Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism

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.

[1]  Ian Hacking,et al.  On the Stability of the Laboratory Sciences , 1988 .

[2]  Michael Weisberg,et al.  Biology and Philosophy symposium on Simulation and Similarity: Using Models to Understand the World , 2013 .

[3]  Julian Newman,et al.  Epistemic Opacity, Confirmation Holism and Technical Debt: Computer Simulation in the Light of Empirical Software Engineering , 2015, HaPoC.

[4]  Paul Humphreys,et al.  The philosophical novelty of computer simulation methods , 2009, Synthese.

[5]  Ulrich Krohs,et al.  How Digital Computer Simulations Explain Real‐World Processes , 2008 .

[6]  Margaret Morrison,et al.  Reconstructing Reality: Models, Mathematics, and Simulations , 2015 .

[7]  Mary S. Morgan,et al.  Experiments without material intervention: Model experiments, virtual experiments and virtually experiments , 2000 .

[8]  Eric Winsberg,et al.  Simulated Experiments: Methodology for a Virtual World , 2003, Philosophy of Science.

[9]  R. Persaud Philosophy of science , 1992, The Lancet.

[10]  Michael M. Resch,et al.  Mathematische Opazität. Über Rechtfertigung und Reproduzierbarkeit in der Computersimulation , 2018 .

[11]  S. Freytag Image And Logic A Material Culture Of Microphysics , 2016 .

[12]  Wendy S. Parker,et al.  Does matter really matter? Computer simulations, experiments, and materiality , 2009, Synthese.

[13]  Eric Winsberg,et al.  Science in the Age of Computer Simulation , 2010 .

[14]  Eric Winsberg,et al.  Holism, entrenchment, and the future of climate model pluralism , 2010 .

[15]  J. Edwards,et al.  Rethinking Expertise , 2008 .

[16]  Paul Humphreys,et al.  Computational Science and Its Effects , 2019, Philosophical Papers.

[17]  Claus Beisbart,et al.  Are computer simulations experiments? And if not, how are they related to each other? , 2017, European Journal for Philosophy of Science.

[18]  Roman Frigg,et al.  The philosophy of simulation: hot new issues or same old stew? , 2009, Synthese.

[19]  Hilary Kornblith,et al.  Justification and Knowledge , 1979 .

[20]  T. Trucano,et al.  Verification, Validation, and Predictive Capability in Computational Engineering and Physics , 2004 .

[21]  R. Levins The strategy of model building in population biology , 1966 .

[22]  W. Bhimji,et al.  Computer simulations and experiments: The case of the Higgs boson , 2015 .

[23]  Paul Humphreys,et al.  Extending Ourselves: Computational Science, Empiricism, and Scientific Method , 2004 .

[24]  Timothy G. Trucano,et al.  Verification and validation benchmarks , 2008 .

[25]  Timothy R. Colburn,et al.  Abstraction in Computer Science , 2007, Minds and Machines.

[26]  Juan Manuel Durán,et al.  Explaining simulated phenomena : a defense of the epistemic power of computer simulations , 2014 .

[27]  Alessandro Vespignani,et al.  Multiscale mobility networks and the spatial spreading of infectious diseases , 2009, Proceedings of the National Academy of Sciences.

[28]  Timothy G. Trucano,et al.  Verification and Validation in Computational Fluid Dynamics , 2002 .

[29]  Claus Beisbart,et al.  How can computer simulations produce new knowledge? , 2012 .

[30]  Margaret Morrison,et al.  Models, measurement and computer simulation: the changing face of experimentation , 2009 .

[31]  Mary S. Morgan,et al.  Experiments versus models: New phenomena, inference and surprise , 2005 .

[32]  Timothy G. Trucano,et al.  Verification and Validation in Computational Fluid Dynamics , 2002 .

[33]  Will Venters,et al.  Software engineering: theory and practice , 2006 .

[34]  Jack K. Horner,et al.  Software Intensive Science , 2014, Philosophy & Technology.

[35]  M. Detlefsen Hilbert's program , 1986 .

[36]  Yuan Guo-xing,et al.  Verification and Validation in Scientific Computing Code , 2010 .

[37]  Alvin I. Goldman,et al.  What is Justified Belief , 1979 .

[38]  Marion Vorms,et al.  Computer simulations and empirical data , 2013 .

[39]  Roman Frigg,et al.  The philosophy of simulation: hot new issues or same old stew? , 2008, Synthese.

[40]  Alessandro Vespignani,et al.  Comparing large-scale computational approaches to epidemic modeling: Agent-based versus structured metapopulation models , 2010, BMC infectious diseases.

[41]  Hans Hasse,et al.  Boon and Bane: On the Role of Adjustable Parameters in Simulation Models , 2017 .

[42]  Juan M. Durán,et al.  Varying the Explanatory Span: Scientific Explanation for Computer Simulations , 2017, ArXiv.

[43]  Michelle J. Alfa,et al.  Erratum to: EVOTECH® , 2010 .

[44]  Juan M. Durán Computer simulations in science and engineering - Concepts - Practices - Perspectives , 2019, ArXiv.

[45]  Thomas Tymoczko Computer Use to Computer Proof: A Rational Reconstruction , 1981 .