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Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism. / Duran, Juan Manuel; Formanek, N.

In: Minds and Machines: journal for artificial intelligence, philosophy and cognitive sciences, 10.2018.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

Duran, JM & Formanek, N 2018, 'Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism' Minds and Machines: journal for artificial intelligence, philosophy and cognitive sciences. https://doi.org/10.1007/s11023-018-9481-6

APA

Duran, J. M., & Formanek, N. (2018). Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism. Minds and Machines: journal for artificial intelligence, philosophy and cognitive sciences. https://doi.org/10.1007/s11023-018-9481-6

Vancouver

Duran JM, Formanek N. Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism. Minds and Machines: journal for artificial intelligence, philosophy and cognitive sciences. 2018 Oct. https://doi.org/10.1007/s11023-018-9481-6

Author

Duran, Juan Manuel ; Formanek, N. / Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism. In: Minds and Machines: journal for artificial intelligence, philosophy and cognitive sciences. 2018.

BibTeX

@article{4ff43b0c7e3e4fedb7e563766edcc13b,
title = "Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism",
abstract = "Several philosophical issues in connection with computer simulations rely on the assumption that results of simulations are trustworthy. Examples of these include the debate on the experimental role of computer simulations (Parker in Synthese 169(3):483–496, 2009; Morrison in Philos Stud 143(1):33–57, 2009), the nature of computer data (Barberousse and Vorms, in: Dur{\'a}n, Arnold (eds) Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013; Humphreys, in: Dur{\'a}n, Arnold (eds) Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013), and the explanatory power of computer simulations (Krohs in Int Stud Philos Sci 22(3):277–292, 2008; Dur{\'a}n in Int Stud Philos Sci 31(1):27–45, 2017). The aim of this article is to show that these authors are right in assuming that results of computer simulations are to be trusted when computer simulations are reliable processes. After a short reconstruction of the problem of epistemic opacity, the article elaborates extensively on computational reliabilism, a specified form of process reliabilism with computer simulations located at the center. The article ends with a discussion of four sources for computational reliabilism, namely, verification and validation, robustness analysis for computer simulations, a history of (un)successful implementations, and the role of expert knowledge in simulations.",
keywords = "Computer simulations, Reliabilism, Epistemic opacity, Verification and validation, Robustness analysis, History of success, Expert knowledge",
author = "Duran, {Juan Manuel} and N. Formanek",
year = "2018",
month = "10",
doi = "10.1007/s11023-018-9481-6",
language = "English",
journal = "Minds and Machines: journal for artificial intelligence, philosophy and cognitive sciences",
issn = "0924-6495",
publisher = "Springer Netherlands",

}

RIS

TY - JOUR

T1 - Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism

AU - Duran, Juan Manuel

AU - Formanek, N.

PY - 2018/10

Y1 - 2018/10

N2 - Several philosophical issues in connection with computer simulations rely on the assumption that results of simulations are trustworthy. Examples of these include the debate on the experimental role of computer simulations (Parker in Synthese 169(3):483–496, 2009; Morrison in Philos Stud 143(1):33–57, 2009), the nature of computer data (Barberousse and Vorms, in: Durán, Arnold (eds) Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013; Humphreys, in: Durán, Arnold (eds) Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013), and the explanatory power of computer simulations (Krohs in Int Stud Philos Sci 22(3):277–292, 2008; Durán in Int Stud Philos Sci 31(1):27–45, 2017). The aim of this article is to show that these authors are right in assuming that results of computer simulations are to be trusted when computer simulations are reliable processes. After a short reconstruction of the problem of epistemic opacity, the article elaborates extensively on computational reliabilism, a specified form of process reliabilism with computer simulations located at the center. The article ends with a discussion of four sources for computational reliabilism, namely, verification and validation, robustness analysis for computer simulations, a history of (un)successful implementations, and the role of expert knowledge in simulations.

AB - Several philosophical issues in connection with computer simulations rely on the assumption that results of simulations are trustworthy. Examples of these include the debate on the experimental role of computer simulations (Parker in Synthese 169(3):483–496, 2009; Morrison in Philos Stud 143(1):33–57, 2009), the nature of computer data (Barberousse and Vorms, in: Durán, Arnold (eds) Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013; Humphreys, in: Durán, Arnold (eds) Computer simulations and the changing face of scientific experimentation, Cambridge Scholars Publishing, Barcelona, 2013), and the explanatory power of computer simulations (Krohs in Int Stud Philos Sci 22(3):277–292, 2008; Durán in Int Stud Philos Sci 31(1):27–45, 2017). The aim of this article is to show that these authors are right in assuming that results of computer simulations are to be trusted when computer simulations are reliable processes. After a short reconstruction of the problem of epistemic opacity, the article elaborates extensively on computational reliabilism, a specified form of process reliabilism with computer simulations located at the center. The article ends with a discussion of four sources for computational reliabilism, namely, verification and validation, robustness analysis for computer simulations, a history of (un)successful implementations, and the role of expert knowledge in simulations.

KW - Computer simulations

KW - Reliabilism

KW - Epistemic opacity

KW - Verification and validation

KW - Robustness analysis

KW - History of success

KW - Expert knowledge

U2 - 10.1007/s11023-018-9481-6

DO - 10.1007/s11023-018-9481-6

M3 - Article

JO - Minds and Machines: journal for artificial intelligence, philosophy and cognitive sciences

T2 - Minds and Machines: journal for artificial intelligence, philosophy and cognitive sciences

JF - Minds and Machines: journal for artificial intelligence, philosophy and cognitive sciences

SN - 0924-6495

ER -

ID: 47222108