Computationalism—the view that cognition is computation—has always been controversial. It faces two types of objection. According to insufficiency objections, computation is insufficient for some cognitive phenomenon X. According to objections from neural realization, cognitive processes are realized by neural processes, but neural processes have feature Y, and having Y is incompatible with being (or realizing) computations. In this article, I explain why computationalism has survived these objections. To adjudicate the dispute between computationalism and its foes, I will conclude that we need a better account of computation.

Daniel Dennett distinguishes real patterns from bogus patterns by appeal to compressibility. As information theorists have shown, data are compressible if and only if those data exhibit a pattern. Noting that high-level models are much simpler than their low-level counterparts, Dennett interprets high-level models as compressed representations of the fine-grained behavior of their target system. As such, he argues that high-level models depend on patterns in this behavior. Unfortunately, data scientific practice complicates Dennett’s interpretation, undermining the traditional justification for real patterns and suggesting a revised research program for its defenders.

Recently Halpern and Pearl and Hitchcock have presented influential accounts of actual (token) causation using Bayesian networks. These accounts have been deterministic. Here we present a probabilistic extension to these active path analyses of actual causation. The extension uses “soft” interventions to set distributions rather than just single values. The resulting account can handle at least as wide a range of examples as the original accounts, without assuming determinism.

Huggett and Weingard's critical review provides an opportunity to continue the interpretive examination of quantum field theory in terms of some specific issues as well as comparison of alternative approaches to the subject. This note recasts their example of inequivalent Fock spaces in an effort to further clarify what it illustrates. Questions are addressed about the role of analogy in developing quantum field theory and about the conflict between formal vs. concrete methods in both physics and its interpretation, continuing the well-known historical debate between Pierre Duhem and Clark Maxwell. Huggett and Weingard's examination very usefully occasions clarification on some points of exposition which, it is hoped, will make An Interpretive Introduction to Quantum Field Theory a more useful resource for understanding this subject.

One thing which has struck me most as I have read the articles of the Encyclopedia of Unified Science is the complexity that can be discerned in many of the operations which for the purpose of the article are treated as elementary. It is apparent that Unity of Science, like every other discipline, has its own stock of “atoms of discourse”, suited to its own purposes. Experience in physics would prepare one to expect that for certain purposes it may be profitable to attempt to analyze these atoms further. The atom of discourse, or presupposition commonly made by most adherents of the Unity of Science movement, with which I shall be chiefly concerned, is with regard to the nature of “science“. My present concern with this matter has arisen from my extreme difficulty in communicating my meaning to other people. The difficulty has been a genuine puzzle to me, until quite recently a discussion with one of my colleagues disclosed a difference of attitude on fundamental matters so revelatory that I am encouraged to return again to the attack.

Success-to-truth inferences have been the realist stronghold for a long time. Scientific success is the parameter by which realists claim to discern approximately true theories from false ones. But scientific success needs to be probed a bit deeper. In this article, I tell three tales of scientific success, by considering in turn success from nowhere, success from here now, and success from within. I argue for a suitable version of success from within that can do justice to the historically situated nature of our scientific knowledge. The outcome is a new way of thinking about success-to-truth inferences along perspectivalist lines.

Utilizing Carnap's notions of “questions [or assertions] within a framework” and “questions [or assertions] about a framework” and his account of A-truth (analyticity in the broad sense), a theory of the ontological status of entities—in particular, that of theoretical entities—is adumbrated.

In addition to the usual L-rules, each conceptual framework considered embodies a set of sentences whose truth value is quickly decidable on other than purely linguistic grounds, a set of A-true formulae, and a set of rules for the confirmation and disconfirmation of non-L-true, non-A-true formulae which are not quickly decidable. Criteria which acceptable sets of A-true formulae must fulfill are given.

Using this apparatus, a schema for a realistic interpretation of scientific theories is outlined.

The value-ladenness of computer algorithms is typically framed around issues of epistemic risk. In this article, I examine a deeper sense of value-ladenness: algorithmic methods are not only themselves value-laden but also introduce value into how we reason about their domain of application. I call this domain distortion. In particular, using insights from jurisprudence, I show that the use of recidivism risk assessment algorithms (1) presupposes legal formalism and (2) blurs the distinction between liability assessment and sentencing, which distorts how the domain of criminal punishment is conceived and provides a distinctive avenue for values to enter the legal process.

Though one believes that P is true, one can have reasons for thinking it false. Yet, it seems that one cannot know that P is true and (still) have reasons for thinking it false. Why is this so ? What feature of knowledge (or of reasons) precludes having reasons or evidence to believe (true) what you know to be false? If the connection between reasons (evidence) and what one believes is expressible as a probability relation, it would seem that the only satisfactory explanation of this fact is that when one knows that P is true, the reasons or evidence one has in support of P are such as to confer upon P the probability of 1. It is shown by an application of Bayes' Theorem that any value smaller than 1 would permit having reasons to believe what one knows to be false. Hence, it would seem that knowledge requires conclusive reasons to believe (if reasons or evidence is required at all).

Rédei and Gyenis suggest that Lewis’s Principal Principle is meaningful only if it satisfies certain consistency conditions: starting from any assignment of credences to some algebra of events, we must always be able to extend our algebra with events as “the value of the objective chance of event E is p” and assign credences to such events in a consistent manner. I show that this extension is possible. However, I also argue that this requirement is unnecessary: the Principal Principle concerns subjective beliefs about objective chance; hence, events concerning those probabilities are meant to be in the algebra initially.

Among philosophers of science nearly a century ago the dominant attitude was that (in Rudolph Carnap's words) philosophy of science was “like science itself, neutral with respect to practical aims, whether they are moral aims for the individual, or political aims for a society.” The dominant attitude today is not much different: our aim is still to articulate scientific rationality, and our understanding of that rationality still excludes the moral and political. I contrast this with the growing entanglements within the sciences of the ethical and the epistemic, and I suggest ways in which philosophers of science can usefully respond.

I present a response to Vollmer's review of the book Of Minds and Molecules, and especially her comments on my own article therein. This provides an opportunity to discuss two central ideas in the philosophy of chemistry. These are the distinction between elements as simple substances (element-1) and elements as basic substances (element-2) and Paneth's proposed intermediate position for philosophy of chemistry. The response also discusses the question of isotopes in relationship to the nature of the elements and their classification as well as the philosophical status of atomic orbitals.

In this paper, I provide an account of scientific representation that makes sense of the notion both at the nanoscale and at the quantum level: the partial mappings account. The account offers an extension of a proposal developed by R. I. G. Hughes in terms of denotation, demonstration, and interpretation (DDI). I first argue that the DDI account needs some amendments to accommodate representation of nano and quantum phenomena. I then introduce a generalized framework with the notions of unsharp denotation, unsharp interpretation, and partial mappings. I conclude by arguing that the resulting view not only accommodates nano and quantum representations but also makes sense of representation by imaging in (scanning tunneling) microscopy.

Hermann Weyl succeeded in presenting a consistent overarching analysis that accounts for symmetry in (1) material artifacts, (2) natural phenomena, and (3) physical theories. Weyl showed that group theory is the underlying mathematical structure for symmetry in all three domains. But in this study Weyl did not include appeals to symmetry arguments which, for example, Einstein expressed as “for reasons of symmetry” (wegen der Symmetrie; aus Symmetriegründen). An argument typically takes the form of a set of premises and rules of inference that lead to a conclusion. Symmetry may enter an argument both in the premises and the rules of inference, and the resulting conclusion may also exhibit symmetrical properties. Taking our cue from Pierre Curie, we distinguish two categories of symmetry arguments, axiomatic and heuristic; they will be defined and then illustrated by historical cases.

This paper examines the problem of founding irreversibility on reversible equations of motion from the point of view of the Brussels school's recent developments in the foundations of quantum statistical mechanics. A detailed critique of both their ‘subdynamics’ and ‘transformation’ theory is given. It is argued that the subdynamics approach involves a generalized form of ‘coarse-graining’ description, whereas, transformation theory cannot lead to truly irreversible processes pointing to a preferred direction of time. It is concluded that the Brussels school's conception of microscopic temporal irreversibility, as such, is tacitly assumed at the macroscopic level. Finally a logical argument is provided which shows, independently of the mathematical formalism of the theory concerned, that statistical reasoning alone is not sufficient to explain the arrow of time.

What one is acquainted with has always been important for the rejection or acceptance of any ontological description. Yet the relevance of acquaintance to ontology has not always been clearly stated. Some philosophers have held that they were acquainted with the simple entities of ontological analysis. They also held that if they were not acquainted with such entities, their analysis would be inadequately supported. In this paper I argue that acquaintance with ontological simples cannot be a reason for accepting or rejecting any ontological analysis. At the same time, I examine what I believe to be the relevance of acquaintance to ontological description.