Models, Parameterization, and Software: Epistemic Opacity in Computational Chemistry

Computational chemistry grew in a new era of “desktop modeling,” which coincided with a growing demand for modeling software, especially from the pharmaceutical industry. Parameterization of models in computational chemistry is an arduous enterprise, and we argue that this activity leads, in this specific context, to tensions among scientists regarding the epistemic opacity transparency of parameterized methods and the software implementing them. We relate one flame war from the Computational Chemistry mailing List in order to assess in detail the relationships between modeling methods, parameterization, software and the various forms of their enclosure or disclosure. Our claim is that parameterization issues are an important and often neglected source of epistemic opacity and that this opacity is entangled in methods and software alike. Models and software must be addressed together to understand the epistemological tensions at stake.

[1]  Alejandro Pisanty,et al.  “We were here before the Web and hype…”: a brief history of and tribute to the Computational Chemistry List , 2018, Journal of Cheminformatics.

[2]  Juan M. Durán,et al.  Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism , 2018, Minds and Machines.

[3]  R. B. Hermann,et al.  The Development of Computational Chemistry in the United States , 2007 .

[4]  Joseph A. November Early Biomedical Computing and the Roots of Evidence-Based Medicine , 2011, IEEE Annals of the History of Computing.

[5]  Grant Fisher,et al.  Diagnostics in computational organic chemistry , 2016, Foundations of Chemistry.

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

[7]  Jon Agar,et al.  What Difference Did Computers Make? , 2006 .

[8]  Nancy Beadie,et al.  Creating the market university: how academic science became an economic engine , 2013 .

[9]  Frédéric Wieber,et al.  Multiple Means of Determination and Multiple Constraints of Construction: Robustness and Strategies for Modeling Macromolecular Objects , 2012 .

[10]  Ana Simões,et al.  Neither Physics nor Chemistry: A History of Quantum Chemistry , 2011 .

[11]  É. Francoeur Molecular models and the articulation of structural constraints in chemistry , 2001 .

[12]  Eric Winsberg Philosophy and Climate Science , 2018 .

[13]  Buhm Soon B. S. Park,et al.  The 'Hyperbola of Quantum Chemistry': the Changing Practice and Identity of a Scientific Discipline in the Early Years of Electronic Digital Computers, 1945-65 , 2003 .

[14]  Frédéric Wieber,et al.  “Only the Initiates Will Have the Secrets Revealed”: Computational Chemists and the Openness of Scientific Software , 2017, IEEE Annals of the History of Computing.

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

[16]  B. Park Between Accuracy and Manageability: Computational Imperatives in Quantum Chemistry , 2009 .

[17]  Peter A. Chow-White,et al.  Bidirectional Shaping and Spaces of Convergence , 2012 .

[18]  Frédéric Wieber,et al.  Mailing list archives as useful primary sources for historians: looking for flame wars , 2018 .

[19]  V. Seifert Essays in the Philosophy of Chemistry , 2016 .

[20]  Matt Spencer,et al.  Brittleness and Bureaucracy: Software as a Material for Science , 2015, Perspectives on Science.

[21]  Donald F. Hornig,et al.  Molecular Vibrations. The Theory of Infrared and Raman Vibrational Spectra. , 1956 .

[22]  E. Berman,et al.  Creating the Market University: How Academic Science Became an Economic Engine , 2011 .

[23]  Ann Johnson,et al.  Modeling Molecules: Computational Nanotechnology as a Knowledge Community , 2009, Perspectives on Science.

[24]  Allen B Richon Current status and future direction of the molecular modeling industry. , 2008, Drug discovery today.

[25]  Richard W. Counts,et al.  Strategies I , 1987, J. Comput. Aided Mol. Des..

[26]  Michael S. Mahoney,et al.  What Makes the History of Software Hard , 2008, IEEE Annals of the History of Computing.

[27]  Evan Hepler-Smith Paper Chemistry: François Dagognet and the Chemical Graph , 2018, Ambix.

[28]  Johannes Lenhard,et al.  Disciplines, models, and computers: the path to computational quantum chemistry. , 2014, Studies in history and philosophy of science.