When Machines Learn to Dream: A Creative Echo Across Time
Hey everyone. I’ve been deep-diving into how technology stirs things up in the art world, especially as I explore AI in my own music. It got me thinking about history, and how this isn’t the first time artists have faced a new machine that seems to challenge everything we know.
Right now, we’re buzzing (or maybe trembling) about generative AI – tools like Midjourney, Stable Diffusion, and GPT-3/4 that can create images and words from simple prompts. It feels revolutionary, like a sudden shift in the creative earth. But step back about 150 years, and artists were having a very similar moment. The culprit then? Photography.
The Camera’s Jolt to the Canvas
Back in the mid-1800s, when guys like Louis Daguerre made photography practical, it was like a lightning strike. Before that, if you wanted a picture of yourself, you hired a painter. It took time, skill, and money. Painting was the main way we captured the visual world, the official record keeper of faces and places.
Suddenly, this camera could do it in minutes. A mechanical eye, capturing reality with unbelievable detail. The public went wild! They called it “daguerreotypomania” in Paris – everyone wanted a photo. Portrait studios popped up everywhere, making images accessible to way more people than ever before. Imagine the middle class, who could never afford an oil portrait, suddenly having a likeness of their family. It was amazing for the public, but for painters? It felt like a direct hit.
The Scream of “Painting is Dead!”
Yeah, you can guess how many painters felt. Threatened. Anxious. Some were downright angry. There’s this famous (maybe legendary) story about the French painter Paul Delaroche seeing a daguerreotype and supposedly declaring, “From today, painting is dead!” Whether he actually said it or not, that phrase captured the fear perfectly. Artists had spent years mastering realism, and now a machine could do it faster and cheaper.
Critics like Charles Baudelaire, a poet and art critic, were furious. He called photography “art’s most mortal enemy,” a soulless, mechanical thing for the unthinking masses. He saw it as a threat, something that would “supplant or corrupt” true art. To him, the camera just copied nature mindlessly, without the spark of human imagination.
Art academies, the gatekeepers of the art world, often shut photography out, saying it was just craft or science, not real art. They dismissed early photos as “mere mechanism” or “industrial imitations.” This resistance wasn’t just in France; it was a global feeling. Many predicted painting, especially portraits, would be devastated. And honestly? They were partly right. The business of portrait painters and miniaturists did collapse as people flocked to photographers.
The language they used back then sounds so familiar today, doesn’t it? They called photography lazy, uncreative, impersonal. They argued a machine could never replace the artist’s hand and soul. Sound like any debates you’ve heard lately about AI?
Finding the Light: How Art Adapted
But here’s the cool part, the part that gives me hope. Not everyone resisted forever. As the initial shock faded, some painters started to use photography. Some used photos as references for tricky details or anatomy – a quiet way of folding the new tech into their process.
More importantly, photography forced painters to ask a huge question: If the camera can capture reality perfectly, what is painting for now? This wasn’t the end; it was a beginning. Painters were suddenly freed from the pressure of just copying the world. They could explore other things!
This liberation directly helped spark movements like Impressionism. Artists like Monet, Degas, and Renoir knew they couldn’t out-realism the camera. So, they stopped trying. Instead, they focused on things the early camera couldn’t capture: the fleeting light, the feeling of a moment, subjective impressions. Their paintings became about color, emotion, and personal vision, not just crystal-clear detail. As one art analysis puts it, painting realized it wasn’t meant to compete with photography, but to complement it, to show what photography couldn’t.
Photography didn’t kill painting; it redefined it. It pushed painting towards abstraction, emotion, and modern art. And guess what? Photography itself eventually evolved into a recognized art form too. Artists like Julia Margaret Cameron and Alfred Stieglitz showed that a photographer wasn’t just a technician; they were artists making creative choices with light, composition, and mood. What looked like a death knell became a catalyst for incredible new art.
The Algorithm Arrives: A 21st-Century Echo
Fast forward to today. We have generative AI. Like photography, it automates aspects of creative labor. It can generate images or text mimicking countless styles learned from vast datasets of human work. And the reaction? So many echoes of the 1800s!
Artists and writers are definitely feeling that anxiety. If an AI can generate art or text instantly and cheaply, what happens to human creators? When AI image generators exploded onto the scene, you saw that same “art is dead” sentiment online. Molly Crabapple, an illustrator, spoke of looking at generative image AI with “horror,” seeing it poised to eliminate humans from illustration.
It’s not just visual art. Writers and actors in Hollywood went on strike in 2023, partly fighting for “guardrails” on AI use. They didn’t want AI to replace them or devalue their work. The resulting contract was a big step, treating AI as a tool writers can use, but not something studios can force on them or use to steal their credit. It’s about ensuring AI is complementary, not a replacement.
We’ve also seen powerful protests. Artists flooded ArtStation, a portfolio site, with a “NO AI GENERATED IMAGES” protest because AI art was showing up alongside their work, feeling like a trivialization. The core issue? These AI models were trained on millions of human images scraped from the internet without permission or compensation. It feels like automated plagiarism, using artists’ creative energy against them.
Over 20,000 creators, including big names like Hans Haacke, Margaret Drabble, Kazuo Ishiguro, and even members of Radiohead, signed a statement against the “unlicensed use of creative works for training generative AI.” Lawsuits have been filed against companies like Stable Diffusion and OpenAI by artists and authors whose work was used without consent. This is the modern version of the 19th-century worry about technology appropriating and reproducing work – but on a scale Daguerre could never have imagined.
Finding New Collaborators in Code
But, just like with photography, alongside the resistance, there’s also adaptation and exploration. Many artists are already seeing AI as a powerful tool to augment their own creativity. Some digital artists use AI image generators to brainstorm ideas or create reference points, then build upon them with their own hand and vision. The human artist is still the director, using AI as a supercharged brush or camera.
Look at someone like Refik Anadol. He creates amazing, immersive installations with AI. One piece used NASA data to train an AI that generated a swirling “dream” visualization of space. He calls criticisms of AI art as soulless “lazy… doomsday hysteria,” seeing algorithms as just another color on the palette.
Even institutions are starting to recognize this. Christie’s auction house held an all-AI art auction, arguing that AI “enhances the human spectrum of creativity,” pushing boundaries with human agency, not replacing it. This echoes how photography came to be seen – not the death of image-making, but an expansion.
Could AI enable entirely new art forms, just as photography led to motion pictures? Artists are programming AI as collaborators, curating outputs, or exploring AI-assisted storytelling. The debate over authorship is tricky – if an AI trained on thousands of poets helps a human poet craft a line, who gets the credit? It’s a new puzzle, but one we’ve faced before. Society eventually recognized the photographer’s creative choices; we’ll likely figure out how to recognize the human artist’s vision when working with AI too, whether it’s in prompting, curating, or refining.
What Makes it “Art,” Anyway?
Both eras force us to wrestle with big questions: What is art? Who is the artist? Can a machine truly be creative? In the 1800s, they asked if a mechanical picture could hold artistic soul. Critics like Baudelaire said no, it was just a copy. Today, some critics say AI art is just a “derivative collage,” a “pareidolia” of art that lacks true consciousness or communication.
But photographers eventually showed their medium could express deep feeling and vision. Maybe artists using AI will do the same, proving the human guiding the tool is the source of authentic expression. It takes time, and debate, for these new forms to gain legitimacy.
Comparing the Echoes: Similarities and Differences
Putting the camera and the algorithm side-by-side, the parallels are loud:
- Disruption: Both threatened traditional creative roles and livelihoods. Painters feared cameras stealing portraits; illustrators fear AI stealing gigs. Both technologies could do certain tasks faster/cheaper.
- Resistance: Established artists and critics initially rejected both as illegitimate or harmful. Baudelaire’s attacks on photography sound a lot like modern artists’ protests against AI being “theft” or “fraudulent.” The language of “corruption” and “enemy” is there in both debates. It’s a fight for the value of human creativity itself.
- Adaptation: In both cases, many artists eventually pivoted to experimentation. The Impressionists redefined painting because photography existed. Today, artists are finding ways to use AI or focus on what makes human art unique.
- Public Journey: The public was initially amazed by both (realistic photos then, incredible AI images now). Skepticism mixed with wonder. Eventually, familiarity leads to acceptance. Photos became normal; AI tools are fast becoming integrated into daily life.
But there are key differences:
- Speed & Scale: Photography matured over decades. AI capabilities have exploded in just a few years and spread globally instantly via the internet. The shock is compressed, maybe more intense. And AI’s scale (training on basically the entire internet) is unprecedented.
- Nature of Output: Early photos were bound to reality. AI can conjure anything imaginary in any style. It can mimic creative imagination directly, which feels like a broader threat than photography did initially.
- Ethics & Economics: While photography affected incomes, it also created new industries. AI’s economic impact is less clear; it might eliminate jobs without creating equivalent new ones, potentially concentrating power with tech companies. The ethical issues around consent for training data are central to the AI debate in a way they weren’t for photography. And labor organizing (like the Hollywood strikes) is a new factor.
- Authorship Perception: People in the 1800s knew a person operated the camera. With AI, the human hand can feel completely hidden, even is present, potentially leading the public to devalue the human role in creative works.
The Enduring Flow of Creativity
So, where does this leave us? History suggests that total displacement isn’t the most likely outcome. Just as painting didn’t die but reinvented itself, and music survived synthesizers, human creativity is resilient.
The role of the artist or writer might evolve. Maybe it becomes more about curation, vision, prompting the right ideas, and adding that uniquely human layer of emotion and meaning that an algorithm can’t replicate. New art forms will likely emerge from the fusion of human and algorithmic creativity.
Society will adjust its understanding of art to include works made with AI, but hopefully, our appreciation for the human imagination at the core will remain. Artists are masters of adaptation. Confronted with the camera, they gave us modern art. Confronted with AI, they are already finding ways to assert the vital value of the human touch.
The debates about automation, ownership, and originality are here to stay. But if history is our guide, technology doesn’t kill art. It pushes us to redefine it, to remember what we truly cherish about creating, and to find new ways for that human spark to shine through, no matter what tools we’re using.
It’s a challenging, exciting, and sometimes scary time. But for artists, that’s often where the most interesting work begins.
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