Algorithmic Instructions for Analogue Circuits

Wednesday, March 4th, 13h00-15h00 EST @ 4th Space - Concordia University

Learning Machines: Algorithmic Instructions for Analogue Circuits is a live, public experiment in machinic pedagogies, where transparency shifts from promises of clarity and control toward a limit point where instruction breaks down and learning amps up! 

Using old-school learning machines—think: overhead projectors, photocopiers, cassette players—we will build a visible circuit that runs on clear prompts, transparent instructions, and see-through processes. Drawing on traditions of instructional art, the collaborative installation aims to explore algorithmic thinking, artificial intimacies, pedagogical power, perceptual circuits, and the radical difference that exists at the heart of intelligence. Visitors both in person and online will be invited to help build our emergent learning machine, following algorithmic instructions (or refusing them!), making things (or unmaking them!), adjusting conditions (or disrupting them!), and interfering with the system as it runs in real time. What accumulates on walls, tables, screens, and surfaces will be streamed live, distributing (and distorting) this algorithmic thought in the making.

The Learning Machines team is led by Dr. jessie beier and includes Sarah Belanger-Martel, Jihane Mossalim, Nata Pavlik, Aaron Ansuini, Elizabeth Dovolis, Catlin W. Kuzyk, Patrick Lostracco, Reza Sedighian, and Jana Wodicka.