How to See like a Machine

Lately there have been a litany of alarming headlines declaiming the new ways AI is expediting, unnerving, or sometimes comically­ failing our near-future world. At the heart of these are debates about ownership and privacy, labor and exploitation, reality and fakery. And with the recent breakthroughs of AI image and text generators, the public discussion has entered the art world.

For the latest episode of our How to See series, we spoke with three artists who engage with the ways in which AI and machine learning algorithms are demanding new approaches to art making.

“I think we are at a crucial inflection point right now,” says Kate Crawford, professor, artist, and author of Atlas of AI. “I’ve been calling it the generative turn. It’s a moment where what we previously understood as how everything from illustration to film directing to publishing works is all about to change very rapidly.”

Trevor Paglen has been mining data sets that are used to train the machine-learning systems that surveil our daily lives. He investigates the dangerous oversimplification inherent in these processes, and the ethics of the intentions behind them. “Artists, what we bring to the party is thousands…of years of thinking about what the hell an image is,” he says. “The kind of engineering/computer science tradition does not have that. This is a place where artists are bringing voices to the conversation that I think are quite urgent.”