Smell with Genji: Rediscovering Human Perception through an Olfactory Game with AI

TL;DR

This paper introduces Smell with Genji, an AI-enhanced olfactory game that enables shared human-AI perception of scents, fostering reflection and new sensory interaction possibilities.

Contribution

It presents a novel AI-mediated olfactory system that reinterprets the traditional Genji-ko game as a collaborative sensory experience with dialogue and scent comparison.

Findings

AI can participate in olfactory perception alongside humans.

The system facilitates reflection on sensory differences and similarities.

It opens new avenues for AI-supported sensory and HCI interactions.

Abstract

Olfaction plays an important role in human perception, yet its subjective and ephemeral nature makes it difficult to articulate, compare, and share across individuals. Traditional practices like the Japanese incense game Genji-ko offer one way to structure olfactory experience through shared interpretation. In this work, we present Smell with Genji, an AI-mediated olfactory interaction system that reinterprets Genji-ko as a collaborative human-AI sensory experience. By integrating a game setup, a mobile application, and an LLM-powered co-smelling partner equipped with olfactory sensing and LLM-based conversation, the system invites participants to compare scents and construct Genji-mon patterns, fostering reflection through a dialogue that highlights the alignment and discrepancies between human and machine perception. This work illustrates how sensing-enabled AI can participate in olfactory experience alongside users, pointing toward new possibilities for AI-supported sensory interaction and reflection in HCI.