Ideas for machine learning from psychology's reproducibility crisis

Samuel J Bell (University of Cambridge); Onno P Kampman (University of Cambridge)

In the early 2010s, a crisis of reproducibility rocked the field of psychology.

Following a period of reflection, psychology has responded with radical reform of its scientific practices. More recently, similar questions about the reproducibility of machine learning research have also come to the fore. In this short paper, we bring a novel perspective to this discussion.We present select ideas from the discipline of psychology, translating them into relevance for a machine learning audience. Whether we seek to build machine learning systems or to understand them, we can all learn from psychology's experience.