The philosophical novelty of computer simulation methods

Humphreys, Paul

doi:10.1007/s11229-008-9435-2

Cited by 219 publications

(159 citation statements)

References 11 publications

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“…Others have described complex simulations as only engaging "the same old stew" of standard epistemological questions (Frigg and Reiss 2009). In response, Humphreys (2009) outlined four specific issues that, in his view, make complex simulations stand out from other kinds of science: 1) the difficulty in understanding why a simulation produces the results that it does from the theory it encodes ("epistemic opacity"), 2) the intertwining of semantic and syntactic variations in applying the model to its target system, 3) the time iterative nature of most simulations, and 4) the unavoidable difference between what is doable in principle, and what is doable in practice. Humphreys claims that each of these four issues are grounded in the idea that simulations require an epistemology in which human actions are no longer central.…”

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confidence: 99%

A practical philosophy of complex climate modelling

Schmidt

Sherwood

2014

Euro Jnl Phil Sci

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We give an overview of the practice of developing and using complex climate models, as seen from experiences in a major climate modelling center and through participation in the Coupled Model Intercomparison Project (CMIP). We discuss the construction and calibration of models; their evaluation, especially through use of out-of-sample tests; and their exploitation in multi-model ensembles to identify biases and make predictions. We stress that adequacy or utility of climate models is best assessed via their skill against more naïve predictions. The framework we use for making inferences about reality using simulations is naturally Bayesian (in an informal sense), and has many points of contact with more familiar examples of scientific epistemology. While the use of complex simulations in science is a development that changes much in how science is done in practice, we argue that the concepts being applied fit very much into traditional practices of the scientific method, albeit those more often associated with laboratory work.

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confidence: 99%

A practical philosophy of complex climate modelling

Schmidt

Sherwood

2014

Euro Jnl Phil Sci

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“…In [Humphreys, 2004] (section 1.2 pp. 6-8), he argues that "our own intellectual and computational capabilities as human beings is no more the benchmark of scientific thought", and in [Humphreys, 2009] (section 2) he adds that "Computational science introduces new issues into the philosophy of science because it uses methods that push humans away from the center of the epistemological enterprise" and that:"[...]the situation within which humans deal with science that is carried out at least in part by machines [is] the hybrid scenario and the more extreme situation of a completely automated science [is] the automated scenario [...]". In our view the changes brought by the methods of data analysis are not simply an issue of automated versus human science.…”

Section: Discussion What Role For Mathematics?mentioning

confidence: 99%

Agnostic Science. Towards a Philosophy of Data Analysis

Napoletani

Panza²,

Struppa³

2010

Found Sci

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In this paper we will offer a few examples to illustrate the orientation of contemporary research in data analysis and we will investigate the corresponding role of mathematics. We argue that the modus operandi of data analysis is implicitly based on the belief that if we have collected enough and sufficiently diverse data, we will be able to answer most relevant questions concerning the phenomenon itself. This is a methodological paradigm strongly related, but not limited to, biology, and we label it the microarray paradigm. In this new framework, mathematics provides powerful techniques and general ideas which generate new computational tools. But it is missing any explicit isomorphism between a mathematical structure and the phenomenon under consideration. This methodology used in data analysis suggests the possibility of forecasting and analyzing without a structured and general understanding. This is the perspective we propose to call agnostic science, and we argue that, rather than diminishing or flattening the role of mathematics in science, the lack of isomorphisms with phenomena liberates mathematics, paradoxically making more likely the practical use of some of its most sophisticated ideas.

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“…Since the early 1950s, theories and experiments, the two basic paradigms brought at the hearth of science by the Galilean revolution, have been joined by computer simulations, a qualitatively new research method "lying somewhere intermediate between traditional theoretical science and its empirical methods of experimentation and observation" [21]. Often defined as the "third paradigm" of science, computer simulations have gradually enabled the "in silico" exploration of phenomena otherwise inaccessible, sparking a huge debate in many areas of scientific research (see, merely as an example, in the body of scientific literature that spans from plasma physics to biology, from linguistics to cognitive and social science: [22][23][24][25][26][27]) and, understandably, in philosophy of science [28,29].…”

Section: The Computational and Data Driven Turn Of Sciencementioning

confidence: 99%

Ex Machina: Analytical platforms, Law and the Challenges of Computational Legal Science

Lettieri¹,

Altamura

Giugno

et al. 2018

Future Internet

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Over the years, computation has become a fundamental part of the scientific practice in several research fields that goes far beyond the boundaries of natural sciences. Data mining, machine learning, simulations and other computational methods lie today at the hearth of the scientific endeavour in a growing number of social research areas from anthropology to economics. In this scenario, an increasingly important role is played by analytical platforms: integrated environments allowing researchers to experiment cutting-edge data-driven and computation-intensive analyses. The paper discusses the appearance of such tools in the emerging field of computational legal science. After a general introduction to the impact of computational methods on both natural and social sciences, we describe the concept and the features of an analytical platform exploring innovative cross-methodological approaches to the academic and investigative study of crime. Stemming from an ongoing project involving researchers from law, computer science and bioinformatics, the initiative is presented and discussed as an opportunity to raise a debate about the future of legal scholarship and, inside of it, about the challenges of computational legal science.

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The philosophical novelty of computer simulation methods

Cited by 219 publications

References 11 publications

A practical philosophy of complex climate modelling

A practical philosophy of complex climate modelling

Agnostic Science. Towards a Philosophy of Data Analysis

Ex Machina: Analytical platforms, Law and the Challenges of Computational Legal Science

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