Abstract This offers a design framework to guide more effective and ethical design of AI systems that model human likeness. Drawing on ethnographic research with StoryFile, a company pioneering conversational video AI, it traces how the promise of “authentic interactions” and lasting legacies emerge through the assemblage of human storytelling, performance, design choices, technical affordances, corporate narratives, and cultural values. For practitioners and organizations building similar products, this paper offers the myth/mess framework as a design tool: to locate where corporate narratives meet messy realities, to surface how values are embedded or eroded, and to guide the development of AI systems, such as grief tech or heritage projects, that model human likeness and mediate embodied practices through which we form identity, memory, and relationships. Using anthropologists Paul Dourish and Genevieve Bell's myth/mess framework, the paper analyzes two key tensions that illuminate the distributed, relational nature of ‘intelligence’ in such systems.
Helen Robertson (Sat,) studied this question.
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