Despite many years of research, there has been surprisingly little progress in our understanding of how faces are identified. Here I argue that there are two contributory factors: (a) Our methods have obscured a critical aspect of the problem, within-person variability; and (b) research has tended to conflate familiar and unfamiliar face processing. Examples of procedures for studying variability are given, and a case is made for studying real faces, of the type people recognize every day. I argue that face recognition (specifically identification) may only be understood by adopting new techniques that acknowledge statistical patterns in the visual environment. As a consequence, some of our current methods will need to be abandoned.
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