Why "AI Slop" Might Be the Best Thing to Happen to Visual Storytelling

When Sora 2 dropped, hot on the heels of Meta's Vibes, it opened the floodgates for the "AI Slop": dazzlingly rendered, narratively empty videos that overflow with hyperreal imagery but lack coherent storytelling. Some look terrifyingly photorealistic; others drift in the uncanny valley, beautiful yet hollow. The reaction was swift and nearly unanimous: the web is doomed.

But doesn't have much to do with AI. It's what happens when access to a powerful tool spreads faster than the skill to wield it. More importantly, it's what always happens at the dawn of a new creative medium, when possibility outpaces literacy.

We've Been Here Before

Early photography was full of stiff, uninspired portraits. Desktop publishing in the 1980s and 1990s gave us decades of typographic crimes. The synthesizer faced similar skepticism. Every transformative creative tool goes through an awkward phase where enthusiasm outpaces skill and access outpaces literacy.

And it's not just history. It's recent memory.

YouTube in the mid-2000s unleashed a flood of shaky handheld videos, chaotic "YouTube Poop" remixes, and awkward monologues. Most of it looked like nonsense. But that messy, lawless experimentation was how a generation learned the grammar of digital video. Historians now describe it as the "wild west" of online video, an era when media literacy moved from institutions to individuals.

Today's AI slop is the same story on a new timeline: an unfiltered apprenticeship at global scale. Those strange clips are collectively teaching the medium how to think about composition, pacing, coherence, and emotion. This is how every new artform learns its language.

The scale and speed are different now, but we're moving faster because we're building on existing foundations. Everyone using these tools has absorbed decades of professional media. The question is whether the infrastructure for skill development can keep pace with the democratization of access.

(single) shots and (iteration) loops

Generating an image with a single prompt and calling it done? That's like judging writing by autocomplete. Of course it produces garbage. That's not how meaningful creative work has ever happened. The problem isn't the technology; it's the assumption that creativity happens in an instant rather than through iteration.

Here's what most discourse misses: the real revolution isn't image generation. It's the ability to iterate and explore at a speed and scale previously impossible. We are yet to have convinient tools to harness the power of latest models, but this is just a matter of time.

A filmmaker who once spent three weeks perfecting one sequence can now test thirty approaches to that same scene. That's what word processors did for writers. Removing tedious technical obstacles doesn't erase craft, it liberates it. Creative labor shifts from execution to judgment.

Compressed feedback loops accelerate taste development. The tools that matter will make iteration central, not treat generation as the endpoint. One-click outputs will stay what they are: the creative equivalent of stock footage. The work of value will come from people who see these tools as starting points, not destinations.

Taste Is What Matters

AI can produce technically coherent images. But it has no idea what's worth making. It doesn't know which stories matter, when to break the rules, or when imperfection makes the work memorable.

Everyone has taste, but it's often underdeveloped. Good judgment doesn't require credentials, it requires engagement and intention. Proved by JVC GR-C1 camerans and, later, iPhone. When everyone has access to technically proficient tools, judgment becomes the only differentiator.

We've seen this in the post-Photoshop era. Once digital retouching became ubiquitous, "making things look good" stopped being special. Craft was commoditized; taste became scarce. Fashion magazines launched "no-Photoshop" campaigns to reclaim authenticity, while social platforms like Instagram eroded the monopoly of elite visual gatekeepers, creating micro-styles and aesthetic subcultures.

The same dynamic defines AI art. Once polish is free, meaning costs judgment. Artists who treat AI like Photoshop (as an instrument requiring skill, iteration, and style) will make the one-prompt crowd look like children with crayons.

New Creative Economies Emerging

Creative labor has always evolved alongside technology. When digital photography appeared, wedding photographers panicked. When desktop publishing arrived, print specialists feared extinction. Yet each time, the market expanded. Not because old roles survived unchanged, but because new ones emerged. More people could afford tools which quality was previously out of reach. The same creative-destruction cycle is unfolding again: losses are real, but so are the opportunities.

The question isn't whether displacement is happening (it is). The question is what infrastructure gets built to respond. That means new financial mechanisms that return value to creators, marketplaces for custom styles and model fine-tunes, and training systems that help workers reskill rather than exit.

For decades, visual storytelling required expensive cameras, proprietary software, and years of technical training. Those barriers shaped not only who could create, but whose stories got told. Now, as access costs collapse, different stories become possible and economically viable.

Solo animators run profitable studios from their bedrooms. Communities document their own cultures with authenticity and speed. Independent creators build original IPs once reserved for seven-figure budgets. The pattern mirrors YouTube's evolution: from messy webcam confessions to global-scale productions and entirely new storytelling genres.

AI-assisted creation will follow the same arc, if we design the ecosystem around it. One that supports adaptation and rewards originality. The tools are here. What matters is how we distribute the power to use them.

What This Is Really About

The real revolution isn't what AI can produce in one click. It's who now gets to speak visually at all, and how iteration reshapes the creative learning curve. It's stories that couldn't be told because economics didn't work. It's artists with vision but no pipeline. It's communities documenting themselves in their own language.

The slop is real, and it's everywhere. But it's temporary: the awkward adolescence of a new medium finding its voice. What matters is what we build during the transition. Infrastructure, economic models, and education systems that decide whether AI expands creative possibility or concentrates it further.

At ISPO we are re-thinking video creation around the AI. If what's written above resonates with you, consider joining our community. We're on track to launch our public beta soon.

References