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

2026-02-02

AI Summary

This work addresses the highly subjective and inherently non-shareable nature of olfactory experiences, which hinders intersubjective perceptual communication. To overcome this limitation, the study reimagines the traditional Japanese “Genji-ko” incense game as a collaborative human–AI olfactory interaction system that integrates an odor sensor, a large language model (LLM), a mobile application, and a dialogic interface—marking the first integration of LLMs with olfactory perception. Users compare scents to generate Genji patterns and engage in reflective dialogue with an empathetic AI companion to explore similarities and differences in their sensory interpretations. By doing so, the system extends the sensory dimensions of human–computer interaction and demonstrates a novel paradigm in which AI serves as an empathetic partner to facilitate shared sensory experiences and cross-subjective perceptual exchange.

Technology Category

• Humans and AI: Interaction Techniques and Devices
• Cognitive Modeling & Cognitive Systems: Social Cognition And Interaction
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions
• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Social Networks and Social Media: Generative AI / large language models and their impact on social systems

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.

Problem

• olfaction
• human perception
• subjectivity
• sensory interaction
• AI-mediated experience

Innovation

• olfactory interaction
• AI-mediated sensing
• human-AI collaboration
• LLM-powered co-smelling
• sensory reflection