The aim or goal of science has long been discussed by both philosophers of science and scientists themselves. In The Scientific Image (van Fraassen 1980), the aim of science is famously employed to characterize scientific realism and a version of anti-realism, called constructive empiricism. Since the publication of The Scientific Image, however, various changes have occurred in scientific practice. The increasing use of machine learning technology, especially deep learning (DL), is probably one of the major changes in the last decade. This paper aims to explore the implications of DL-aided research for the aim of science debate. I argue that, while the emerging DL-aided research is unlikely to change the state of classic opposition between constructive empiricism and scientific realism, it could offer interesting cases regarding the opposition between those who espouse truth as the aim of science and those oriented to understanding (of the kind that sacrifices truth).
