IMAGO is a conceptual listening device created by Central Saint Martins designers Domenico Di Paolo and Kieran Feechan. Designed for domestic environments, the project encourages active engagement with music through physical interaction and focused listening.
The device operates using locally processed AI models trained with artist participation and consent, presenting an alternative approach to music technologies that rely on large-scale datasets gathered from online sources. The project examines how artificial intelligence can be integrated into creative experiences while maintaining direct involvement from the artists whose work informs the system.
Local processing forms a key part of the concept, allowing the device to function without relying on cloud-based data collection. The designers developed IMAGO as both a listening tool and a platform for exploring questions surrounding authorship, consent, and AI-generated creativity.
Image Credit: Domenico Di Paolo, Kieran Feechan
Key Themes Behind This Trend
- Consent-based AI Creativity
- Artist-approved training models present new possibilities for creative AI systems that preserve authorship, licensing control, and cultural value within generated media experiences.
- Localized Music Intelligence
- On-device processing enables private, cloud-independent listening products that reduce data extraction while offering personalized and context-aware audio interactions.
- Tactile Listening Interfaces
- Physical controls and intentional interaction formats reframe music playback as an immersive domestic ritual rather than a passive streaming behavior.
Where This Applies
- Consumer Electronics
- AI-enabled home audio devices can differentiate through privacy-first hardware, sensory design, and localized intelligence that challenges subscription-based smart speaker ecosystems.
- Music Technology
- Rights-conscious playback platforms create space for artist-partnered tools where consent, provenance, and creative participation become core product features.
- Artificial Intelligence
- Small-scale models trained with direct creator involvement signal a shift toward accountable AI systems designed around transparency, ownership, and edge-based deployment.
