As we all know at this point in the NFL season, the Chicago Bears aren't very good. Going by record, they are the fourth worst team in all of the NFL. Now yes as fans, this is awful. A 3-10 record is nothing but embarrassing. Yes I know it could be worse but it is still bad. Now looking back into the Bears past seasons, its been bad for a long time. Since 1947, in the last 70 seasons, the Bears have 2 championships. They have only appeared in three other title games. That’s five championship/Super Bowl appearances in seven decades. Of course from a fans perspective, especially in a city that just got over a 108 year drought, this is not all that bad. It could be a lot worse. In more recent years, the Bears have made a habit of being an average to way below average team. Now being an average/below average team for multiple years really starts to hurt an organization. It is clear that they are missing a few key pieces, a star player or two to push them over the top. In the bears case, they never got that push to the top. They played their average games with their average teams. Now they're not even the average team they used to be. They slowly fell to the bottom of the league, but this is a good thing. Once a team hits the bottom there is only one place to go, up. Being in the position the Bears are in means losing is good. Losing more games means better draft picks. Better draft picks gives them the chance to get the players they need to spark the rise back to the top. Better draft picks means they wont be stuck picking mediocre wide receivers or line backers like they have made a habit of. They now have the chance to get rid of overpaid players who clearly don't have what it takes with this current team. Being bad gives the Bears the chance to rebuild. It gives them the chance to start fresh, starting with a new coach and maybe a new front office. They can get rid of the players who wont be able tp help the team in the long run. They have the chance to accumulate draft picks to bring in young stars from college who have the potential to turn it around for the Bears. Yes, I know this is a long process but at this point with the record the Bears have managed to produce not only this year but in the last 5 years, there is not much else they can do. We all know a process like this works, we just saw the end product with the cubs. The process works and in my opinion it is what the Bears need to do. This is why the Bears should keep losing. Being a fan, you never want your team to lose, but losing will only help the Bears begin the process of rebuilding the team.
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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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