In a new paper in the Journal of Experimental & Theoretical Artificial Intelligence, Chris Drummond takes aim at the 'reproducibility movement' which has lately risen to prominence in science. As one of the early advocates for this movement, I was interested to see what Drummond had to say. While I don't find his argument wholly convincing, he does raise some good points.
Drummond begins by summarizing the case for reproducible research as it sees it. The claim is that reproducibility - the ability of other scientists to exactly reproduce and confirm a given result - is central to science. It is further claimed that we can promote reproducibility by requiring authors to submit their data, and their analysis scripts (code), with each publication and that this will, amongst other benefits, help to prevent scientific fraud. Against this, Drummond says that
(1) Reproducibility, at least in the form proposed, is not ...
