The Age of Noise - by Eryk Salvaggio - Cybernetic Forestshttps://cyberneticforests.substack.com/p/the-age-of-noiseThe information age has ended and we have entered the age of noise.
Noise is a slippery word. It means both the presence and absence of information. Today it's in the urbanisation of our world, the hum of traffic and jet engines. Noise is also where we go to escape noise. In August of 2023, Spotify announced that users had listened to 3 million hours of white noise recordings. Noise to sleep to, noise to drown out noise. Noise is also the mental cacophony of data. We often think of noise as a presence. In America, we call it snow, the static. I've heard of other things as well. It's called ants in Thailand. Other places have other metaphors. But snow is a presence. We see snow. We see noise. We hear noise. Noise from a communication engineering perspective is the absence of information. Sometimes that absence is the result of too much information, a slippery paradox. Information which cannot be meaningfully discerned is still noise. Information has been rushing at us for about two decades now, pushing out information in the frame of content to such an extent that almost no signal remains that is worth engaging with.
I'm often asked if I fear that AI will replace human creativity, and I don't remotely understand the question. Creativity is where agency rises, and as our agency is questioned, it is more important than ever to reclaim it, through creativity, not adaptability. Not contorting ourselves to machines, but agency — contorting the machines to us. I fear that we will automate our decisions and leave out variations of past patterns based on the false belief that only repetition is possible. Of course, my work is also a remix. It has a lineage. To Nam June Paik, who famously quipped, “I use technology in order to hate it properly.” And this is part of the tension, the contradictions that we're all grappling with. I'm trying to explore the world between archive and training data, between the meaningful acknowledgement of the past and the meaningless reanimation of the past through quantification. Archives are far more than just data points. We're using people's personal stories and difficult experiences for this. There's a beauty of lives lived and the horrors, too. Training images are more than data. There is more to our archives than the clusters of light-coloured pixels. Our symbols and words have meaning because of their context in collective memory. When we remove that, they lose their connection to culture. If we strip meaning from the archive, we have a meaningless archive. We have five billion pieces of information that lack real-world connections. Five billion points of noise. Rather than drifting into the mindset of data brokers, it is critical that we as artists, as curators, as policymakers approach the role of AI in the humanities from a position of the archivist, historian, humanitarian, and storyteller. That is, to resist the demand that we all become engineers and that all history is data science.
I worry that the age of noise will mark the era where we turn to machines to mediate this media sphere on our behalf. It follows a simple logic. To manage artificial information, we turn to artificial intelligence. But I have some questions. What are the strategies of artificial intelligence? The information management strategies that are responsible for the current regime of AI can be reduced to two, abstraction and prediction. We collect endless data about the past, abstract it into loose categories and labels, and then we draw from that data to make predictions. We ask the AI to tell us what the future will look like, what the next image might look like, what the next text might read like. It's all based on these abstractions of the data about the past. This used to be the role of archivists. Archivists used to be the custodians of the past, and archives and curators, facing limited resources of space and time, often pruned what would be preserved. And this shaped the archives. The subjects of these archives adapt themselves to the spaces we make for them. Just as mold grows in the lightest part of a certain film, history is what survives the contours we make for it. We can't save everything. But what history do we lose based on the size of our shelves? These are a series of subjective, institutionalised decisions made by individuals within the context of their positions and biases and privileges and ignorances. The funding mandates, the space, and the time. (No offence!)
Humans never presided over a golden age of inclusivity, but at least the decisions were there on display. The archive provided its own evidence of its gaps. What was included was there, and what was excluded was absent. And those absences could be challenged. Humans could be confronted. Advocates could speak out. I'm reminded of my work with Wikipedia, simultaneously overwhelmed with biographies of men, but also host to a remarkable effort by volunteers to organise and produce biographies of women. When humans are in the loop, humans can intervene in the loop.
The words we shared built chat GPT, the images we shared built Stable Diffusion. Generative AI is just another word for surveillance capitalism. Taking our data with dubious consent and activating it through services it sells back to us. It is a visualisation of the way we organise things, a pretty picture version of the technologies that sorted and categorised us all along. Instead of social media feeds or bank loans or police lineups, these algorithms manifest as uncanny images, disorienting mirrors of the world rendered by a machine that has no experience of that world. If these images are unsettling because they resemble nothing like the lives they claim to represent, it's because that is precisely what automated surveillance was always doing to us. The internet was the Big Bang of the information era, and its noisy debris lingers within the Big Bang of generative AI. Famously, Open AI's chatbot stopped learning somewhere in April of 2021. That's when the bulk of its training was complete, and from there it was all just fine-tuning and calibration. Perhaps that marks the start of the age of noise, the age where streams of information blended into and overwhelmed one another in an indecipherable wall of static, so much information that truth and fiction dissolved into the same fuzz of background radiation.
We need to see knowledge as a collective project, to push for more people to be involved, not less, to insist that meaning and context matters, and to preserve and contest those contexts in all their complexity. If artificial intelligence strips away context, human intelligence will find meaning. If AI plots patterns, humans must find stories. If AI reduces and isolates, humans must find ways to connect and to flourish. There is a trajectory for humanity that rests beyond technology. We are not asleep in the halls of the archive, dreaming of the past. Let's not place human agency into the dark, responsive corners. The challenge of this age of noise is to find and preserve meaning. The antidote to chaos is not enforcing more control. It's elevating context. Fill in the gaps and give the ghosts some peace.
Looking at the Machine | FACT24 Symposiumhttps://www.youtube.com/watch?v=Eqw7U8BA5aM