Objective Portrait

We let a subjective algorithm give intepretations of a portrait of objects.

As makers, we are often fascinated by particular objects without really knowing why. This project explores whether a differently trained object recognition algorithm can help to understand such relations.

Usually, these algorithms are used to very accurately recognise whether something is a chair or a plant, for instance. But something interesting happens when the algorithm makes a ‘wrong’ guess. When it sees a plant in a chair, this guess is still based on something: namely, on how the algorithm is coded and trained. Instead of trying to erase such biases, we take this reflection of its maker as a starting point.

If we explicitly train an algorithm on someone’s personal values, can it capture something of their particular way of seeing? While an object recognition algorithm usually tries to learn the definition of an object, we explore the potential for a subject recognition algorithm: can an AI learn to see what objects mean to someone?

An object portrait?

To test this, we let such a subjective algorithm interpret the things that a designer made and collected over time. These objects embody their fascinations, fears, desires, even when their maker doesn’t always know what they are.

First we tried to capture these elusive features visually, by making an ‘object portrait’ of a maker: a still life of their objects. We wonder what such a composition could say about someone. But above all, could someone’s subjective algorithm help reveal other meanings?

Take notice! Objective Portrait will be presented at the first floor of Theater de Veste. This location is only accessible by stairs. This location is therefore not accessible to people with limited mobility.

Can an algorithm be a mirror for a maker, a kind of personal curator?