Micro-narratives: A Scalable Method for Eliciting Stories of People's Lived Experience
Amira Skeggs, Ashish Mehta, Valerie Yap, Seray B. Ibrahim, Charla Rhodes, James J. Gross, Sean A. Munson, Predrag Klasnja, Amy C. Orben, Petr Slovák
Abstract
Engaging with people's lived experiences is foundational for HCI research and design. This paper introduces a novel narrative elicitation method to empower people to easily articulate 'micro-narratives' emerging from their lived experiences, irrespective of their writing ability or background. Our approach aims to enable at-scale collection of rich, co-created datasets that highlight target populations' voices with minimal participant burden, while precisely addressing specific research questions. To pilot this idea, and test its feasibility, we: (i) developed an AI-powered prototype, which leverages LLM-chaining to scaffold the cognitive steps necessary for users' narrative articulation; (ii) deployed it in three mixed-methods studies involving over 380 users; and (iii) consulted with established academics as well as C-level staff at (inter)national non-profits to map out potential applications. Both qualitative and quantitative findings show the acceptability and promise of the micro-narrative method, while also identifying the ethical and safeguarding considerations necessary for any at-scale deployments.
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