Not Everybody Thinks the Emphasis on Reproducibility is a Good Thing

[From the article “Reproducible research: a minority opinion” by Chris Drummond, published in the Journal of Experimental & Theoretical Artificial Intelligence.]
“Reproducible research, a growing movement within many scientific fields, including machine learning, would require the code, used to generate the experimental results, be published along with any paper. …This viewpoint is becoming ubiquitous but here I offer a differing opinion. I argue that far from being central to science, what is being promulgated is a narrow interpretation of how science works. I contend that the consequences are somewhat overstated. I would also contend that the effort necessary to meet the movement’s aims, and the general attitude it engenders would not serve well any of the research disciplines, including our own.”
“Let me sketch my response here:
– Reproducibility, at least in the form proposed, is not now, nor has it ever been, an essential part of science.
– The idea of a single well-defined scientific method resulting in an incremental, and cumulative, scientific process is, at the very best, moot.
– Requiring the submission of data and code will encourage a level of distrust among researchers and promote the acceptance of papers based on narrow technical criteria.
– Misconduct has always been part of science with surprisingly little consequence. The public’s distrust is likely more to with the apparent variability of scientific conclusions.”
To read more, click here (but note the full article is behind a paywall).

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