Everyone has a specific thing they want to do in the future. I want to be on ESPN someday talking about sports with someone else that has the passion about it like I do. Sports intrigue me because of the competitiveness that is involved. My favorite sports to watch are basketball and football. I love just having conversations with people about those two sports. People that I look up to within this field are Stuart Scott and Stephen A. Smith. They are African Americans who are very prominent people within the sports broadcasting field. Being African American and being successful is rare. Not a lot of people who are my complexion are on ESPN and successful. I look up to Stephen A. Smith because of the amount of passion that he shows when he talks about sports. When I watch him on ESPN I can tell he enjoys his job and loves sports. When he is on television everything he says does not seem like it's scripted at all. Certain topics will get him mad so he expresses that emotion with speaking very eloquently. Then Stuart Scott, who is no longer alive, is someone else I looked up to. When he was on ESPN his catchphrases were well remembered when he talked about sports, as was the passion he showed when he talked about various sports or people. He was always showing excitement doing his job. I want to be someone like them but more than them. I want to bring myself to those jobs by working hard while at the University of Clafin. I would absolutely try my hardest to be on ESPN. No one in their right mind can stop me to reach that goal. The work that I am going to put into to someday be on ESPN and making money will be achieved through the work ethic that I have. I know it is not easy to achieve but as long as I put my mind to it I know for a fact I can achieve it. Being a student at Claflin I must ask everyone in the Mass Communication department to help me to achieve that goal. I need to make connections with more people at my school. In order to be that man on ESPN that I want to be it all start at the University of Claflin.
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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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