Recently, I had a task that was not exactly art. An application needed my biography in three different word counts, and a budget in a format I never used. I was late, and the tool was right there.

I typed a prompt, watched the paragraphs assemble themselves in seconds, and then stopped with my hands hovering over the keyboard.

In my last post I called generative AI a parasitic renaissance: an age of creative abundance, built on the theft of the life’s work of our whole craft’s creative lineage. Nothing about that has changed. But since I published it, most conversations on that topic came down to the same question, or a version of it.

And what do we do now?

In this article I try to give my answer. That answer is incomplete. It is not an exit from the dilemma, but a code of conduct for navigating life inside it.

Can responsible AI use exist at all?

Yes and no, and the difference matters more than the answer.

The answer is a very clear no, if we expect responsibility to be a property of the tool. There is no way to turn a parasitically trained model into a clean one. We can’t prompt, license or legislate our way out of it. The machine stays what it is, no matter how we use it. Whoever sells you “ethical AI” as a feature, sells you a story.

But maybe it can be a yes, if responsibility is in user behaviour. It’s a matter of daily discipline, a process that we need to commit to. It can fail, very easily. While it does not change the machine at all, it will keep us honest. And honesty is the one thing I claimed is left in the parasitic renaissance.

Also, “responsible” is a big word, and “big” is often used to avoid decisions. So let’s make it precise. Responsible to whom? In my practice, four parties:

• The artists whose work was stolen to train the models. I owe them not to increase the demand for uncompensated extraction. I also owe them not to create stuff that competes with them for their livelihood.
• The people whose job is the task I’m about to automate. I owe them honesty about the fact that my convenience may be their lost income. While we talked about artists above, this rule extends to all other crafts and skills that I can automate.
• My audience. They are owed the truth about what they are looking at, because the whole arts and culture sector runs on attribution. We want to know who created what, and the creators deserve credits.
• Myself and my craft. I owe it to the work that made me worth watching, not to hollow it out for speed. I owe it to myself, to keep my skills intact and my mind sharp.

Four addressees, three rules, one commitment. Everything else is just details.

One thing before we start, because it usually comes up quickly: I know that these rules, that apply to individual people only, will not fix a broken industry. There is no ethical consumption under platform capitalism, and one human’s principles will not change what OpenAI does next.

I still don’t consider this a reason to do nothing. We are the domain experts in the fields being extracted from. This means we have more leverage over this specific supply chain than most people have over anything in their lives. Our harm reduction counts, even when it is only partial. Norms compound. Every licensing deal and consent tool that exists now, is only there because enough people wanted it. And we are not doing our peers a favor by pretending there are no choices. I have choices. So do you. That is exactly why we feel uncomfortable. The choices are on us.

And nope, this is not the middle ground I said does not exist. Middle ground would be pretending we can make the tool clean. This code of conduct is choosing to work with dirty hands and open eyes.

Rule 1: Only use models trained on licensed or consented data

This tries to get to the root of the problem, so we’ll talk about it first. It is also one where I have to damage my own rule’s reputation from the start: licensed is necessary, but not sufficient.

Three reasons I hold myself to a stricter standard than the label suggests:

Licensing is not consent

Licensing is not necessarily consent. As of Adobe’s own FAQ, contributors to Adobe Stock cannot opt out of having their work used to train Firefly (the model that is often credited as the one that uses on licensed stuff in training data). They get a bonus instead. Technically, that is a license, but it is buried in the terms of service. To be meaningful this would need three steps: consent, credit, and compensation. There is no payment trail back to the artists, so “licensed” is only doing rhetorical work here. Find

Certification exists but is still very scarce. Fairly Trained certifies models that use no copyrighted work without a licence. It exists, it’s a real thing but it does not cover the tools that were in front of me at one in the morning.

We can’t change the past. Even a perfectly consented model is built on top of a decade of unconsented training. The machine was built on stolen data. No license sold today unsteals it. So Rule 1 is harm reduction. It can never be absolution. I feel I need to be precise about that, because precision is what separates an ethic from a vibe.

Because binary rules often fail in real world scenarios, I am not using a yes/no test, but a ladder, and I try to be as high on it as the task allows:

The licence ladder: from my own archive to refusal

1. My own archive. As a former software engineer, I can fine-tune models on material I made myself. One dataset where consent is clear, and provable.
2. Certified or licensed tools with a traceable payment trail to the ones who created the training data.
3. Public domain and CC0 material, built with governance. For example, Spawning’s PD12M. It has twelve million public domain images, checked against an opt-out registry.
4. General models, with mitigations: Don’t imitate the style of real artists. Don’t use them when I can’t judge the output myself. Disclose it, and use as little of it as possible.
5. Don’t. There are tasks I simply keep away from these tools.

We also need to look at it in reverse: what are my own terms for my work and AI? If I demand consent from the machines, I owe the machines an answer about how to treat my stuff. I declare it in machine-readable form, using frameworks like Creative Commons’ CC Signals, and potentially opt-out registries. If you don’t have a position yet, get one. Giving away terms of use is a decision too. It should be yours, not someone else’s.

Rule 2: Only automate what I could do, would do, and would admit to

The first version of this rule was “automate tasks we could and would do ourselves.” It was a good try, but with a loophole. Everyone “would” learn everything, in theory. So I added the third test, the one that actually bites:

Could I do this myself? Would I have done it without the machine? And would I be comfortable if everyone knew exactly which parts I automated?

If my answer changes depending on who knows, I found the dishonesty the rule was supposed to counter. It’s a lie detector.

Two refinements I had to make along the way:

Competence is the boundary

Automate only what I have already mastered, or at least I am qualified to judge. Because I cannot responsibly supervise output, that I can’t evaluate. A study by Microsoft Research among knowledge workers suggests that people skip critical verification exactly when they don’t have the skills to inspect what the AI produced. Automating beyond your own competence seems to make you faster, but it primarily makes you irresponsible, because you never know if the AI hallucinates. It removes the only part of the job that was ever really yours.

Never automate a task that exists to teach someone

The poster you design badly, the grant text you rewrite five times, the first mix that sounds wrong. None of them are busywork. That is your training ground. In the last post I mentioned creative lineages being broken. This is how it happens: not necessarily with a dramatic theft, but with a whole generation never doing the entry-level repetitions, that would allow them to become masters down the road. So the rule stands to protect our own learning, and it stands double for anybody I teach or advise. I will not silently replace a paid task of a student, assistant or collaborator with a prompt.

And still: this rule does not answer the accountant. In the last post I admitted that we artists defend our own work against the machine but happily let it do the work of others – accounting, transcription, translation, whatever. Rule 2 doesn’t solve that. If I automate a task that would otherwise pay someone’s bills, I have chosen convenience over a livelihood. I can’t make that choice disappear, but I can acknowledge it and that will change my approach.

The accountant clause: every euro AI saves goes to a human

So I created a companion clause, and it is the most practical thing in this post: it says every euro that AI saves me should be spent on another human. If I no longer pay a translator, the money saved goes to a photographer, a dancer, an assistant, or maybe even a non-profit association. This gives back to our community … and makes a difference.

Rule 3: Don’t automate my thinking

The first two rules govern our responsibility towards others. This one makes sure we don’t lose too much ourselves.

Look at the layers of thinking in the following table, because “thinking” is not only one thing:

The reason to protect formulation and judgement is that these set you apart in a market where execution became fast and cheap. It is what you get paid for in a market flooded with “good enough” (what others might call AI slop). In the last post I said, that a small group of artists will stay valuable or even rise in value because they, and their audience, see the difference where most people will not. That ability stems from doing the thinking yourself, thousands of times. Automating it, saws off the branch you sit on.

There is scientific evidence, and it is not comfortable. MIT researchers put 54 people in EEG caps and had them write essays. One group used ChatGPT from the start, one did not use generative AI, and (the interesting part) some who wrote unaided first and used the model afterwards. The group that started with the AI showed the weakest activity in networks for memory and remembered less of their own text. They also produced the most generic texts. The ones who wrote first and used AI second showed the strongest connectivity of all.

This suggests not “AI makes you dumb.” It suggests it is about order. Think, before you involve the machine. Draft yourself. Argue first. Get lost in the matter. Then use the machine on work that you already did.

Use AI as an adversary, not an author

This points to a better use of AI than generation: have it challenge your work, list counterarguments to your opinions. Use it to show the weak sections in your draft or act as a hostile curator. Let it ask the questions you are avoiding, because you are afraid you don’t have a good answer. This leads to more and better thinking by you. The AI is used as tool and not as a ghostwriter.

And if you need the image that made me write this post: remember the man from the last post about the parasitic renaissance dilemma, staring at his grandmother’s porch with tears in his eyes. Neither his tears, nor my grief can ever be generated by AI. They can only be described. And that description of a feeling, will never be the feeling. The third rule is not about morality, it is about staying an artist.

One commitment: say what I did

The rules above govern what I do. None of them governs what I say, and that gap is where most of the culture sector’s trust problems will actually happen. So I disclose what I used, in credits, captions, grant reports, everywhere it matters

AI-generated, AI-assisted, AI-free: three words that should be on every credit line

It’s not complicated, but it needs three words instead of vague ones:

• AI-generated: the machine produced it, I directed it.
• AI-assisted: I made it; the machine did specific, nameable steps.
• AI-free: no model involved, and now a claim worth defending.

I also keep a boring log of what I used and why. Boring is the point: six months later, when a collaborator asks or a contract does, memory is not evidence.

This is no longer a purely private decision, at least in Europe. Since August 2, 2026, the transparency obligations of the EU AI Act apply: AI-generated content must be machine-readable marked, deepfakes labeled, AI text published on matters of public interest disclosed. So the law has arrived where the ethics were pointing.

The law is the floor. My disclosure is not there because Brussels told me to; it is there because my audience, surveys of museum visitors and cultural audiences assume they are being told the truth, and are angry when they find out they weren’t.

Five red lines I don’t cross

Rules cover the negotiable zone. Some things are not negotiable, and it helps to write them down:

1. I don’t sign AI output as wholly my own work.
2. I don’t generate the identifiable style, voice or likeness of a living artist.
3. I don’t replace a paid human step in a project without disclosure.
4. I don’t put collaborators’, students’ or clients’ material into a tool without their consent.
5. I don’t let a model be the author of any judgment about another artist.

Where my rules hit their ceiling: what institutions must do

Three rules and a commitment change my personal conduct. They don’t change anything about the machine, and I don’t want to end this text pretending otherwise. Individual ethics should be paired with demands on the institutions that move money:

Public funders and venues should disclose AI use and license terms in applications and contracts. Public money should never buy models trained on the work of its own citizens without compensation. And politicians need to stop pretending this regulates itself. Because if we trust in that self-regulation, the money just drifts upward, as always.

The porch, ten years later

I can’t tell what the man with the wisteria should have done. I don’t know whether his four images were worth the extraction they cost. Did his tears justify the theft? And what does he owe the thousands of painters who drew his grandmother’s porch without ever meeting her? Those questions are still open, and maybe they will stay unanswered.

What I do know is that in a dilemma, the only thing you fully own, is your own conduct. These rules will not fix generative AI’s underlying issue. And they will not repay the cultural debt. They only mean that when someone asks me, why I used these tools and where I refused, I will have an answer that doesn’t require me to look away.

My hands are still dirty. Now I know exactly how dirty, and why. That is not peace of mind. It is the minimum.

If you have not read the first part of this argument, the one about the porch, the grandmother, and the theft beneath the miracle, start there: The Parasitic Renaissance of Generative AI. And if you use these tools: which rule do you break most often? I’d genuinely like to know.

Frequently asked questions about responsible AI use

About FraGue Moser-Kindler

FraGue Moser-Kindler is a former software engineer turned multi-disciplinary artist, author and creative advisor based in Salzburg, Austria. He explores AI ethics and if AI can be used in arts and culture in a responsible way.

Der Beitrag Can responsible AI use exist? The rules I live by erschien zuerst auf FraGue Moser-Kindler | Artist, Author & Creative Advisor.

In my opinion the defining tragedy of generative AI is that its gift of democratization is inherently inseparable from the historic theft of human craft. Therefore, I call it a parasitic renaissance of generative AI. Like the renaissance, it is a time where we can see a lot of creative work, due to the removal of the time-gated skill acquisition process aka learning the craft. But none of it is possible without the parasitic extraction of the work of generations of artists and thinkers before us. A classic dilemma where both sides of the coin have merit, but each side wants to sacrifice the other.

For the sake of clarity, I’ll use image generation and painting in this text, but the same principle goes for writing, music and basically every other art form or craft that can be replicated with artificial intelligence.

Why democratization in art through AI matters

Art has historically worked as a mirror of society. It gave us a glimpse into the mind or soul of an artist. The collective body of art showed us the state of humanity. Previously the abilities to show others what’s on your mind was only available to those who had access to teachers of the craft and the time and discipline to hone it. Throughout history this could be classified as time or class privilege.

Having an artistic vision meant nothing unless you invested thousands of hours mastering anatomy, perspective, draftsmanship, color theory, or later, software. Craft acted as an involuntary gatekeeper.

When this barrier falls, it gives us a higher-resolution image of the status quo. More people will be able to materialize what’s in their mind. We gain a richer, potentially more diverse perception of how we humans see the world.

We will see or hear stories, that would otherwise have been locked away. In my opinion, that is a desirable outcome.

An unprecedented plunder of our artistic lineage

Artists critique that their work was stolen to feed the machine. That is an undeniable fact. Legal courts around the world are trying to figure out how to handle this. Living artists are forced to compete with machine output, that is based on their work, skill and time. They never agreed and never saw compensation or appreciation. Even if we think legal courts will settle this, it’s unlikely that notable money will find its way to all the artists that are victims of this AI theft.

We also sacrifice culture. Traditionally any craft was passed down in creative lineages over generations. Teachers, students, apprenticeships, struggle and time invested. An artists style depended on those who came before him and who walked besides him. The masters who taught and the peers who walked the way together.

With the emergence of generative AI, this lineages are broken. Everything becomes averaged out. This might give birth to new lineages of generative AI users, who follow in similar traditions, but they start at zero.

Living inside the dilemma of the parasitic renaissance

The democratization of art in the hands of amateurs, via generative AI, relies on the economic death of the artisan. AI decouples the vision from the execution. It dignifies the inner world of non-specialists by letting them materialize their thoughts by writing a prompt that simply explains what they envision. In doing so, it treats centuries of human discipline and physical sacrifice as a solved mathematical problem instead of an act of lived endurance.

If everyone can create art that is “good enough,” many artists will not be able to earn a living anymore. A small fracture of artists will be. Those who stand out among the others and their art will become even more valuable, but only for those who can see the difference and are willing to pay the premium price. Most other illustrations will be done by AI, because it will be “good enough” and most humans won’t notice it’s AI soon.

Interestingly, artists, including myself, are not worried if they use generative AI to tackle tasks that don’t produce art. But the underlying machine, runs on the same mechanics. It pulls from the work of humans before it. We just don’t care about it, if it is not our work, or we don’t like the work at all. Thinking it through until the end, would lead to the exact same dilemma on another playing-field. It does your accounting but someone else could do it, who spent the time to learn it. It’s just not art.

But is it fair, that we don’t care? We defend our own work against the machine, but not the work of others. Those others also learned their craft, and some of them might love their jobs, as much as we love being artists – even if most of us find it hard to get behind the idea of loving to be an accountant or a physical worker in hazardous environment. If we abstract the idea of what happens with genAi and art, it is exactly the same as AI taking any other job.

I try to give that dilemma a practical answer in my follow-up post, including the part I could not solve: Is there a way for responsible AI use?

Beyond denial

Silicon Valley just wants to wave AI through and wants artists to adapt to and adopt the new ways. Traditional artists and many others want to outright ban all AI, because they are afraid of losing jobs and possible Terminator scenarios. In between are tech-enthusiasts who are excited to live through a major change in human history, entrepreneurs who see this fourth industrial revolution as their once-in-a-lifetime opportunity, culture workers who automate costly tasks that would have prevented projects from happening, and many others who use AI in their daily lifes.

There is no objectively correct answer on how to navigate this dilemma, and there is no real middle-ground. Being fine with AI doing some work, as long as it not ours, is hypocrisy. Thinking we can put it back in a box, is naive.

There might be solutions in the future, like models that are exclusively trained on data where everyone approved. There could be new tech that allows us to track what data was used for a generation and pay compensation. But right now, we have very little of the first and we don’t have the second. And over all, the tech was still built using data that was stolen, even if we fix it later.

So the parasitic renaissance dilemma will be a topic for the years to come. Anyone who uses generative AI tools must develop the moral honesty to acknowledge both sides: celebrating the voice they have gained, while grieving the cultural debt they will likely never repay.

October 4, 2026: Since writing this, I tried to turn the honesty I demand here into rules I can actually follow → Can responsible AI use exist? The rules I live by.

About FraGue Moser-Kindler

FraGue Moser-Kindler is a former software engineer turned multi-disciplinary artist, author and creative advisor based in Salzburg, Austria.

Der Beitrag The Parasitic Renaissance: how generative AI democratizes art through theft erschien zuerst auf FraGue Moser-Kindler | Artist, Author & Creative Advisor.

The Raygun controversy in a nutshell

Raygun was the lowest scoring contender in the b-girl category of the Paris Olympics in 2024. She did not earn a single vote from the judges. So far so good, as every competition needs someone to score lowest. In her presentation, especially the last battle, she leaned heavily into creative moves and references to her home Australia. Usually this is considered a positive thing in the breaking scene, as dancers work to develop a unique style. In her case, the missing athletic component that was displayed by the other contenders, in combination with the creative, some might call it quirky, approach led to her performance being picked up by the masses. And it became a global meme.

Raygun-related memes dominated social media, TV shows and online magazines around the globe. It came so far, that the real Olympic winners of this historic event did not get the shine they deserved. All medalists together did not have the same reach as the lowest-scoring contender of the whole breaking Olympics. The stories that should have traveled the world didn’t and the dance scene hated it. It came so far that there were rumors of her cheating her way into the Olympics and of her being the reason for breaking not being in the Olympics in LA 2028. Both of these have been debunked early, but most didn’t care. Feelings are hurt until this day.

The Netflix documentary and what it does well

The documentary was well-crafted, for a mainstream audience. It tells the story of Raygun’s Olympic journey. Not more, not less. It doesn’t judge breaking, the Olympic Games or the international scene reactions. It clears up the rumors and conspiracy theories, in a short segment close to the end.

Why Breaking Badly comes at the wrong time

Untold Raygun – Breaking Badly would have been great a year after Paris, or even earlier. It would have helped clear up the rumors and give everyone closure. At the time of the publication, nobody wanted to talk about it anymore. But then everything came back into focus, reigniting a debate, that nobody needed in the first place. As someone who also works in social media, I will have to read unnecessary Raygun jokes for a few more months to come.

TL;DR: Untold Raygun: Breaking Badly from Netflix is a well-crafted documentary that came at least a year too late, stirring up talks and emotions that should have been forgotten by now.

About FraGue Moser-Kindler

FraGue Moser-Kindler is a multi-disciplinary artist, author and creative advisor based in Salzburg, Austria. He is best known for his dance work and non-fiction books around dance and dance-business.

Der Beitrag Untold: Raygun – Breaking Badly Review: Nicely crafted, badly timed erschien zuerst auf FraGue Moser-Kindler | Artist, Author & Creative Advisor.

This story recently got some minor updates due to high interest, because breaking was part of the Olympic Games 2024.

It’s called Breaking

I call the dance that I love breaking. I consider it to be the correct original term, which also makes sense as B-Boys & B-Girls initially danced to the break of the record. Therefore the term B-Boy refers to Break-Boy. I am aware that Bronx-Boy is also a common meaning, but the word Bronx-Boy relates to where one comes from and not what he dances, so I go with the other one.

B-Boying is also a thing, but I’m not too fond of it

The term “b-boying” is also accepted and common within our scene, but I don’t like and use it for multiple reasons:

• It names the dance after the dancer, but the name of the dancer is, in my books, already named after the dance. You would not say “break-boying,” would you?
• The word “b-boying” does not flow well about my lips when I try to say it.
• “B-Boy” and “b-girl” are terms that have a gender. Using “b-boying” as the name for the dance opens up a lot of questions like: Is it “b-girling” if a female does that dance? If so, do we just call it different, or is it another thing? If it is another thing, can “b-girls” do “b-boying” and vice versa? What happens if we enter the realm of transgender and so on? For me, that whole discussion is an endless loop that I don’t want to be a part of. For me, “b-girls” and “b-boys” are “breakers” and do “breaking”.

The term breakdance is inauthentic (but…)

Breakdance is a term that was introduced by a British music promoter who could either not remember “breaking” and made up “breakdance” on the spot or just said it the wrong way. Stories differ about which of these options it originally was. But the essential point is: The term has nothing to do with the people who created our dance.

I still use the term “breakdance” in addition – especially on the website and in promotion, because that is what the uninitiated would use when searching for our dance. In that instances I consider it my obligation to teach them about it in my first class or workshop. Not using “breakdance,” would lead to people finding websites of others, who care less about our dance and the correct terminology.

Wanna check out someone else’s take on it? Watch B-Boy Crumbs talk about it below.

About FraGue Moser-Kindler

FraGue Moser-Kindler is a multi-disciplinary artist, author and creative advisor, best known for his theatre work with breaking and writing non-fiction about dance and dance business.

Der Beitrag Why I call it Breaking instead of B-Boying and Breakdance erschien zuerst auf FraGue Moser-Kindler | Artist, Author & Creative Advisor.

You can still listen to the episodes in the Tanzcafé Podcast archive.

Der Beitrag Tanzcafé Podcast is discontinued erschien zuerst auf FraGue Moser-Kindler | Artist, Author & Creative Advisor.

Generative AI is not a futuristic concept. It is an active collaborator and competitor within the cultural landscape. It challenges the status quo, how art has been made. And it might take the jobs of many who are “just doing their job.”

The Current State of Generative AI

The current boom in AI art is defined by rapidly evolving tools. Text-to-Image models like Midjourney and DALL-E, advanced language models such as ChatGPT or Grok, and powerful music and video generators are making creation faster then ever. These tools have drastically lowered the barrier to entry for creative output.

A user with a simple text prompt can generate complex visual concepts, musical scores, or narrative outlines in seconds. This accessibility democratizes creation, allowing users who lack traditional skills (like painting, writing or filmmaking) to execute ideas at an unprecedented speed.

AI: Creator, Co-Pilot, and Cultural Catalyst

The possibilities AI offers in culture and arts are best understood through a dual lens: creation and administration.

AI for Creation

AI could serve as a powerful partner. For an artist, it can be used for rapid prototyping, instantly generating variations of a concept, breaking through creative blocks, or pushing the boundaries of traditional media into new forms of interactive and personalized art. AI can turn a simple sketch into a detailed rendering, or translate a mood into a musical composition, focusing the human creator’s time on curation and direction rather than tedious execution.

But exactly in this advantage is also the big problem. Many who did not learn any skills in the arts are now able to participate in a game that was only for those who “earned their stripes” in thousands of hours of practice.

Connoisseurs still recognize AI art as machine-made, but the current speed of development suggests it’s only a matter of a few years, or maybe months, until it will be indistinguishable to all of us. The big bunch of people don’t see the difference now, and many more don’t care. This creates a potential imbalance in compensation for time invested.

AI for Logistics (The ‘Orga’)

AI’s role also extends far beyond the studio and into the operational core of cultural institutions. Here, it acts as a catalyst for efficiency. It can help with grant writing, with texting and illustrating concepts, ads and other sales material.

It finds holes in your workflow, acts as your accountant, does research, and can speed up processes. Especially this way of using AI for the orga in your artistic ventures gives a lot of power back to the artists, as they would now be able to do tasks themselves, which usually required a producer. It removes gatekeeping and makes producing art more affordable for the artist.

While using AI for creation is currently frowned upon, using AI to support in the orga is a thing people appreciate. But if we think things through, it is doing the same to producers and assistants as it does to artists in the other case. So, celebrating one of those two and condemning the other would be a double standard.

The Ethics of Creation: Ownership and the Authenticity Crisis

The rapid adoption of AI is accompanied by significant moral and legal concerns that must be addressed and understood by artists and institutions alike.

Ownership and Copyright

The most contentious issue involves the training data. Generative AI models are trained on massive amounts of data. Billions of copyrighted images, texts, or songs have been fed into the machine, most of the time without the explicit consent or compensation of the original human creators. This raises fundamental questions of intellectual property and is copyright infringement on a massive scale.

When an AI creates a piece, who owns it: the original artists whose work was scraped, the company that built the model, or the user who supplied the prompt? Current legal frameworks are struggling with this question. In most countries, the law gravitates towards “when something is created by AI, you can monetize it, but you don’t have a copyright.” Means everyone could steal what the AI created, because it’s nobody’s intellectual property.

An interesting story from a US Copyright Office shows how this could end up in reality. A creator got copyright on a print and digital comic because the copyright office deemed the arrangement of the comic, which was done by a human, as enough to say: “this is a new work, defined by the human’s involvement.” Important to note, only the comic in its entirety has a copyright. The single graphics that are generated by AI, can still be used by everyone and are not protected.

The laws around this will change quickly, and it will definitely be a pain in the ass to stay up to date.

The Crisis of Authenticity

The ease and speed of AI output also generate an authenticity crisis. If an AI can create a complex, technically proficient painting in under a minute, does the work still hold the same cultural value as a piece created over months of human labor, struggle, and learned skill? Many, including me, feel the essence of art lies in the effort and the human intent, which AI currently bypasses, leading to a devaluing of traditional artistic expertise.

That’s the point we discussed already. Art lovers and people who are skilled in the arts can see the difference and despise work created by AI. For good reasons. Studio Ghibli Founder Hayao Miyazaki called AI-created graphics an “Insult To Life Itself,” after millions of AI-generated images, in the signature style of his studio, showed up all over social media.

AI will take our jobs

The threat of AI taking jobs is real. Especially jobs that are basically doing the same thing over and over. Mundane intellectual labor is the first thing that will be replaced by AI. Most creative jobs will be among these. Top players within their respective fields will have no problem, as they are paid for their taste and style of doing things in a specific way.

But the average person’s work can and will be replaced by AI, as it is more consistent and will soon be cheaper. Physical jobs (everything that is not in the office) will be viable for a few more years, until robots can be mass-produced cheaply at scale.

What do we make of it?

AI is here to stay. Thinking about it differently is naive. Too many global players with too much money are currently racing towards the improvement of their AI systems and they are already integrated everywhere.

It’s time for everyone to think about how we’ll handle AI. You can ignore, you can hate it, or you can learn to dance with it. There will be bubbles that are AI-free, but the majority of life will integrate AI, whether we like it or not. The real challenge is not to reject the technology, but to define its role in your workflow and find ways to improve your art, without taking away its soul.

I recently wrote two additional articles about this topic. In “The Parasitic Renaissance of generative AI,” I explore the dilemma of giving a voice to the many, while sacrificing the work of those who came before us and in “Can responsible AI use exist?” I try to define rules that enable me to navigate that dilemma.

While I don’t have perfect answers yet, it helped me to gain a little more clarity about the topic. And I still think we should learn how to build an EMP.

About FraGue Moser-Kindler

FraGue Moser-Kindler is a former software engineer turned multi-disciplinary artist, author and creative advisor based in Salzburg, Austria. He explores AI ethics and if AI can be used in arts and culture in a responsible way.

Der Beitrag Navigating the AI Revolution in Art and Culture erschien zuerst auf FraGue Moser-Kindler | Artist, Author & Creative Advisor.

Sixteen b-boys and sixteen b-girls hit the stage, all hungry for that top spot. The crowd? Insane. Full of life, cheering like their lives depended on it. The battles were intense, the energy unmatched, and by the end of it all, two names stood out: Menno and India. They didn’t just win—they made history.

The event wasn’t just about the competition, though. It was a full-on celebration of hip-hop culture. Amjad and Magá Moura were hosting, hyping the crowd like pros. DJ Nobunaga dropped a mix of old and new beats challenging the dancers to do their best. And the judges—Jeromeskee, Narumi, Amir, Roxy, and Lil G — had the impossible job of picking winners. Every decision felt like a coin toss with how close the battles were. As usual, many disagreed with their decisions, but that is a given when the competition reaches the highest level there is.

Before the finals, there was the Red Bull BC One Camp Rio—a three-day lead-up packed with workshops, battles, and exchanges. It brought breakers from all over together, trading ideas and skills. By the time the final rolled around, the vibe was already electric.

The battles were pure madness. Right from the first clash in the b-boy category, between Hiro10 and Samuka, the crowd was in it. Toquinha, a local favorite, made waves, becoming the first Brazilian b-girl to hit the semis. Then there were international powerhouses like Yasmin from Japan and Alvin, each bringing something unique to the floor.

One of my personal highlights was the showdown of the Red Bull BC One All Stars Victor and Menno. Menno came out on top, clinching his fourth Red Bull BC One title. A new record right there, and as Menno’s style is not for everyone and hard to read, many scream it’s undeserved. I won’t judge – but I see why he won.

India went for her second title. She brought power, creativity, and flow like no one else. Seeing her and Menno celebrate together, as crew mates, was the perfect way to close the night.

While the Olympics didn’t pick up Breaking for the next edition, Breaking isn’t just alive — it’s thriving. I am looking forward to the 2025 season and to see all of ya in Tokyo.

Der Beitrag Red Bull BC One World Final 2024 erschien zuerst auf FraGue Moser-Kindler | Artist, Author & Creative Advisor.

Now that the Olympic Games are over, I perceive them as a net positive. But before we dive deeper into the matter, let’s check what people were worried about.

Disclaimer: I know it’s not called Breakdance in the scene, but I also want to reach people who don’t know that.

The risk of breakdance being part of the Olympic Games

The biggest fear in the dance scene is that breaking will become detached from its cultural roots, and the bigger part of the world will perceive it as an acrobatic form of sports instead of an art form that goes hand in hand with cultural values. There is nothing we can say to debunk this claim, and many people who perceived breaking through a classical sports lens did not understand why dancers freestyled to the music instead of preparing a fixed routine like floor gymnasts.

The advantages of breaking at Olympia

With breaking becoming an Olympic discipline, its exposure is now much bigger. The bigger exposure will create a lot of opportunities for dancers to earn more money and educate the public (if they choose to do so). The older generation will be able to judge and share their view about dance and culture. The young generation will have an additional platform to test their skills. This attention will lead to even more brands and sponsors come on-board for breaking, which opens up opportunities for people to make a living from breaking.

Will breaking change because of its inclusion in the Olympic Games?

Yes and No. We will see an increased focus on the athletic aspects of the dance. The young generation is already pushing the boundaries of what can be done. Olympia will only speed up this development, but it is not its sole reason. Breaking has always been a phenomenon living in the twilight between art and sports, and the aspect that caught people’s initial attention was the acrobatics. This will not change.

The jams, battles and gatherings where we celebrate the culture will not go away just because there is an additional platform. Underground events that are true to the culture will still be around, and they are not competing with sports competitions. It will be in the power and responsibility of all the b-girls and b-boys participating in significant sports events, like Olympia, to represent our culture appropriately. This includes competitors, judges, consultants, and even visitors familiar with the culture.

Manny talked to Red Bull BC One 2020 E-Battle Champ and World Final Runner-Up Madmax about the balance between being an athlete and an artist. Also, Tracy interviewed Ayane, talking about her point of view when thinking about Paris 2024. I highly recommend you read them both.

What happened with Breaking in the Olympic Games 2024?

First off, we had some amazing battles with more eyeballs than we are used to. B-Girl Ami, from Japan, won the gold medal with Nicka, from Lithuania, and 671, from China, coming in second and third. Phil Wizard, from Canada, took the win in the b-boy category, with Dany Dan, from France, and Victor, from the USA, taking silver and bronze.

The dancers enjoyed the music provided by DJs Fleg and Plash and gave their best. There was some controversy about B-Girl Raygun from Australia, who presented a more originality-based approach to the dance, which was not well-perceived by the uninitiated part of the audience. To be honest, it was to be expected that something like this might happen. Raygun did an amazing job, but one can’t please everyone.

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A post shared by WDSF Breaking for Gold (@_breakingforgold)

I’d like to paraphrase Theodore Rosevelt here and leave it at that.

It is not the critic who counts; not the one who points out how the strong one stumbles, or where the doer of deeds could have done them better. The credit belongs to the one who is actually in the arena.

Theodore Rosevelt

The battles were great, the dancers performed like crazy and some unsung heroes from the scene stepped up to take care of the many tasks needed to make the event happen.

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A post shared by WDSF Breaking for Gold (@_breakingforgold)

I call that a win.

Dig deeper into breaking at the Olympic Games

Here are some links to stuff others had to say.

• https://www.worlddancesport.org/News/Everyone-Won-with-the-2024-Olympic-B-Boys-Competition-3465
• https://www.cbsnews.com/news/breaking-2024-paris-olympics-medals-sunny-choi-viktor-montalvo-jeffrey-louis/
• https://www.youtube.com/watch?v=whUx-5mbLl0
• https://www.youtube.com/watch?v=aYUgZ5WpYP8
• https://www.youtube.com/watch?v=d-Vo866_jhY
• https://www.youtube.com/watch?v=Syt3_Jz4gwU

Der Beitrag Breakdance at the Olympic Games 2024 erschien zuerst auf FraGue Moser-Kindler | Artist, Author & Creative Advisor.

Before we jump into the topic itself, for the sake of this article, I refer to freestyle as “improvisation within the boundaries of a dance style” and not “do whatever you want”.

Here are my two cents on why this discussion does not go anywhere and why you should be able to freestyle and create choreography. To clarify my point, I will use my favourite metaphor to compare dance to a language.

Our moves in any given style are comparable to words in a language and, therefore form our vocabulary. Our grammar is the flow of the style and how we connect our moves to form our dance being the text that has a meaning that is created by the combination of words. And finally in hip hop and it’s related styles, music is the topic we talk about.

The difference between dancing freestyle or a set choreography is like the difference of talking free versus reciting a poem. Both are fine at the correct time. You can make a serious impact by having the right poem at hand for the right occasion, but bringing a poem about the beauty of x-mas in a discussion about the ecologic crisis is just stupid.

At the same time, you miss out on a big part of the beauty of choreography if you don’t understand how the moves connect. This is the same as learning a poem in a foreign language when you can tell it to people but don’t know what it means.

And you can’t say you are a master of a language/dance if you can’t create a speech/choreography to a given topic.

This means there is no “which is better/superior/whatever”. You need to understand both to master your craft. There is nothing wrong in specialising in one or the other if you want. But if you do so, don’t divide what’s one in an artificial discussion and openly admit that you don’t care enough to work to learn both.

Der Beitrag Of Freestyle and Choreography erschien zuerst auf FraGue Moser-Kindler | Artist, Author & Creative Advisor.

What is hip hop dance?

Hip-hop dance is a vibrant form of expression and kinetic poetry born from hip-hop culture’s energetic and resilient spirit. This culture, originating from the 1970s South Bronx, is a rich tapestry woven with various elements, each contributing to its diverse and dynamic identity. While breaking was the original dance form of hip hop culture, hip-hop dance came in later and can be considered the younger sibling of breaking. These dance forms are one of the four foundational elements of hip-hop culture, intertwined with rap music, graffiti art, and DJing. Working in harmony, these elements created a revolutionary artistic movement, echoing the voices, stories, and experiences of marginalized communities, thus providing a platform for self-expression, communication, and identity.

At its core, hip-hop dance is a physical articulation of hip-hop music’s rhythmic and lyrical components. Its improvisational nature, unique movements, and powerful expressions of individuality and freedom characterise it. In its pure form, it is a freestyle dance. The original moves of hip hop are based on social and party dances that people did together on jams, in clubs or simply in the streets. Often these moves were inspired by cartoons (e.g. the Bart Simpson, Roger Rabbit), fashion (e.g. the Gucci, Reebok or Fila) or movie stars (e.g. the Steve Martin).

Hip-hop dance is not just about the moves; it’s about the attitude, the swag, and often about the story it tells. It’s an eclectic blend of various dance forms and cultures, allowing for various movements and expressions. With its global reach and universal appeal, it has transcended boundaries, enabling individuals from diverse backgrounds to connect and communicate through the universal language of dance. It has transformed streets into stages, providing a canvas for dancers to paint their stories, struggles, and triumphs, fostering unity and mutual respect among different communities.

How to learn hip-hop dance?

Learning hip-hop dance offers unparalleled flexibility, allowing enthusiasts to adapt and tailor their learning experiences to suit their preferences, lifestyles, and learning paces. Whether you prefer the structured environment of a dance studio or the comfort and convenience of your living room, the journey of mastering hip-hop dance is accessible to all. With many resources available online and offline, anyone can immerse themselves in the rhythmic symphony of hip-hop.

Find yourself a teacher or mentor

The best way to learn hip hop dance is with capable teachers. No matter if that is in a studio or within a crew. Getting input from a trusted source and feedback on your progress also guarantees fast progress. Certainly, having a knowledgeable mentor provides a structured learning environment and fosters a space for constructive critique, honing your skills more effectively. Furthermore, a teacher’s experience and insights can help navigate the intricacies of hip-hop dance, ensuring a deeper, more nuanced understanding of each movement and its cultural context and enriching your overall dance experience.

Learning to dance hip hop online

Learning hip-hop dance at home, leveraging the vast resources available on the internet, is a viable option for those who don’t have good teachers at hand. The online world is brimming with tutorials, workshops, and lessons that can guide you step by step on your journey through hip-hop dance. This method not only allows for flexible scheduling, catering to your pace and routine but also offers many styles and techniques to choose from, diversifying your learning experience. However, it demands discipline, self-motivation, and a discerning eye to select quality content, ensuring that the essence and authenticity of the dance form are preserved and respected.

There are full-fledged online courses out there, or you can pick and match tutorials from various online sources – mostly YouTube.

Take workshops

Opting to travel to various workshops led by esteemed teachers offers a balanced approach to learning the dance, allowing you to curate a personalized curriculum that reflects your interests and needs. This method combines structured, quality learning from reputable sources with the flexibility to choose specific styles, techniques, and teachers, enriching your repertoire with diverse insights and experiences. This tailored approach enables a deeper exploration of the dance form, allowing for a more nuanced understanding of its elements. It also allows connecting with like-minded individuals and communities, fostering a sense of belonging and shared passion within the dance community.

These workshops can always be an addition, even if you choose to learn in a studio or from online sources. Most big dance events offer workshops with their headline guests, so be sure to have your eyes open on those.

What to focus on when learning?

In my personal opinion, there are three parts you should focus on while learning hip hop dance. I will compare dance with language to make my point.

Moves and Steps are your Vocabulary

Consider each move and step as the vocabulary, the building blocks of your dance language. These elements are the expressions and words that you can use. Just as an extensive vocabulary can make conversations rich and expressive, learning a diverse range of moves and steps allows you to articulate your dance more vividly and precisely.

Grooves and Concepts are your Grammer

Next in line are grooves and concepts, the grammar of your dance language. They are the rules and structures that organize your vocabulary into coherent, meaningful “sentences”. Mastering the grammar of hip hop – understanding the foundational grooves and internalizing various dance concepts – enables you to create fluid, logical, and impactful dance sequences, that look like hip hop and something else. Just as grammar gives language its rhythm and flow, grooves and concepts lend your movements a natural, rhythmic coherence, allowing your dance to speak eloquently and fluidly.

Music is your topic

Lastly, the music is the topic of your conversation, the theme around which your dance language revolves. The context gives meaning to your vocabulary and grammar, shaping the mood, tone, and content of your dance narrative. An intimate understanding of the music allows your dance expressions to be in harmony with the song’s rhythm, melody, and emotion, making your dance conversation engaging, emotive, and in sync with the musical discourse.

So by understanding these three components (moves, grooves/concepts and the music) you will soon be able to speak freely in the language of hip hop.

What is the hip hop dance experience?

You wanna know what to expect – about the hip hop dance experience? Let me give you my two cents. You can anticipate a vibrant and welcoming experience, full of energy, passion, and creativity. On the other hand, this culture has its black sheep like every other scene. Meet the right people and everything is “Peace, Love, Unity and Having Fun” – the credo of hip hop culture. Meet the wrong ones and you will meet narrow-mindedness and bigotry. The hip hop scene is a smaller mirror of our complex society, you will find everything in there, that you encounter somewhere else. We just have better music and the better moves.

Joining the hip-hop community opens up a world of opportunities to connect with like-minded individuals, passionate about dance, music, and art. This community is a tapestry of people from different backgrounds, united by a common love for hip-hop, offering a supportive environment to grow, learn, and create. The camaraderie within this community is palpable, with experienced dancers and newcomers alike sharing knowledge, encouraging each other, and pushing the boundaries of what hip-hop dance can be. It’s a space where creativity flourishes, friendships are forged, and where each dancer contributes to the ever-evolving tapestry of hip-hop dance.

Learning the dance itself is not just about acquiring new moves; it’s about immersing yourself into the possibilities of expression within your physical and mental capabilities. It’s challenging and rewarding at the same time. It teaches you a lot about yourself if you let it and are open to reflect and think about what it does to you. Learning hip-hop provides an avenue to explore and understand the multifaceted world of hip-hop, music and yourself. It’s a trip you should at least take once.

In case you are looking for reasons to get into Breakdance aka Breaking, you might want to check out a story I wrote for Red Bull: 10 Reasons why you should start to break.

Online Resources to help you learn

The following links are online classes and resources that I can recommend wholeheartedly. I either know the classes from first-hand experience or personally know the people who offer them.

• Hip Hop Moves List: this is a collection of steps I know. It’s free and will be free forever. When I have time, or somebody sponsors a coffee for an extra night shift, I try to add more to the list or find tutorials to add.
• B-Boy Dojo’s Mr. Wiggles Original Hip Hop & Party Rock: This is one of the best online classes if you want to learn original steps from one of the pioneers.
• Beyond The Moves: The BTM platform has a lot of of different training programmes for all levels.
• Steezy: Steezy.co is a mainstream-focused platform for dance classes. If you want to dig hardcore in your own style, go with BTM, but if you like choreography Steezy might be the place for you.

Books that can help you learn

• Dance Smart: I wrote this book to guide people on their journey with dance concepts, which can be used to create your freestyle dances or choreography. It might be too heavy for total beginners, but when you have a few moves down already, this will help you find your own way of creating dance.
• Performance Skills: Another one of my own, for those who are afraid of dancing in front of people or those who want to improve their stage presence.
• Oxford Handbook of Hip Hop Dance Studies: This one is a compendium of research around all topics hip hop dance. If you like to explore stuff from a scientific perspective, this books is for you.

The book links above are affiliate links and will take you to Amazon.

Der Beitrag Mastering the Groove: How to Learn Hip Hop Dance erschien zuerst auf FraGue Moser-Kindler | Artist, Author & Creative Advisor.