My whole life, I’ve been a western rider. I ride western on all sorts of horses. A few years into my riding career, I made the switch to being an english rider. At that point, I became an all-arounder and I LOVE it. The only thing is that, I’m more of a western rider. I grew up riding in a barn that was more western than english, which explains a lot about me and my riding styles and habits. When I moved off to college, everything changed for me. I absolutely love my school. However, just because I love it, doesn’t mean that there’s nothing I would change about it. Like I said before, I’m an all-arounder, but I think I’m a better western rider than english rider. As it turns out, I’m going to a school that has a really big english program, a decent-sized dressage program, and no western program. Before you jump to conclusions and think that there’s zero western here, there is! My school has an extremely small IHSA western team. We compete at high levels in our region. We work just as hard as everyone else. Since we’re a small team, it’s hard for us to keep up with the hustle and bustle of the english barn. Sometimes I have issues realizing that I’m in a barn filled with english riders. Sometimes I feel like I’m being judged because of the fact that I’m a western rider, that I’m not following the “norm.” You know what, I don’t care. I’m proud of my accomplishments in the western world and I’m proud to be a western rider. Don’t let people tell you what you can and can’t do. It’s your life. Now take the reins and ride.
Recommended for you
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
Trending Topics
Trending Stories
Best of Sports
![Cristina Yang and Meredith Grey in scrubs sit against a wall, smiling and enjoying a break.]()
![Woman in field with a red heart-shaped balloon under a colorful sky.]()
