Cross-group recognition bias generalizes to diverse non-face representations of digital identity

We investigated the potential for cross-group recognition bias, the reliable tendency for perceivers to better recognize people who share their ethnic or social groups than people who do not share their ethnic or social groups, with diverse non-face representations of digital identity. We compared German participants' memory for people they believed to be German or French when those people were identified using non-face pictorial representations of identity (Studies 1 and 2) and verbal written representations of identity (Study 3) taken from the World Wide Web. Participants better recognized ingroup targets than outgroup targets regardless of type of identity representation. These results generalize cross-group recognition bias to an important new domain as well as to a new class of stimuli and suggest that process explanations of cross-group recognition bias that are domain specific to faces do not provide a comprehensive account of the bias.

► Cross-group recognition bias extends to non-face representations of digital identity.
► Two studies demonstrate this with pictorial representations of digital identity.
► Study 3 demonstrates this with written verbal representations of digital identity.
► We document a novel dynamic on the technological frontier of human communication.
► Current models of recognition bias need modification to account for this result.