AI-driven experiment exploring new ways to exhibit and experience physical art in the digital space.
The coronavirus pandemic forced the closure of the world’s art galleries leaving many seeking ways to publish their works online to an audience trapped indoors.
One of the galleries leading this push was the Louvre which created a dedicated collections website featuring over 480,000 items – many of which had been hidden away in storage for years. Ironically the restrictions of the pandemic had opened up more of the Louvre than had ever been possible to see before.
We’re fascinated with how large datasets can be combined with technology to create new ways of seeing and experiencing the world. Naturally this huge repository caught our attention. Seeing all of this artwork online was fantastic, but as a team who care deeply about user experience we felt the website was a missed opportunity. From our perspective the academic tone seemed misaligned with modern users and their increasing expectation of joyful digital experiences.
This led us to two questions:
- How might we engage the audience in new ways, encouraging exploration through playful design and novel interactions?
- How might we use machine learning to uncover patterns in the collection, using data to show trends and transformations happening across generations of artists?
Framework is our response to these questions – a series of experiments aiming to show the Louvre’s collection in a new light, untethered to the reality of the physical gallery.