All At Once

This spatial installation explores a digital museum collection as a whole using machine learning, print and augmented reality.

First installed at Williams College Museum of Art, “All At Once” invites an algorithmic, data-driven dive into their digital museum collection. It presents the collection as a whole, seen from a new perspective, and allows new adjacencies and connections to come to the fore. The project entices important questions around the curation, history and politics, and equality and bias of museum collections.
The walls of a room are filled with images of the entire museum collection aligned in a grid. Viewers can explore the entire collection simply by walking past the printed walls. The images are not organized alphabetically, chronologically or by department, but instead their position is determined using a machine learning algorithm that goes by visual similarity alone.

A second layer of information is available through an Augmented Reality app on an ipad. Viewers can scan individual images and find related images within the grid, using attributes such as artist, year of creation or medium.

All At Once: Sequence explores this algorithmic juxtaposition in one dimension, instead of two. In this video installation, images from WCMA’s collection are ordered by visual similarity—an algorithm “sees” a strong connection between one image and the next—and presented as a fast-flowing stream through time. Over the course of 10 minutes, visual trends and particularities come and go as the collection is seen in a new way.

This is a self-initiated TheGreenEyl project supported by New Inc and the Knight Foundation.