How do the ways in which we learn influence our cognitive representations of what we learn? We show that in language learning tasks, the process of learning to conceptualize and categorize perceptual input shapes how that input gets represented in mind. In representation, there seems to be a give and take between veridicality and completeness, on the one hand, and discrimination and accurate categorization, on the other. Learning to better discriminate objects into categories based on their highly-discriminating features makes people less likely to notice or remember the same objects' less-discriminating features. Gains in response-discrimination between categories thus come at a cost to within category discrimination. We suggest that the mechanisms of human learning obey a simple principle: there can be no representation without taxation.