Isabelle Levent

Academically, this is a collision of everything from computer science and art history to media studies to disruptive innovation to labor economics, and no one of these disciplines seems sufficient to cover the topic. 

For a computer to make a subtle combinational joke, never mind to assess its tastefulness, would require, first, a data-base with a richness comparable to ours, and, second, methods of link-making (and link-evaluating) comparable in subtlety with ours. 

Crawford elaborated in an interview. “When you have this enchanted determinism, you say, we can’t possibly understand this. And we can’t possibly regulate it when it’s clearly so unknown and such a black box,” she says. “And that’s a trap.”

As more artists gain access to AI and take up the tools, artists will have a whole new look — both how they look making art and how their art develops.

As part of this model where the ‘back-end’ gets more attention than the artefact, a systematic dismantling of the myth of ‘the artist’ as a stand-alone genius, standing above, or aside from the world, needs to be enacted.

New art-making technologies change art in consistent ways, and studying the past helps us understand how things will change in the future.