There is strong evidence that face processing is localized in the brain. The double dissociation between prosopagnosia, a face recognition deficit occurring after brain damage, and visual object agnosia, difficulty recognizing otber kinds of complex objects, indicates tbat face and non(cid:173) face object recognition may be served by partially independent mecha(cid:173) nisms in the brain. Is neural specialization innate or learned? We sug(cid:173) gest that this specialization could be tbe result of a competitive learn(cid:173) ing mechanism that, during development, devotes neural resources to the tasks they are best at performing. Furtber, we suggest that the specializa(cid:173) tion arises as an interaction between task requirements and developmen(cid:173) tal constraints. In this paper, we present a feed-forward computational model of visual processing, in which two modules compete to classify input stimuli. When one module receives low spatial frequency infor(cid:173) mation and the other receives high spatial frequency information, and the task is to identify the faces while simply classifying the objects, the low frequency network shows a strong specialization for faces. No otber combination of tasks and inputs shows this strong specialization. We take these results as support for the idea that an innately-specified face processing module is unnecessary.