Welcome to BIAS ONLINE: a virtual exhibition space by Science Gallery at Trinity College Dublin showcasing digital artworks exploring data equity, privacy, surveillance culture, facial recognition, class and artificial intelligence.

From cognitive function to machine learning, bias is a shortcut, for our brain or for data.

This virtual exhibition is part of Science Gallery Dublin’s year-long BIAS season, interrogating how bias moves from human to machine and how persuasion, preference, motivation and misinformation contribute to our individual, societal and digital biases.

BIAS ONLINE was developed with the support of the European ARTificial Intelligence Lab, co-funded by the Creative Europe Programme of the European Union, and was created with the support of The Department of Tourism, Culture, Arts, Gaeltacht, Sport and Media.

Featured

STEALING UR FEELINGS

Can the internet read you? This exhibit by Noah Levenson knows you better than you know yourself. STEALING UR FEELINGS is an interactive film that learns your deepest, darkest secrets - just by looking at your face. That's the good news. The bad news? Your favourite apps are doing exactly the same thing.

Click here to explore it.

Dark Matters

What does bias sound like? Dark Matters by Johann Diedrick exposes the absence of Black speech in the datasets used to train voice interface systems in consumer AI products like Alexa and Siri. This is a digital-first experience that puts you in the position of a machine learning researcher exploring the absence of Black voices in the datasets.

Click here to explore it.

CLASSES

How are invisible biases translated into code? CLASSES by Libby Heaney is a video essay exploring the entanglements between machine learning classification and social class(ification). The exhibit takes place in a simulated model of a London council estate, where the artist lives.

Click here to explore it.

NORMALIZI.NG

What does normal look like? This exhibit by Mushon Zer-Aviv aims to analyze and understand how we decide who looks more “normal”. By contributing to the dataset and choosing between faces you deem more normal, the machine analyzes your decisions and will add you to its algorithmic map of normality.

Click here to explore it.