Memory Printer: Exploring Everyday Reminiscing by Combining Slow Design with Generative AI-based Image Creation
This work addresses the challenge of improving human-AI interaction in emotionally sensitive contexts like reminiscing, though it is incremental in combining existing design and AI methods.
The paper tackled the problem of disengaging interactions in generative AI tools for memory reconstruction by introducing Memory Printer, a tangible design combining silk-screen printing with text-to-image generation, and found in a study with 24 participants that it enhanced user control and memory evocation but raised risks like false memory formation.
Generative Artificial Intelligence (GAI) offers new opportunities for reconstructing these unrecorded memory scenes, yet existing web-based tools undermine users' sense of agency through disengaging and unpredictable interactions. In this work, we advance three design arguments about how slow, tangible interaction can reshape human-AI relationships by making temporality, embodied agency, and generative processes experientially legible. We instantiate these arguments by presenting Memory Printer, a tangible design that combines silk-screen printing metaphors with text-to-image generation. The design features layered reconstruction that decomposes image generation into incremental steps, a physical wooden scraper enabling embodied control over image revelation, and built-in printing that produces tangible photos. We examine these arguments through a comparative study with 24 participants, exploring how participants engage with, interpret, and respond to this interaction stance. The study surfaces both opportunities -- such as vivid memory evocation, heightened sense of control, and creative exploration -- and critical tensions, including risks of false memory formation, algorithmic bias, and data privacy. Together, these findings articulate important boundaries for deploying generative AI in emotionally sensitive contexts.