Underutilized & The Hypothetical Image (Salvaggio)
Eryk Salvaggio, Cybernetic Forests
I would not compare the current regime of statistics to the destruction wrought by slavery. I only want to acknowledge that the origins and ideologies derived from that place — of distance from the real-world effects of abstraction. Generative AI owes more to this history of data analytics than to any history of AI. It is less about figuring out autonomous systems and more about automated pattern analysis.
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Without the massive expansion of data, generative AI tools could not exist. The rebranding of data analytics to AI severs a historical narrative and perspective about where AI actually comes from, distorting the way we make sense of it and our perception of its risks.
But meanwhile, San Francisco in the 2010s, scores of consultants made careers advising on data monetization and tapping the power of underutilized digital assets. This data wasn’t useful on its own, it had to be activated. The reanimation of this data was achieved through predictive analytics. The idea was simple: gather enough data, from our credit card purchases and grocery store cards, and companies would find useful patterns in that data. They’d use those patterns to figure out when to push sales, send us an email, or show us an ad on Instagram.
The social media model was simple: people provided content for free, and companies sold the ads. Writers were reduced to content, and reactions to that content created data that helped social media further analyze, predict, and target its users. At the heart of this practice was the view that writers and artists could be reduced to signals. The real value was mining people’s response to those signals. Today, companies are aiming to remove artists and writers from the loop entirely — it turns out, even free labor was too expensive.
The great disintermediaries became a new intermediary. It wasn’t a people’s revolution, it was a coup.
Cory Doctorow : "Remember when we said the internet would disintermediate everything? It did. And then it reintermediated everything."
En évoquant les monte-plats de Monticello, la plantation de Thomas Jefferson :
Technology has long been designed at the expense of those whose living is earned through service for the benefit of those who pay to be served. The interface is a tool of obscuring human labor behind screens.
I don’t believe that the internet connected us to each other. I find it has isolated us from physical proximities to ideological ones. Now AI promises to further constrain those relationships, to move us from a time when one could speak and hear from many to a time when one can speak only to ourselves: one-to-none communication, a throwback to the days of yelling at the TV, but now the TV can adjust.
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I see this as the true existential risk of AI. Not the machines, which simply hum math into pixels. I am convinced that those who build the technology of generative AI will aim to replace, not empower, the communities and interactions we find ourselves valuing most today.
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None of the training data is being destroyed. But I would argue that they are nonetheless being desecrated. It’s an empty ritual of erasure. Every AI image is built on images that came before, but those originals are completely severed of any connection to meaning.
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In that way, Diffusion is dis-integration. The meaning of historical images is derived not purely from what is depicted, but from what is understood by the viewer. Disconnect images from their social meaning — treat them solely as data, rather than cultural artifacts, as tools for remembrance — and you erase their significance.
Diffusion models aestheticize what data analytics has always done. It alienates a sliver of the world, abstracts it through measurement, and predicts corollaries. It turns a photo into a representation of what it represents, rather than a reference to the slice of time depicted.
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