Technology for applying explainable artificial training algorithms (XAI) to training machine learning algorithms for identifying potentially developing computer vision syndrome (CVS), CVS and/or recommended remedial action(s) that a user can perform to counter potentially developing CVS and/or existing CVS. In some embodiments, the XAI includes a Contrastive Explainability model. In some embodiments, the training performed by the XAI includes assigning weight factors respectively to CVS input parameters (for example, blink rate) based upon how strong the respective CVS input factor is correlated with development of CVS in the user.