  Visual illusions allow researchers to devise and test new models of visual
perception. Here we show that artificial neural networks trained for basic
visual tasks in natural images are deceived by brightness and color illusions,
having a response that is qualitatively very similar to the human achromatic
and chromatic contrast sensitivity functions, and consistent with natural image
statistics. We also show that, while these artificial networks are deceived by
illusions, their response might be significantly different to that of humans.
Our results suggest that low-level illusions appear in any system that has to
perform basic visual tasks in natural environments, in line with error
minimization explanations of visual function, and they also imply a word of
caution on using artificial networks to study human vision, as previously
suggested in other contexts in the vision science literature.
