European Journal for Philosophy of Science最新文献

I extend work from Krakauer et al. (2020), who propose a conception of individuality as the capacity to propagate information through time. From this conception, they develop information-theoretic measures. I identify several shortcomings with these measures—in particular, that they are associative rather than causal. I rectify this shortcoming by deriving a causal information-theoretic measure of individuality. I then illustrate how this measure can be implemented and extended in the context of evolutionary transitions in individuality.

The reactions that science triggers on the people it studies, describes, or theorises about, can affect the science itself and its claims to knowledge. This phenomenon, which we call reactivity, has been discussed in many different areas of the social sciences and the philosophy of science, falling under different rubrics such as the Hawthorne effect, self-fulfilling prophecies, the looping effects of human kinds, the performativity of models, observer effects, experimenter effects and experimenter demand effects. In this paper we review state-of-the-art research that falls under the remit of the philosophy of reactivity by considering ontological, epistemic and moral issues that reactivity raises. Along the way, we devote special attention to articles belonging to this journal's Topical Collection entitled “Reactivity in the Human Sciences”.

In the science and values literature, scholars have shown how science is influenced and shaped by values, often in opposition to the ‘value free’ ideal of science. In this paper, we aim to contribute to the science and values literature by showing that the relation between science and values flows not only from values into scientific practice, but also from (allegedly neutral) science to values themselves. The extant literature in the ‘science and values’ field focuses by and large on reconstructing, post hoc, how values have influenced science; our reconstruction of the case studies, instead, aims to show that scientific concepts and methods too, because of specific identifiable characteristics, can promote some values rather than (or at the expense of) others. We explain this bidirectional relation in analogy to debates on the normativity of technical artifacts and on feminist approaches in science, and we illustrate our claims with cases from the health sciences and machine learning. While our arguments in this paper also draw on post hoc reconstructions, we intend to show where, in the science in the making, we should engage not only with the question whether a practice is value-laden, but also how specific conceptual and methodological choices can influence values down the road. All in all, these considerations expand the ways in which philosophers can contribute to more value-aware scientific practices.

In a recent article, David Ludwig proposed to reorient the debate on natural kinds away from inquiring into the naturalness of kinds and toward elucidating the materiality of kinds. This article responds to Ludwig’s critique of a recently proposed account of kinds and classification, the Grounded Functionality Account, against which Ludwig offsets his own account, and criticizes Ludwig’s proposal to shift focus from naturalness to materiality in the philosophy of kinds and classification.

Recently, there has been an increased interest in employing model-based definitions of actual causation in legal inquiry. The formal precision of such approaches promises to be an improvement over more traditional approaches. Yet model-based approaches are viable only if suitable models of legal cases can be provided, and providing such models is sometimes difficult. I argue that causal-model-based definitions benefit legal inquiry in an indirect way. They make explicit the causal assumptions that need to be made plausible to defend a particular claim of actual causation. My argument concerns the analysis of legal cases involving a combination of double prevention and causal redundancy. I show that discussions among legal theorists about such cases sometimes suffer from ambiguous assumptions about the causal structure. My account illustrates that causal models can act as a heuristic tool for clarifying such assumptions, and that causal models provide a framework for more accurate analyses of legal cases involving complex causal structure.

Abstract

Computer assisted theorem proving is an increasingly important part of mathematical methodology, as well as a long-standing topic in artificial intelligence (AI) research. However, the current generation of theorem proving software have limited functioning in terms of providing new proofs. Importantly, they are not able to discriminate interesting theorems and proofs from trivial ones. In order for computers to develop further in theorem proving, there would need to be a radical change in how the software functions. Recently, machine learning results in solving mathematical tasks have shown early promise that deep artificial neural networks could learn symbolic mathematical processing. In this paper, I analyze the theoretical prospects of such neural networks in proving mathematical theorems. In particular, I focus on the question how such AI systems could be incorporated in practice to theorem proving and what consequences that could have. In the most optimistic scenario, this includes the possibility of autonomous automated theorem provers (AATP). Here I discuss whether such AI systems could, or should, become accepted as active agents in mathematical communities.

The question of whether Everettian quantum mechanics (EQM) justifies the existence of metaphysical indeterminacy has recently come to the fore. Metaphysical indeterminacy has been argued to emerge from three sources: coherent superpositions, the indefinite number of branches in the quantum multiverse and the nature of these branches. This paper reviews the evidence and concludes that those arguments don’t rely on EQM alone and rest on metaphysical auxiliary assumptions that transcend the physics of EQM. We show how EQM can be ontologically interpreted without positing metaphysical indeterminacy by adopting a deflationary attitude towards branches. Two ways of developing the deflationary view are then proposed: one where branches are eliminated, and another where they are reduced to the universal quantum state.

Modeling his position on Arthur Fine’s Natural Ontological Attitude, Derek Turner proposed the Natural Historical Attitude. Although these positions share a family resemblance, Turner’s position differs from Fine’s in two important ways. First, Fine’s contextualism is more fine-grained. Second, Turner’s argument for metaphysical agnosticism seems to lead to the implausible conclusion that we should be agnostic about the mind-independence of ordinary objects – a position in tension with Fine’s “core position.” While this paper presents a textual analysis of Fine’s and Turner’s arguments, the conclusions reached here cohere well with some of the best empirically-informed assessments of the historical sciences. Given the diversity of the historical sciences, the fact that many claims in the historical sciences have enough support to be regarded as true, and the implausibility of Turner’s agnosticism, philosophers studying historical science would be better served by embracing a stance closer to Fine’s Natural Ontological Attitude.

Abstract

While dissent is key to successful science, it is not always beneficial. By requiring scientists to respond to objections, epistemically detrimental dissent (EDD) consumes resources that could be better devoted to furthering scientific discovery. Moreover, bad-faith dissent can create a chilling effect on certain lines of inquiry and make settled controversies seem open to debate. Such dissent results in harm to scientific progress and the public policy that depends on this science. Biddle and Leuschner propose four criteria that draw on inductive risk as a method for separating this EDD from beneficial dissent while de Melo-Martín and Intemann reject this approach for failing to capture paradigmatic instances of EDD. Against de Melo-Martín and Intemann’s objections, I propose the inductive risk account can be saved and strengthened through the following modifications: (1) removing the requirement that the four conditions of EDD be jointly satisfied, (2) requiring that each criterion be measured as a matter of degree rather than as a binary, and (3) requiring that the four criteria are measured holistically. These modifications not only mitigate the criticisms but produce five benefits over Biddle and Leuschner’s account, including: (1) capturing paradigmatic instances of EDD, (2) reflecting the degree to which an instance of EDD is problematic, (3) capturing the interactions between criteria, (4) avoiding legitimizing inappropriate dissent, and (5) reflecting changes to the epistemic standing of dissent. As such, I argue that the modified IndRA provides a powerful tool for identifying EDD and strengthening science.

Heterogeneous treatment effects represent a major issue for medicine as they undermine reliable inference and clinical decision-making. To overcome the issue, the current vision of precision and personalized medicine acknowledges the need to control individual variability in response to treatment. In this paper, we argue that gene-treatment-environment interactions (G × T × E) undermine inferences about individual treatment effects from the results of both genomics-based methodologies—such as genome-wide association studies (GWAS) and genome-wide interaction studies (GWIS)—and randomized controlled trials (RCTs). Then, we argue that N-of-1 trials can be a solution to overcome difficulties in handling individual variability in treatment response. Although this type of trial has been suggested as a promising strategy to assess individual treatment effects, it nonetheless has limitations that limit its use in everyday clinical practice. We analyze the existing variability within the designs of N-of-1 trials in terms of a continuum where each design prioritizes epistemic and pragmatic considerations. We then support wider use of the designs located at the pragmatic end of the explanatory-pragmatic continuum.