Re.Dis.Cover Place with Generative AI: Exploring the Experience and Design of City Wandering with Image-to-Image AI

TL;DR

This study explores how image-to-image AI can enhance urban exploration by supporting playful interactions, reimaginations, and rediscoveries of cityscapes, providing initial empirical insights and design considerations for future HCI applications.

Contribution

It offers novel empirical insights into the use of generative AI for urban exploration and proposes design considerations for creating playful city experiences with AI technology.

Findings

AIGT supports playfulness and reimaginations of urban spaces.

Familiarity with places influences AI interaction experiences.

AIGT can act as a 'tourist' metaphor for engaging exploration.

Abstract

The HCI field has demonstrated a growing interest in leveraging emerging technologies to enrich urban experiences. However, insufficient studies investigate the experience and design space of AI image technology (AIGT) applications for playful urban interaction, despite its widespread adoption. To explore this gap, we conducted an exploratory study involving four participants who wandered and photographed within Eindhoven Centre and interacted with an image-to-image AI. Preliminary findings present their observations, the effect of their familiarity with places, and how AIGT becomes an explorer's tool or co-speculator. We then highlight AIGT's capability of supporting playfulness, reimaginations, and rediscoveries of places through defamiliarizing and familiarizing cityscapes. Additionally, we propose the metaphor AIGT as a 'tourist' to discuss its opportunities for engaging explorations and risks of stereotyping places. Collectively, our research provides initial empirical insights and design considerations, inspiring future HCI endeavors for creating urban play with generative AI.