Artificial intelligence (AI) is arguably the new spectre of digital cultures. By filtering information out of existing data, it determines the way we see the world and how the world sees us. Yet the vision algorithms have of our future is built on our past. What we teach these algorithms ultimately reflects back on us and it is therefore no surprise when artificial intelligence starts to classify on the basis of race, class and gender. By imposing identity on input data, in order to filter, that is to discriminate signals from noise, machine learning algorithms invoke a ghost story that works at two levels. First, it proposes that there is a reality that is not this one, and that is beyond our reach; to consider this reality can be unnerving. Second, the ghost story is about the horror of the past – its ambitions, materiality and promises – returning compulsively and taking on a present form because of something that went terribly wrong in the passage between one conception of reality and the next.

Spheres Editorial Collective; Maya Indira Ganesh; Stina Lohmüller:

Contents

#5 Spectres of AI

How a Machine Learns and Fails

Artificial Intelligibility and Proxy Error

Technologies of Power - From Area Studies to Data Science

An Agenda for Decolonizing Data Science

AI and the Imagination to Overcome Difference

The Difference that Difference Makes

Restorative Justice in Artificial Intelligence Crimes

The Electric Kool-Aid Turing Test

Micropolitics of a Recommender System – Source Code

Micropolitics of a Recommender System – Machine Learning and the Machinic Unconscious

The Disruptions of Neutral Machine Translation

Galton's Utopia

"Das hätte nicht passieren dürfen"

Automating Creativity

Documentary: Automating Creativity

Insectile Indices

Article: An Agenda for Decolonizing Data Science

Published in:

Keywords

Article:
An Agenda for Decolonizing Data Science