Should We Kill IP law? A Fresh View on Copyright from a Designer

Let me explain why I wrote such a seemingly ridiculous title to this chapter.

My thoughts begin with my conversation with Michael Chruściński, a graphic designer with a new view on what design will be in the AI age. He used to work in an ecommerce marketing company that specialized in the Amazon marketplace across Europe’s largest economies. I had worked in a similar type of company called Pattern. It was an environment obsessed with performance, where each image, line of copy, and click-through percentage was measured. But for Chruściński, the constraints of that world were not the problem, the problem was the refusal to evolve. He decided to leave and build his own practice.

Since July of this year, he has been working at the intersection of AI consulting, art direction, and process design. His work is no longer designing and re-designing graphics with manual precision. He’s evolved to more strategic work such as pulling apart a company’s workflows, exposing the bottlenecks, and then rebuilding the system so that AI is a natural part of it. He is doing more with less using AI.

Chruściński’s personal stack reflects this focus on workflow over novelty. ChatGPT is his daily anchor, while AI Studio serves as his modular toolkit for building lightweight apps that standardize how teams interact with processes. For creative work, he uses Flora AI, a web-based, node-driven interface that mimics ComfyUI’s logic without its steep learning curve. Flora lets him connect text, image, and video generation in a visual way and even tap into early-release models like Veo 3 through a token-based access system.

In our interview, he demos the more intuitive way that Flora is run. Products like ChatGPT functions linearly, where it is a ping pong question and answer user interface. But that’s not the way that most humans think. We think in a more mind map form. That’s why something like Flora AI’s product is a lot more amenable to the way we work. Everything is in a flowchart.

The shifting definition of “creative work”

For Chruściński, the arrival of AI in design is not an extinction event, it is the arrival of a new medium. He draws the parallel to photography’s impact on painting. Cameras didn’t kill the portrait; they pushed artists into impressionism, cubism, and abstraction. AI will push designers in the same way, from pixel-level execution to higher-order roles as storytellers and art directors.

The roles most at risk are the mechanical ones, tasks that can be defined in exact steps and repeated without context. The ones that endure are those that rely on shaping narratives, orchestrating emotion, and connecting ideas. The deciding factor, he says, is care. A person who cares about the work and the audience will consistently outpace someone treating the job as a transaction, even if both have the same AI tools at their disposal.

Lessons from corporate adoption

One of his most compelling examples comes from a large German CPG company. When these large companies run multiple offices and introduce the same product to different markets, they often will localize campaigns and photo shoots with local models. Sometimes, due to a lack of human resources, the smaller countries that exhibit lower sales predictions will have lower priority and be bumped to the bottom of the list. This is why big consumer countries like the US and China will often get more resources and priority in assets. I saw that during my time of working in ecommerce too. This German company, though, began experimenting with AI image from their global office so that the smaller countries can adjust the photos with local design assets and no longer needed to wait.

Across German corporates, Michael sees a similar starting point: enthusiasm for AI with no clear implementation path. Systems are fragmented, multiple CRM tools, manual data entry, disconnected databases, so even when AI could help, there’s nowhere for it to plug in. That’s why Chruściński started giving AI literacy workshops, followed by a live process map. Once people see where the slowdowns really are, the conversation shifts from abstract hype to concrete fixes.

Jack Dorsey’s no-IP future

In my interview with him, we also talked about Jack Dorsey. Michael brought up an article in which Dorsey argued that all IP law should be eliminated. In his view, culture is collective, every song, photograph, design, or novel is an echo of something that came before. Current copyright systems lock away this shared cultural material, allowing individuals or corporations to profit disproportionately from works that are, at their core, built on the commons. Dorsey says the current systems we have today exacerbate the problem where the creator is not the one compensated; instead, the owner of the IP is. Sometimes that’s a massive company, like a record label or management company, already rich because they were at the right place at the right time.

Applied to AI, the logic sharpens. Large models are trained on vast cultural corpora. Every output is an amalgam of what humanity has already made. If all creation is derivative, then gatekeeping access to that cultural base distorts progress. Instead of granting monopolies over derivatives, Dorsey envisions a culture fund, a shared pool that creators and citizens contribute to, which then distributes resources back into the creative ecosystem.

I thought that was a pretty unintuitive thought that a designer would have, because most artists that I know err on the side of copyright protection. But I wonder if I have it all wrong too, that maybe the old laws of copyright and IP ownership is not suitable for a new world of AI where art, songs, words are mixed and remixed to make new creations, often not crediting the original author.

His claim corroborates with the US Copyright Court, that AI-generated works without meaningful human input cannot be copyrighted. In 2023, a US court rejected a case where an artist tried to copyright an AI-generated image with zero human contribution. Copyright law is built around “original works of human authorship,” and machines don’t qualify as authors[i].

However, if a person can show substantial human involvement: through prompts, editing, curation, or transformation, then parts of the work may be copyrighted. For example, if you generate raw AI art but then heavily modify it with your own creative choices (composition, retouching, integrating other elements), you may have a claim to copyright on the human-authored portions. But the AI-generated sections themselves may not be protected. In the US, the Copyright Office requires disclosure of which parts were machine-generated when filing.

Looking Ahead

Maybe the law is trying to retrofit an old system onto a new kind of creation. Creativity in the AI era isn’t about a single author applying final touches. It’s about networks, of machines, of datasets, of people feeding and remixing ideas. To any given artist, where they move a pixel or let the model move it doesn’t change the fact that all art is collective. So maybe the question shouldn’t be about edits but about what is the new way to compensate the original creators. 

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Hello! I’m Sharon Gai, a keynote speaker on AI and its effects on workers and society. 

[i] Thaler v Perlmutter, No. 1:22‑cv‑01564 (D DC Aug 18, 2023) (district court affirming that an AI‑generated work lacks human authorship and is ineligible for copyright)