During the NFL (National Football League) Draft the Dallas Cowboys chose to select Dak Prescott during round 4. The Cowboys needed a quarterback for the future because Tony Romo does not have that many more years to continue playing as well as being injury prone. With Romo being close to his 40s a back up quarterback will be good for the Cowboys in the near future. They learned their lesson for not having a back up quarterback last season which led to them being one of the worst teams. Romo was hurt the majority of all season which led to a record under .500. Getting Dak in the draft will give the Cowboys a young talented quarterback that can potentially start in the league or even be a substitute if Romo is hurt. During the preseason games Dak has played exceptionally well. His accuracy of passing to his wide receivers is sowing that he has potential to be a star in NFL in the near future. In just 3 preseason games he has accumulated 454 passing yards as well as completing his passes at a 78% mark. As well as that he has not yet thrown an interception during the preseason. Even though this is bot the regular season this just shows the possible potential he has in the NFL. Just recently Tony Romo got hurt in their last game that was played. With it being the preseason the Cowboys were not taking any chances and letting him sit out the rest of the game. That was a scare for them in the sense that their starting quarterback could be hurt before the actual season begins. So far he is alright but the team is trying to make sure he is 100% when week 1 begins. Prescott has playing out of his mind lately so he has gotten confidence from those games. The confidence can give him the bet ability to perform if the team calls his name when the regular season begins. Dak might be a rookie but he can accomplish more once he becomes the starter with the talent he has. Being a 4th round draft pick essentially he was a steal to be picked that late. It all depends on what happens to Romo if he plays or not during the regualr season.
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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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