- All right, time to start this shift. 8:00 a.m. to 4:30 p.m. I can do this.
- How is it only 10:03 a.m.? I have been here for 16 hours.
- There are already too many people here. Why are you all here already? Don’t you have jobs or families?
- This store isn’t nearly as festive as it should be.
- There are too many Santas in this store. Tone it down, please.
- Yes, ma’am! I will defiantly check in the back for a clearance product that we sold out of in March. I need to check my phone again, anyway.
- Why won’t anyone smile back at me? Aren’t people supposed to be jolly during the holidays?
- I am thirsty.
- I am only asking how you are because my boss is staring at me. I really don’t have time to do your Christmas shopping.
- And now, I am Christmas shopping. Guess my work can wait.
- Time to take a break! How have I only been here for two hours?
- No, I want to go on break! I don’t want to go to the backroom again!
- Again, Christmas shopping for a family that isn’t mine.
- I wish my mom would buy me those boots. Kelly is a lucky girl.
- Okay! I am now safe in the break room!
- Why don’t we get any treats? I want a holiday cookie.
- Maybe I will make cookies on my lunch. But there isn’t an oven in here. Can you make cookies in the microwave?
- There is a tray of old vegetables in here. Guess that’s our holiday treat.
- That break was too short. I am not ready to venture back out.
- Wow, I think the entire state of Kentucky is in this store right now.
- I haven’t walked this many steps all year. This store seems so much bigger with all these people.
- If I have to check on a toy in the backroom one more time, I will vomit.
- If no store in a 30 mile radius has this blender, why do you think we do? Why wouldn’t you call before?
- I am so thirsty.
- Thank you for knocking this entire rack of clothes over three minutes before my lunch. I promise this is exactly what I wanted to be doing.
- I need a break and a snack.
- I am so very tired.
- LUNCH!
- I only have another two hours, 17 minutes and 45 seconds left for this shift. I can do this.
- And a kid just threw up on the floor. I can’t do this.
- Manager, I know you’re upset that I haven’t made any progress. But there are three piles of things to sort and put back on the floor, and I am only one person.
- I have never been this thirty.
- Old people are the best.
- Except when they yell at you for your pants. Then they are the worst.
- 30 minutes left!
- Another Christmas list! WHY? I can’t read your writing!
- Okay, I’m done, time to clock out.
- Only to be stopped by three customers. Great!
- Freedom! Hooray!
- But I will be back tomorrow morning.
- And I am still thirsty.
- We really do need an oven in the break room.
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This article has not been reviewed by Odyssey HQ and solely reflects the ideas and opinions of the creator.
StableDiffusion
The Illusion of Creativity
AI-generated music is often marketed as “artistic” or “educational.” But what does it really teach?
- That style can be replicated without understanding.
- That emotion can be simulated without feeling.
- That effort can be bypassed with a prompt.
For young creators, this sets a dangerous precedent. Why learn to play guitar when an algorithm can do it faster? Why study harmony when AI can generate chord progressions in seconds? The risk isn’t just laziness — it’s the loss of depth, discipline, and the tactile joy of creation.
I have listened to several AI-generated music covers. My initial reaction was one of considerable impressiveness, particularly regarding the reimagining of classic pop hits in diverse genres with novel arrangements. Here is one good example a-ha — Take On Me
However, after engaging with several such Ai generated song covers, a sense of emotional detachment emerged, attributable to the perceived absence of human artistry and genuine sentiment, resulting in a technically flawless yet ultimately soulless auditory experience.
Copyright in Crisis
What does the copyright law say about AI generated music, especially in field of music covers. Who is liable for copyright in this case, AI developers, people who used AI to generate music or people who published it on music platforms?
Recent lawsuits show that the music industry is pushing back hard:
- Universal, Sony, and Warner sued AI music platforms Suno and Udio in 2024 for allegedly training their models on copyrighted songs without permission Ars Technica The Lyon Firm.
- They’re seeking up to $150,000 per infringed song, arguing that the AI outputs resemble famous tracks and voices (e.g., Mariah Carey, Michael Jackson).
- These lawsuits target the developers of the AI tools — but they raise broader questions:The legal gray area is training data. Courts haven’t yet ruled definitively on whether using copyrighted songs to train AI counts as infringement or fair use Sites at USC.
But who’s liable?
Role | Legal Risk | Why |
AI Developers | ✅ High | For training on copyrighted material without licenses. |
Users | ⚠️ Moderate | If they intentionally recreate protected works. |
Publishers/Platforms | ✅ High | For distributing infringing content. |
The grey area lies in training data. Courts haven’t yet ruled definitively on whether using copyrighted songs to train AI counts as infringement or fair use. Meanwhile, AI-generated works themselves aren’t eligible for copyright unless a human provides substantial creative input — leaving them in legal limbo.
The Educational Mirage
Some argue that AI music helps people learn genres, production styles, or vocal techniques. But this “education” often lacks context. It’s like learning to paint by watching a printer — technically impressive, but creatively hollow.
True musical education involves:
- Struggle and iteration: Learning through mistakes.
- Emotional connection: Expressing what words can’t.
- Cultural lineage: Understanding the roots of sound.
AI shortcuts bypass all of this. And in doing so, they risk flattening the rich terrain of human creativity into a sterile landscape of algorithmic mimicry.
Why This Fight Matters
This isn’t just about music. It’s about the future of art, storytelling, and human expression. If we allow machines to dominate creative spaces, we risk turning culture into content — optimized, monetized, and devoid of soul.
We must ask: Do we want a world where art is made by machines, or one where machines help humans make better art?
5 Key Takeaways
- AI-generated music blurs the line between innovation and erosion in the creative arts
- AI-generated music raises questions about copyright, culture, education, and artistic expression
- AI-generated music can replicate style without understanding, simulate emotion without feeling, and bypass effort with a prompt
- AI-generated music sets a dangerous precedent for young creators by potentially leading to a loss of depth, discipline, and joy of creation
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