Designing for Difference: How We Learn to Stop Worrying and Love the Doppelganger
John S. Seberger, Sanonda Datta Gupta
Abstract
To use social media is to interact with digital representations of oneself in the form of algorithmically-determined personalized content. Yet when we assume that interactions with personalized content will be a persistent feature of our futures, the concepts available to frame such digital representations – things variously called doubles, twins, and doppelgangers – appear as worryingly creepy. Where might one find optimism amid such presumptive creepiness? Through conceptual analysis of data doubles, digital twins, and data doppelgangers, we identify and explain one source of justifiable optimism. Unlike the double and twin, the data doppelganger’s dynamics center difference rather than presumed sameness. Fostering justifiable optimism about the futures of personalization – with social media as a starting point – requires learning how to design for the experience of difference represented by the doppelganger: the irreducibility of the person to the represented user.
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