Studies in History and Philosophy of Science最新文献

We inquire into the role of Turing’s biological thought in the development of his concept of intelligent machinery. We trace the possible relations between his proto-connectionist notion of ‘organising’ machines in Turing (1948) on the one hand and his mathematical theory of morphogenesis in developmental biology (1952) on the other. These works were concerned with distinct fields of inquiry and followed distinct paradigms of biological theory, respectively postulating analogues of Darwinian selection in learning and mathematical laws of form in organic pattern formation. Still, these strands of Turing’s work are related, first, in terms of being amenable in principle to his (1936) computational method of modelling. Second, they are connected by Turing’s scattered speculations about the possible bearing of learning processes on the anatomy of the brain. We argue that these two theories form an unequal couple that, from different angles and in partial fashion, point towards cognition as a biological and embodied phenomenon while, for reasons inherent to Turing’s computational approach to modelling, not being capable of directly addressing it as such. We explore ways in which these two distinct-but-related theories could be more explicitly and systematically connected, using von Neumann’s contemporaneous and related work on Cellular Automata and more recent biomimetic approaches as a foil. We conclude that the nature of ‘initiative’ and the mode of material realisation are the key issues that decide on the possibility of intelligent machinery in Turing.

Here I look to some work in the historical sciences in order to draw out some of the epistemic benefits of “speculative narratives,” which bears on some more general epistemic benefits of speculative reasoning. Due to the contingent nature of much historical evidence, some degree of speculative reasoning is necessary to get the epistemological ball rolling in the historical sciences, and I argue that speculative narratives provide the necessary sort of frameworking apparatus for doing precisely this. I use contemporary work on the first peopling of the Americas (the “Clovis First Debate”) for illustration.

In the second half of the 20th century, neuroscientists across North America developed automated systems for use in their research laboratories. Their decisions to do so were complex and contingent, partly a result of global reasons, such as the need to increase efficiency and flexibility, and partly a result of local reasons, such as the need to amend perceived biases of earlier research methodologies. Automated methods were advancements but raised several challenges. Transferring a system from one location to another required that certain components of the system be standardized, such as the hardware, software, and programming language. This proved difficult as commercial manufacturers lacked incentives to create standardized products for the few neuroscientists working towards automation. Additionally, investing in automated systems required massive amounts of time, labor, funding, and computer expertise. Moreover, neuroscientists did not agree on the value of automation. My brief history investigates Karl Pribram's decisions to expand his newly created automated system by standardizing equipment, programming, and protocols. Although he was an eminent Stanford neuroscientist with strong institutional support and computer know-how, the development and transfer of his automated behavioral testing system was riddled with challenges. For Pribram and neuroscience more generally, automation was not so automatic.

Mainstream and alternative nutrition doctrines have crucially shaped our understanding of the vital aspects of and forces in human nutrition. Drawing upon a diverse array of sources, this article delves into cultural, social, and scientific conceptions of vital nutrition and how they evolved in relation to the Finnish obesity discourse from the 1950s to the 1970s. The Association to Combat Obesity (ACO), which brought together nutrition scientists, food faddists and laypeople, was the driving force of these debates. In the context of this article, food was perceived to influence the vitality of individuals and nations through its effect on body weight. Obese bodies seemed to conflict with both utopian visions of bodily transcendence and the ideals of wellbeing in modern health sciences. This work highlights the ideological continuities between interwar and postwar nutrition debates as well as the persistent tensions between scientific advancements and alternative nutrition philosophies. They have molded the conceptions of vitality and attitudes towards obesity. Concludingly, we suggest that the social responses to obesity have been influenced by the condition's perceived adverse relationship to vitality, in which fat has acted as a persistent reminder of corporeality, death, and decay.

Over the past century, the scientific conception of the protein has evolved significantly. This paper focuses on the most recent stage of this evolution, namely, the origin of the dynamic view of proteins and the challenge it posed to the static view of classical molecular biology. Philosophers and scientists have offered two hypotheses to explain the origin of the dynamic view and its slow reception by structural biologists. Some have argued that the shift from the static to the dynamic view was a Kuhnian revolution, driven by the accumulation of dynamic anomalies, while others have argued that the shift was caused by new empirical findings made possible by technological advances. I analyze this scientific episode and ultimately reject both of these empiricist accounts. I argue that focusing primarily on technological advances and empirical discoveries overlooks the important role of theory in driving this scientific change. I show how the application of general thermodynamic principles to proteins gave rise to the dynamic view, and a commitment to these principles then led early adopters to seek out the empirical examples of protein dynamics, which would eventually convince their peers. My analysis of this historical case shows that empiricist accounts of modern scientific progress—at least those that aim to explain developments in the molecular life sciences—need to be tempered in order to capture the interplay between theory and experiment.

Chronostratigraphy is the subfield of geology that studies the relative age of rock strata and that aims at producing a hierarchical classification of (global) divisions of the historical time-rock record. The ‘golden spike’ or ‘GSSP’ approach is the cornerstone of contemporary chronostratigraphic methodology. It is also perplexing. Chronostratigraphers define each global time-rock boundary extremely locally, often by driving a gold-colored pin into an exposed rock section at a particular level. Moreover, they usually avoid rock sections that show any meaningful sign of paleontological disruption or geological discontinuity: the less obvious the boundary, the better. It has been argued that we can make sense of this practice of marking boundaries by comparing the status and function of golden spikes to that of other concrete, particular reference standards from other sciences: holotypes from biological taxonomy and measurement prototypes from the metrology of weight and measures. Alisa Bokulich (2020b) has argued that these ‘scientific types’ are in an important sense one of a kind: they have a common status and function. I will argue that this picture of high-level conceptual unity is mistaken and fails to consider the diversity of aims and purposes of standardization and classification across the sciences. I develop an alternative, disunified account of scientific types that shows how differences in ontological attitudes and epistemic aims inform scientists’ choices between different kinds of scientific types. This perspective on scientific types helps to make sense of an intriguing mid-twentieth-century debate among chronostratigraphers about the very nature of their enterprise. Should chronostratigraphers conventionally make boundaries by designating golden spikes, or should they attempt to mark pre-existing ‘natural’ boundaries with the help of a different kind of scientific type?

Leibniz's famous proposition that God has created the best of all possible worlds holds a significant place in his philosophical system. However, the precise manner in which God determines which world is the best remains somewhat ambiguous. Leibniz suggests that a form of "Divine mathematics" is employed to construct and evaluate possible worlds. In this paper, I uncover the underlying mechanics of Divine mathematics by formally reconstructing it. I argue that Divine mathematics is a one-player combinatorial game, in which God's goal is to find the best combination among many possibilities. Drawing on the combinatorial theory, I provide new solutions to some puzzles of compossibility.

Using a ‘reformulation of Bell’s theorem’, Waegell and McQueen, (2020) argue that any local theory which does not involve retro-causation or fine-tuning must be a many-worlds theory. Moreover they argue that non-separable many-worlds theories whose ontology is given by the wavefunction involve superluminal causation, as opposed to separable many-worlds theories (e.g. Waegell, 2021; Deutsch and Hayden 2000).

I put forward three claims. (A) I challenge their argument for relying on a non-trivial, unquestioned assumption about elements of reality which allows Healey’s approach (Healey, 2017b) to evade their claim. In an attempt to respond to (A), Waegell and McQueen may restrict their claim to theories which satisfy such an assumption, however, I also argue that (B) their argument fails to prove even the so weakened claim, as exemplified by theories that are both non-separable and local. Finally, (C) by arguing for the locality of the decoherence-based Everettian approach (Wallace, 2012) I refute Waegell and McQueen’s claim that wavefunction-based ontologies, and more generally non-separable ontologies, involve superluminal causation. I close with some doubtful remarks about separable Everettian interpretations as compared to non-separable ones.

This paper argues against the claim that high-energy physics experiments done so far could not be carried out without computer simulations. We show that it would be possible to completely dispense with computer simulations for experiments conducted to date, and that computer simulations up to now are mostly used for practical reasons. Our investigation covers all elements of experimental research in which computer simulations have been used. Dispensing with simulations would yield an advantage with regard to the complex theory dependence of experiments. We also point out that computer simulations may play a more essential role for the complex measurements foreseen at the Large Hadron Collider, where subtle dependencies between final state objects in high-energy physics experiments must be accurately described. Therefore, the conceivable complete replacement of computer simulations may have come to an end, and the theory dependence of high-energy physics experiments through computer simulations may be entering a new phase.