notice, I focus my attention on the chapters that deal with the explanationist response to skepticism

Inference to the Best Explanation and the Screening-Off Challenge

We argue in Roche and Sober (2013) that explanatoriness is evidentially irrelevant in that Pr(H | O&EXPL) = Pr(H | O), where H is a hypothesis, O is an observation, and EXPL is the proposition that if H and O were true, then H would explain O. This is a “screening-off” thesis. Here we clarify that thesis, reply to criticisms advanced by Lange (2017), consider alternative formulations of Inference to the Best Explanation, discuss a strengthened screening-off thesis, and consider how it bears on the claim that unification is evidentially relevant

Abductively Robust Inference

Inference to the Best Explanation (IBE) is widely criticized for being an unreliable form of ampliative inference – partly because the explanatory hypotheses we have considered at a given time may all be false, and partly because there is an asymmetry between the comparative judgment on which an IBE is based and the absolute verdict that IBE is meant to license. In this paper, I present a further reason to doubt the epistemic merits of IBE and argue that it motivates moving to an inferential pattern in which IBE emerges as a degenerate limiting case. Since this inferential pattern is structurally similar to an argumentative strategy known as Inferential Robustness Analysis (IRA), it effectively combines the most attractive features of IBE and IRA into a unified approach to non-deductive inference

There are no universal rules for induction

In a material theory of induction, inductive inferences are warranted by facts that prevail locally. This approach, it is urged, is preferable to formal theories of induction in which the good inductive inferences are delineated as those conforming to universal schemas. An inductive inference problem concerning indeterministic, nonprobabilistic systems in physics is posed, and it is argued that Bayesians cannot responsibly analyze it, thereby demonstrating that the probability calculus is not the universal logic of induction. Copyright 2010 by the Philosophy of Science Association.All right reserved

On Probability and Cosmology: Inference Beyond Data?

Modern scientific cosmology pushes the boundaries of knowledge and the knowable. This is prompting questions on the nature of scientific knowledge. A central issue is what defines a 'good' model. When addressing global properties of the Universe or its initial state this becomes a particularly pressing issue. How to assess the probability of the Universe as a whole is empirically ambiguous, since we can examine only part of a single realisation of the system under investigation: at some point, data will run out. We review the basics of applying Bayesian statistical explanation to the Universe as a whole. We argue that a conventional Bayesian approach to model inference generally fails in such circumstances, and cannot resolve, e.g., the so-called 'measure problem' in inflationary cosmology. Implicit and non-empirical valuations inevitably enter model assessment in these cases. This undermines the possibility to perform Bayesian model comparison. One must therefore either stay silent, or pursue a more general form of systematic and rational model assessment. We outline a generalised axiological Bayesian model inference framework, based on mathematical lattices. This extends inference based on empirical data (evidence) to additionally consider the properties of model structure (elegance) and model possibility space (beneficence). We propose this as a natural and theoretically well-motivated framework for introducing an explicit, rational approach to theoretical model prejudice and inference beyond data