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The hidden infrastructure behind AI that creatives rarely see

The hidden infrastructure behind AI that creatives rarely see

Published 2 days, 1 hour ago
Description

The other night I went to hear journalist Karen Hao speak about her book Empire of AI: Dreams and Nightmares in Sam Altman’s OpenAI, presented by the Schwartz Reisman Institute for Technology and Society, at the University of Toronto.

I started reading the book after interviewing Ian Krietzberg, AI correspondent at Puck News, who strongly recommended it.

Hao’s reporting examines the power structures shaping the AI industry, who builds these systems, who profits from them, and the often unseen infrastructure behind them.

As a creative, what will likely stay with you as it did with me, is the hidden labour behind AI: the data labeling, training datasets, and the massive amount of human labour required to prepare the data that models learn from. Alongside this are the ongoing copyright debates around the material used to train these systems.

These are parts of the AI ecosystem that most creatives rarely encounter directly, even though they shape the tools we’re increasingly using in our work, and the more we use them, the more rooted these systems become.

You may not arrive at all the same conclusions Hao does, but investigative perspectives like this add vital context to the broader conversation about AI and creativity. I believe these are conversations we as creatives need to be having so that together, we can work to shape them.

At THE GRAIN, I’m interested in bringing many different viewpoints into that conversation, from builders, to artists, to critics and researchers, because the story of AI is about us, and the systems we increasingly use.

I’d be curious to hear from creatives working with AI tools:

What part of this ecosystem do you think we should be paying more attention to right now, the technology itself, or the infrastructure behind it?



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