- 8:30am and I’m already yawning in Tisch?
- How did I even end up in Tisch? I hate it here.
- Anyway, I should probably get some coffee.
- Or should I wait a little longer to see if I can shake this tiredness?
- No, when does that ever even work?
- Yeah okay I’ll walk to the Rez to get an espresso.
- I know I get jittery if I drink it
- But I’m going to have it anyway.
- Great, now I have my coffee.
- Wait, but now I have to hold it while I’m walking.
- Okay, now it’s spilling everywhere.
- Was this actually worth it?
- Let me take a sip.
- WOW okay it’s way too hot.
- Of course it’s hot, I just got this like 5 minutes ago.
- Wait, oh no I think I burned my tongue.
- This coffee burned my tongue.
- I guess this just goes to show that the things you love the most will hurt you the most.
- Burned my tongue, but still going to drink it.
- Okay, time to head to my 9:30.
- I think I’ll survive with this coffee in my hand.
- NO, actually.
- With this coffee I am UNSTOPPABLE.
- I will destroy this 9:30 class
- Even though it’s just a lecture and I’m sitting there taking notes for 50 minutes
- It’s okay, I’ll just slowly sip on this coffee to wake up.
- Okay, class time now.
- I love this coffee but I just don’t like HOLDING IT in class.
- Plus these desks are so small
- Bromfield-Pearson, why are your desks SO SMALL
- And SLANTED!
- So even if I put my coffee on it, it’s just gonna slide down and probably get all over me.
- Because I’m a mess.
- A freaking mess.
- But that’s okay.
- I need this coffee to make it through the day.
- 9:40am.
- Oh my goodness.
- I thought for sure that I’ve been in class for 30 minutes already.
- Okay, just have to be patient.
- Oh wait, I’m jittery all of a sudden.
- Oh no.
- My heart feels like it’s beating really fast now.
- Yeah that’s definitely not math doing that to me.
- Oh my goodness.
- This espresso is killing me.
- I cannot sit still at all.
- And it’s only 9:42 am.
- Oh my gosh. I still have to sit in this chair for another 40 minutes.
- I can definitely do this.
- No I can’t. My leg is shaking like crazy.
- Okay I need to leave class to take a walk or something.
- Need to walk off this energy.
- How long can I stay out of class and get away with it?
- Let’s see.
- Okay I’m back.
- Wow that was only like 2 minutes.
- It felt like at least 5.
- Oh well.
- Can’t wait to get out of this class.
- Wait.
- If I’m so jittery after a few sips why am I still drinking it?’
- Once again, the thing I love the most has turned around to hurt me.
- Wow.
- This coffee is giving me so much energy though.
- I feel like I could write forever.
- TRIANGLE
- COMPUTER
- WORDS
- Wow I know so many words!!
- This caffeine is doing crazy things to me, oh my goodness.
- Am I going to crash later?
- Maybe.
- Should I stop drinking this coffee?
- Probably.
- Am I going to get again tomorrow?
- Yes, of course.
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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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