I’ve been involved in music and tech for over 35 years. I’ve watched every “next big thing” arrive with fanfare and leave with casualties. This week’s casualty is anyone who followed influencer advice and installed OpenClaw because some guy with a ring light called it a “must-have for your workflow.”

On March 31st, that must-have became a wide-open door for North Korean hackers. You lose.

I’m not a guru. I don’t have a course to sell you, and I really don’t need your money. I’m just sick of watching people get screwed because they trusted the wrong person. Oh, and gurus.

Open Source Is Open. That’s All.

There’s a myth floating around that “open source” means safe, vetted, altruistic. It means none of those things. It means the code is visible. That’s all. You still have to verify it, and most of you don’t have the background to audit a thousand lines of JavaScript. Which is exactly why you shouldn’t be the first, or the fiftieth, to install some game-changing new tool.

Oh, and again, I’m not for closed source either. I have written about open standards, and I‘ve been burned by closed source like most of you, but I need to be honest: just because I like open source doesn’t mean I’m blind.

Here’s What Actually Happened

Most of you use Axios without knowing it. It’s a program that enables your apps to communicate with the internet (and many programs, not just Open Claw, install it automatically.) They pushed a “new version” that looked completely official and contained a Remote Access Trojan. A RAT.

OpenClaw is the current early-adoption darling, so it pulled in that poison immediately. If you installed or updated those tools, someone else may have the keys to your machine right now. And your business. And everything on it.

Influencers Aren’t Experts. They’re Salesmen. But you knew that.

Most of these people get paid for hype, not for being right. (I don’t like to paint with a broad brush, but sometimes the truth hurts.) They want you installing things first so they get the clicks and the commissions. And yes, you have noticed the “ad-free” socials are full of “ads”.

In this business, being first usually just means being the first victim.

Open source is genuinely useful. Should I mention again, I love Open Source, but not for security; for lifespan.

Open source is an ecosystem. One poisoned root and everything that grows from it is toxic.

What I Do

I don’t have a perfect solution. I have a 35-year habit that keeps me mostly out of trouble.

Don’t chase every patch. Don’t chase every update. If your setup works, leave it the hell alone. Let the early adopters be the crash-test dummies. This also applies to your DAW, plugins, etc.

I run a 72-hour rule on updates. Nothing new gets on my machines for three days. Most attacks like this one surface within 24 hours. Boring is safe.

The Bottom Line

Never trust, always verify isn’t a bumper sticker philosophy. Own the process. Nobody else will.

If an influencer calls something magical, remember who’s doing the trick and who’s standing in the audience. They walked away with the views. You walked away with the RAT.

If You’re Technical, Read This

Check your project folders for node_modules/plain-crypto-js.

If it’s there, you’re compromised. Don’t clean it. Wipe the machine, rotate every password and API key you own, and start from scratch. There are no shortcuts on this one. Yeah it sucks.

If you don’t know what that means, it means they’re broke. Bankrupt. The company that made Kontakt, Massive, Reaktor, and half the sample libraries sitting on your hard drive is going under.

And if you’ve been paying attention, you already know what this means for you.

Remember when I said you don’t own shit? This is exhibit A.

What Happens When the Company Dies

Here’s the difference between hardware and software when a company goes belly up.

I bought an Alesis ADAT in 1993. Alesis went bankrupt in 2001. The ADAT still works. Still records. Still plays back. Still syncs with the other two I’ve got in the rack. Alesis being dead doesn’t matter. The machine doesn’t need permission from a server to function.

Now let’s talk about your Native Instruments libraries.

You’ve got Kontakt. You’ve got thousands of dollars worth of sample libraries that run in Kontakt. Maybe you’ve got Massive, Reaktor, Komplete, whatever. You paid for it. You “own” it.

Except you don’t.

When NI goes under completely, what happens to the authorization servers? What happens to the software that checks your license every time you open a session? What happens when there’s nobody left to maintain the DRM that keeps your “owned” software locked down?

Your hardware keeps working. Your software becomes a brick.

The iLok Problem, But Worse

At least with iLok, there’s a third party managing the DRM. If one company using iLok goes under, the rest keep working. Native Instruments managed their own authorization. Their own servers. Their own infrastructure.

When they shut down, that infrastructure goes with them.

Sure, maybe someone buys them. Maybe the assets get picked up by a bigger company who keeps the lights on for another few years. Maybe.

Or maybe they don’t. Maybe the new owner decides supporting legacy products isn’t profitable. Maybe they sunset everything older than two years and tell you to upgrade or get fucked.

This has happened before. It’ll happen again.

Gibson bought Cakewalk in 2013 and killed it in 2017. Tascam bought GigaStudio and ran it into the ground. MakeMusic just discontinued Finale after 35 years. These weren’t small companies. They weren’t fly-by-night operations. They were industry standards.

And they’re all dead now.

What NI Didn’t Do

You know what Native Instruments never did? Open-source anything.

Steinberg open-sourced VST. That was the right move. VST is the backbone of the plugin ecosystem, and making it open-source means it’ll outlive any one company.

But NI? Everything proprietary. Kontakt format is locked down. Their authorization systems are locked down. Their sample libraries only work with their software.

When NI goes under, all those libraries you paid for become dead weight on your hard drive.

The samples are still there. The software to play them won’t be.

Sound familiar? That’s because this is the exact same thing that happened with GigaSampler. Revolutionary format. Dead company. Thousands of dollars worth of libraries that don’t work anymore unless you want to spend weeks converting them and hoping the conversions don’t fuck up the keyswitches.

Hardware Doesn’t Need Permission to Work

I’ve got synths from the eighties and nineties. Roland JV-2080. Yamaha TG500. Roland U-220. All of them still work. The companies are still around, but it wouldn’t matter if they weren’t. The machines don’t phone home. They don’t check a license server. They don’t need an internet connection to function.

You turn them on, they work. That’s it.

That’s what ownership looks like.

Software ownership is a lie. You’re licensing access. And when the company that sold you that license disappears, so does your access.

Is It Time to Stop Relying on Software?

I’m not saying ditch your DAW and go back to tape. I’m not saying software is worthless.

I’m saying stop building your entire setup around proprietary formats controlled by companies that might not exist in five years.

Use open-source tools when you can. Use open formats. Use software that doesn’t require a company to stay in business for you to access your own work.

And when you do use proprietary software, know what you’re getting into. You’re not buying a tool. You’re renting access to it. And that access ends the moment the company decides it’s not profitable anymore.

What’s Next

I’m going to start a series on open-source tools and open formats. How to use them. Why they matter. What you can do now to make sure your work outlives the companies that sold you the software.

Because here’s the thing: your work should outlive you. It sure as hell should outlive a software company’s quarterly earnings report.

Native Instruments going under is just the latest proof that you don’t own what you think you do.

Hardware survives bankruptcy. Software doesn’t.

Plan accordingly.

Here’s the thing nobody wants to tell you: it’s not getting better.

Every day you spend tweaking that snare sound, retuning that vocal line, or debating whether the bridge needs another guitar layer is a day you’re not learning what actually matters. You’re not getting feedback from real listeners. You’re not building momentum. You’re not moving forward. You’re just polishing something that fewer and fewer people will care about the longer you wait.

I've seen this same pattern repeat itself with musicians who have real talent, real songs, real potential. One more take. One more mix revision. One more plugin that'll finally make it sound "professional." Meanwhile, someone else with half the skill and twice the balls releases three albums in the same timeframe and builds an actual audience.

Most musicians don’t fail because they lack talent. They fail because they never release anything.

Perfectionism Isn’t Craft

Let me be clear: perfectionism and high standards are not the same thing.

High standards push you to make something excellent. Perfectionism stops you from making anything at all. High standards improve your output. Perfectionism delays it indefinitely. High standards focus on the work. Perfectionism focuses on protecting yourself from criticism.

Look at Steely Dan. Those guys were actual perfectionists. They’d do hundreds of takes, hire the best session players, spend months on a single song. But here’s the difference: they finished and released albums. Their perfectionism served the work. It didn’t prevent the work from existing.

You tweaking that snare sound for the sixth month straight? That’s not serving the work. That’s fear wearing a craftsman’s costume.

And here’s something nobody talks about: your demos probably sounded better than your “final” mixes. That first or second take where you were just feeling it out, before you started overthinking every decision, that’s usually where the magic lives. By take 500 you’ve surgically removed every trace of spontaneity, every human imperfection that made it interesting in the first place.

Real Feedback Beats YouTube Videos

You can watch another tutorial on compression, study another video about vocal chains, research another forum thread about the perfect snare sound. Or you can release something and find out what actually matters. Only one of these approaches gives you real information.

When you release, you discover what actually matters. You learn what parts people remember, what lyrics they quote back to you, what moments make them rewind. You also learn what doesn’t work, what’s confusing, what’s self-indulgent. This information is gold, and you cannot get it any other way.

No amount of thinking replicates the value of real-world response.

There’s also a profound psychological shift that comes from completion instead of endless refinement. Finishing something, even imperfectly, generates confidence. It proves you can follow through. Each release makes the next one easier.

Meanwhile, the perfectionist is still on verse two of song one, convinced that once they nail this one specific thing, everything will click into place. It won’t. What clicks into place is releasing twelve songs over two years and learning from each one what works and what doesn’t.

Next week: How to get real feedback on your music in the digital age, even if you're not a gigging artist.

Momentum Dissolves Resistance

Small wins reduce resistance. The first song is the hardest. But once you finish and release one, the second one feels less daunting. Once you’ve put out three or four, it becomes part of your rhythm.

Finishing one song completely teaches you more than having ten songs stuck at 80%. When you actually complete something, you learn the whole process. You make decisions about arrangement, mixing, mastering, release. You see what works and what doesn’t.

The musician with ten unfinished songs has fifty ideas about what might work. The musician who finished and released those ten songs has ten data points about what actually works. That’s not even close to the same thing.

Here’s what kills that motion: overthinking. Analyzing every decision to death. Comparing your rough mix to someone else’s mastered commercial release. Restarting from scratch every time you hit a rough patch instead of pushing through to completion.

The solution isn’t to think harder. It’s to move faster. Finish the song. Put it out. Start the next one.

People Connect With Humanity, Not Perfection

Listen to old Motown records. You can hear chairs squeaking, breaths, fingers sliding on strings. Listen to early rock and roll, half of it sounds like it was recorded in a tin can. But it works because there’s life in it.

You strip that out when you pitch-correct every note, quantize every hit, and polish every rough edge until the thing sounds like it was made by a machine. Which, by the way, is exactly what AI-generated music sounds like. Perfect. Duplicative. Forgettable.

People don’t connect with perfection. They connect with humanity. The imperfections are often what make music memorable. The slightly off timing that creates feel. The vocal strain that conveys emotion. The weird production choice that makes a song distinctive.

What Actually Works

The musicians who build actual careers aren’t the ones who waited until everything was perfect. They’re the ones who released things before they felt ready, learned from the response, and iterated based on real feedback instead of bedroom theories.

Dick Grove used to tell us (and I’m paraphrasing): “If you want to create your opus, go to college and spend four years on it. If you want to make it in the real world, just write it.” We wrote a big band chart every week at his school. You get over perfectionism real quick when you’re on that kind of schedule. You learn that done and decent beats perfect and never.

There’s an old saying: perfect is the enemy of good. Turns out it’s true. The good song you release today will do more for your career than the perfect song you’ll finish never.

Your career doesn’t get built on one perfect album. It gets built on a body of work that shows growth, consistency, and an actual point of view. Six solid releases over two years is infinitely more valuable than one “perfect” release that took you five years and still isn’t out.

Here’s the reality: what you have right now is probably good enough to release. Not tomorrow. Not when you’re ready. Not when you’ve got that one piece of gear or learned that one technique. Today. With what you have. As you are.

Stop tweaking that snare. Stop retuning that vocal. Stop mixing the same eight bars you’ve mixed forty times already. Finish the song. Put it out. Start the next one.

The music you release imperfectly today will teach you how to make better music tomorrow. That’s not settling. That’s how you actually get good.

Nobody’s waiting for your perfect song. But they might listen to the real one you release this week.

Want the complete framework for actually finishing and releasing your music? I've written a full guide that walks through exactly how to break the perfectionism cycle, including specific steps for recording, mixing, and releasing without overthinking, plus the common traps that kill progress and how to avoid them. Get the full guide here for free.

Not access to new plugins. Not access to updates. Access to your own fucking work.

That mix you did in 2019? The one the client still plays at conferences? It’s got four plugins from this company baked into the master bus. Stop paying, and that session opens with holes in it. Silent spots where the compressor used to be. A reverb that’s now just empty space. Your work, held ransom.

This is where we are now. And it happened so gradually that most people didn’t notice until they were in too deep to get out.

The Lie of Ownership

Look, I don’t remember when I bought my first software synth. Could’ve been ‘98, could’ve been 2001. What I do remember is that it came on a CD-ROM, I installed it, and it worked.

Does it still work? Probably not. The 32-bit to 64-bit transition killed half the plugins I owned. Apple’s been playing musical chairs with operating systems for two decades. Maybe I could’ve updated some of them. Maybe I did and they’re still sitting there in a folder somewhere.

The point is, if I needed to open those old sessions now, it would be a fucking archaeological dig. And I have done that. I bought Cakewalk Sonar back when it was Cakewalk 1 for DOS. Yeah, I’m that old. I’ve still got .wrk projects from 1990 sitting on a hard drive.

Do they work? Sort of. Gibson bought the company in 2013, shut it down in 2017. Just killed it. Everybody who’d been using it for years got fucked. BandLab picked up the pieces later and made it free, which saved some people’s asses, but that was charity. You can’t plan around charity.

Or how about GigaSampler? Remember that? Revolutionary when it came out. Streaming samples from disk instead of loading everything into RAM. Changed how people worked with sample libraries. I used it for years.

Then Tascam bought GigaStudio, ran it into the ground, and killed it in 2008. All those .gig libraries? Dead format. You can convert some of them if you want to spend days doing it and hope the conversions don’t fuck up the keyswitches and velocity layers. Most people just moved on and lost access to thousands of dollars worth of sample libraries.

The samples still exist on your hard drive. The software to play them doesn’t. That’s the difference between owning something and licensing access to it.

Finale: A Masterclass in Planned Obsolescence

Here’s another one. Finale. I owned Finale 1.0 for Windows back in 1989 or so. I know that software like the back of my hand. Twenty-five years of muscle memory. Twenty-five years of scores and arrangements and charts.

It still works. For now.

But Apple’s going to break it with the next OS update. Windows 12 will probably kill it too. And MakeMusic already announced they’re discontinuing it entirely. After 35 years, they’re just done. No more updates. No more support. Good luck.

So now what? All those Finale files. Decades of work. They open now, but for how long? And even if I wanted to move to Dorico or Sibelius, the import process is a nightmare. Formatting breaks. Articulations don’t translate. It’s not a migration, it’s a rebuild.

This is what happens when your data is locked in proprietary formats controlled by a single company. When that company decides you’re not profitable anymore, your work becomes a museum piece.

You want to avoid this? Use open-source software. Or at least open-source formats. Something that doesn’t require a company to stay in business for you to access your own shit.

Remember when MP3 was a licensed format? Software developers had to pay Fraunhofer for every copy they sold. That cost got passed to you. Then the patents expired in 2017, and suddenly MP3 was free. But for 20 years, you were paying a tax on a codec because someone owned the math.

That’s the game. They own the format, they own your work. And when they’re done with it, so are you.

Waves: The Blueprint for Extortion

Here’s how it works. You buy a Waves plugin in 2015. Pay $200, maybe $300. It’s yours, right? Says so right on the site. “Buy now.”

Works great for three years. Then you get the notice: your version is now “unsupported.”

Unsupported doesn’t mean broken. Means Waves isn’t updating it anymore. Means the next time Apple or Microsoft changes something in the OS, your $300 plugin might stop working. Might not. But Waves isn’t fixing it if it does.

Want the supported version? That’s $240. For software you already bought. And not just once. Every fucking year, there’s a new version, and your old version slides into “unsupported” status like clockwork.

This isn’t a bug. It’s the business model.

But wait, there’s more. Your Waves licenses live on a USB dongle or are tied to a specific computer. That dongle dies? That computer craps out? You’re fucked. Now you get to contact Waves customer support and beg them to “allow” you access to the software you already paid for.

And here’s the best part: they’ll likely tell you to buy a second license. Not replace the one you own. Buy another one. Because the license you purchased apparently came with the condition that it only works as long as the physical hardware it’s tied to doesn’t fail.

Hardware fails. That’s what hardware does. But Waves built a business model around treating hardware failure as a reason to charge you again.

I watched them do this to people for a decade before the backlash got loud enough that they had to walk some of it back. But the damage was done. They proved you could sell someone software and then charge them again for the privilege of continuing to use it. Every other company took notes.

Now it’s subscriptions all the way down, and at least that’s honest. You’re not buying shit. You’re renting until you can’t afford to rent anymore.

Your Back Catalog Is a Ticking Time Bomb

Used to be, your old projects were an asset. A catalog you could revisit, remix, repurpose. I’ve got 2-inch master tapes from the eighties that still play. Scratchy, sure. But they play.

Your 2019 Pro Tools session? That’s not an asset. That’s a liability spreadsheet.

Open it up. Count how many third-party plugins are in there. Now count how many of those companies you’re still paying. Now imagine you stop paying. What happens?

You get a session that opens with errors. Missing plugins. Silent channels. Effects that don’t exist anymore because you’re not subscribed. And sure, you can replace them. Find alternatives. Rebuild the chain. But it’s not the same session anymore, is it? It’s archaeology. You’re reconstructing something that used to work perfectly fine until you stopped feeding the meter.

Multiply that across 200 sessions. Ten years of work. Every project a minefield of potential missing pieces.

This is the deal now. Your catalog isn’t yours. It’s a dependency chain, and every link costs money forever.

When the Company Dies, Your Work Dies With It

And all of this assumes the companies stay in business. That the authentication servers stay online. That nobody decides your product line isn’t profitable enough to maintain.

I’ve seen companies go under. Seen them get acquired and gutted. Seen product lines abandoned mid-cycle because the new owner didn’t give a shit about legacy users.

Your software doesn’t have a warranty. It has a lifespan, and that lifespan is tied to the financial health of a company you don’t control and can’t predict.

iLok is the perfect example. Thousands of plugins. Hundreds of companies. All using the same third-party DRM system. If iLok has a bad quarter, if they get bought by the wrong company, if they just decide the music software business isn’t worth it anymore, what happens?

You’ve got a hard drive full of sessions you can’t open. Plugins you paid for that won’t authorize. No offline verification that lasts. No physical backup. Just faith that a DRM company you’ve never met stays solvent and continues to give a shit about musicians.

I bought an Alesis ADAT in 1993. The company went bankrupt in 2001. The ADAT still records. Still plays back. Still syncs with the other two I’ve got in the rack.

Try that with a plugin that requires server authentication.

The Fantasy You’re Paying For

And here’s the thing that pisses me off most: You’re not even using half this shit.

You’ve got a subscription to Slate Everything Bundle or Plugin Alliance or whatever. Forty-seven compressor plugins. You use two. One’s the stock Pro Tools compressor. The other is some 1176 emulation you’ve had forever and actually understand.

But you keep paying $30 a month because what if you need that obscure British console emulation? What if there’s a session where only that one specific plate reverb will work?

You won’t. There won’t be.

This is Gear Acquisition Syndrome with a monthly billing cycle. The same brain chemistry that makes you buy another guitar you don’t need, except now it’s frictionless. Just keeps charging your card. You don’t even feel it until you look at your statement and realize you’ve paid $2,000 this year for plugins you opened twice.

Meanwhile, the compressor and EQ that came with your DAW? They’re fine. Maybe even good. Engineers made hit records with stock Logic plugins twenty years ago. Radiohead made Kid A with stock software. But we’ve been sold this idea that we need boutique emulations of hardware we’ve never touched to make records that sound like records made with gear we’ve never used.

It’s a con. A subscription con. And it works because we’re musicians, and musicians are suckers for the promise that the right tool will unlock something we don’t have yet.

You’re Building on Sand

So what do you do?

You keep paying. Because you’re in too deep. Because your templates are built around these tools. Because your muscle memory knows these interfaces. Because going back and rebuilding everything with stock plugins or one-time purchases sounds like archaeological work you don’t have time for.

Or you accept that your catalog has an expiration date. That at some point, you’ll stop paying, or the company will stop existing, and all those sessions will become historical artifacts instead of working projects.

There’s no good answer here. The industry moved from selling tools to selling access, and they did it because access is more profitable. You pay forever or you lose everything. That’s the deal.

I’ve got hardware from the eighties and nineties that still works. Powers on. Does exactly what it did when I bought it.

I’ve got software from five years ago that won’t open without errors.

That’s where we are. And it’s not getting better.

Let’s skip the philosophy and get specific.

Everyone wants to talk about whether AI can replicate “the human soul” or “genuine artistic expression.” That’s a nice conversation to have over coffee. But it’s not the conversation we need to be having.

The real question is: who’s losing work to AI right now? Not in some hypothetical future. Right now.

Here’s the list nobody wants to make.

The Middle Class of Music

There’s a whole ecosystem of working musicians you’ve never heard of. They’re not superstars. They’re not playing arenas. They’re making a living, or they were.

Production music libraries. You know that background track playing during a YouTube video? That upbeat corporate montage music? That “inspiring” bed under a commercial? Someone used to get paid to write that. Past tense.

AI can generate 50 variations of “uplifting corporate background music” in the time it takes to make coffee. The clients don’t care who wrote it. They never did. They cared that it was cheap, fast, and didn’t have complicated licensing.

Yeah, some sync agents and music supervisors are putting up resistance right now. They’re drawing lines, making statements about only working with human-created music. Good for them. I mean that sincerely.

But the cat’s out of the bag. It’s already starting. Many songwriters, even top-tier, well-known ones, are using AI for “ideas.” They’re not admitting it publicly, but it’s happening. A chord progression here, a melodic suggestion there. They’ll polish it, humanize it, make it their own. But the AI is in the room.

Once that door opens, it doesn’t close.

Commercial jingles and advertising music. Same story. Ad agencies need music that fits a brief and doesn’t cost much. AI does that now. No negotiations, no revisions, no personalities to manage.

Background scores for content. Podcasts, corporate videos, indie films, online courses. All of that needed music. A lot of composers made decent money filling that need. That market is evaporating.

These weren’t glamorous gigs. But they were real income. Mortgage payments. Health insurance. The kind of work that let musicians keep making music.

Session Musicians (Sort Of)

The top session players are still working. If you’re the guy who can nail a part in one take, who brings something special to the track, who has relationships with producers, you’re probably fine. For now.

But here’s what changed even before AI showed up: remote collaboration killed the need for local session players. Used to be, if you needed a string section in Nashville, you hired Nashville players. Now? You hire someone in Prague and get the files overnight.

AI just accelerates that trend. Why hire anyone when the software can generate a convincing string arrangement in minutes?

The session musician as it used to exist is already over. AI is just making it more obvious.

The Regional and Local Scene

Cover bands and wedding bands. Look, DJs already gutted this market years ago. Why pay five musicians when one guy with a laptop can keep people dancing?

But now that laptop doesn’t even need a guy. AI DJ services are already a thing. They read the room, adjust the vibe, take requests. Cheaper than a DJ, infinitely cheaper than a band.

Teaching gigs. YouTube already gutted this market. Why pay for lessons when you can watch thousands of free tutorials?

But now? AI tutors and lesson software are taking it further. They give you unlimited practice time, instant feedback, and a structured curriculum for $10 a month. They don’t cancel. They don’t show up late. They don’t have bad days.

The counterargument is that people want human interaction, mentorship, the personal touch. Sure. Some do. But most people just want to learn enough guitar to play “Wonderwall” at a party. An app can do that.

What This Actually Means

These aren’t theoretical scenarios. This is happening right now.

I’m not saying every one of these jobs disappears overnight. I’m saying the volume of work is shrinking, the rates are dropping, and the musicians who depended on this income are scrambling to figure out what’s next.

“Adapt” sounds easy when it’s not your rent check on the line.

The carriage makers adapted when cars came along. Some retrained, some found new industries, some thrived. But a lot of them just lost their livelihood and had to start over. That’s the part nobody likes to talk about.

No Solutions Here

I don’t have a tidy answer for how to fix this. I don’t have a roadmap for pivoting your career or a motivational speech about resilience.

What I do have is this: you can’t prepare for what you won’t acknowledge.

The first step is being honest about what’s at risk. Not the superstars. Not the artists with devoted fanbases. The working musicians in the middle. The ones nobody thinks about until they’re gone.

That’s the list nobody wants to make.

But somebody needed to.

Most non-musicians don’t care about who made the music. There, I said it.

I know that stings. I know it goes against everything we want to believe about our craft. But watch someone using Spotify. They put on a playlist. Whatever comes on comes on. They either listen or press next.

They’re not checking liner notes. They’re not following artist journeys. They’re picking a vibe and letting the algorithm feed them.

And while there are artists they care about (sure, they’ll buy tickets to see Taylor or Kendrick if they roll through town), mostly they don’t. And if you live outside the major metros where touring bands actually come around? Even less so.

You know what bothers me most about the “AI can never replace real artists” argument? It’s not that it’s wrong. It’s that it’s only true for about 1% of the music that gets made and consumed.

The Genie Is Out of the Bottle

At 65, I wish things would return to the good old days. I really do.

But I’ve been around long enough to know how this story ends. I’ve watched technology disrupt music over and over, and every single time, the same pattern plays out.

I remember real studios. You know, the kind with one compressor per room and actual tape machines. You made decisions because you had to commit. You couldn’t undo. You couldn’t have seventeen plugins on every track because there weren’t seventeen of anything.

Then bedroom producers came along with their DAWs and their cracked software, and the old guard said, “This isn’t real music production.” Guess what? The world didn’t care. Good enough won.

Then streaming came along and crushed the album format, and everyone said, “People will never stop buying music they love.” Guess what? They did. Convenience won.

Now AI is here, and everyone’s saying, “But people want the human connection! They want the story!”

Do they though? Do they really?

The Story Argument Only Works for Superstars

Look, I get it. People fall in love with stories. They follow artists through their journey: the early struggles, the breakout moment, the evolution. That’s real.

But here’s what that argument conveniently ignores: that only applies to a fraction of the music people actually listen to.

Think about the last ten songs that played on your Spotify. How many of those artists could you name? How many of their “stories” do you know? How many do you actually care about?

For most people, music is functional. It’s the thing that makes the workout less boring. It’s the thing that fills the silence on the commute. It’s the thing playing in the background at the coffee shop while they’re trying to finish an email.

Nobody at that coffee shop is thinking, “Wow, I really connect with the artist’s journey on this lo-fi hip-hop beat.” They just don’t want to hear silence.

And that’s where AI is coming for the industry. Not for the artists who spent years playing dive bars and building a following one small venue at a time. Not for the ones with superfans who follow every Instagram story.

AI is coming for everything else. And “everything else” is most of the music that exists.

The Pattern: Convenience Always Wins

Here’s what I’ve learned watching technology eat the music business for forty-plus years: the mass market doesn’t optimize for quality. It optimizes for convenience and “good enough.”

MP3s sounded like garbage compared to CDs. Didn’t matter. People wanted 1,000 songs in their pocket, not perfect fidelity.

Early streaming was compressed to hell. Didn’t matter. People wanted access to everything without having to own anything.

Yeah, there are hi-fi streaming services now. Deezer, Tidal, Spotify’s adding a premium tier for better quality. You know who uses them? Audiophiles. Gearheads. People like us. The mass market is perfectly happy with the standard compressed stream because it’s good enough and it’s easy.

AI-generated music is going to follow the exact same trajectory.

It doesn’t have to be as good as a real artist pouring their soul into a track. It just has to be good enough to fill the playlist slot. Good enough to pass as background music. Good enough that the average listener doesn’t notice or care.

And here’s the kicker: it’s getting better fast. What sounded like obvious robot trash a year ago is starting to sound... fine. Not great. But fine.

Fine is all it needs to be.

The Geographic Reality Nobody Mentions

If you live in New York, LA, Nashville, or Austin, you’re in a bubble. You can see live music seven nights a week. You can catch touring acts. You can stumble into a club and discover your new favorite artist.

But most people don’t live in those cities.

Most people live in places where live music means a cover band at the brewery on Friday nights. Where “touring artists” means the county fair books a washed-up 80s act once a year. Where the connection between listener and artist was already tenuous at best.

In those places, the “story” of the artist was never part of the equation. Music was something that came through the speakers. That’s it.

AI doesn’t change that dynamic. It just makes it cheaper and easier to fill those speakers.

Your Future Will Involve AI

I’m not saying this to be a pessimist. Well, in this piece maybe I am. But I have hope that this, like all disruptive technologies, will just be another shift. The carriage makers didn’t disappear when Ford fired up the assembly line. They adapted, retrained, found new work. Some thrived. The industry changed, but people figured it out.

I’m saying this because I’ve lived through enough industry shifts to recognize the pattern.

The genie is out of the bottle. You can’t put it back. You can’t wish it away. You can’t regulate it into submission.

The question isn’t whether AI will take over parts of the music industry. It’s already happening. The question is how big those parts will be, and how fast.

If you lived in the big cities through the 90s, you remember cartage companies. They hauled gear to sessions. They made a shit ton of money doing it. Now? Home studios killed that business.

What about music copyists? Mostly gone since computer engraving took over. I remember many a night creating swindles1 and racing to get them reproduced by 11pm when the downbeat was at 9am the next morning. Had to copy the parts myself, by hand. No need anymore. Just print them from the computer.

Those jobs didn’t disappear because the work wasn’t valuable. They disappeared because technology made them obsolete.

Will AI replace the superstar artists with devoted fanbases and compelling stories? Probably not. Those people have something that’s hard to replicate: a genuine human connection with an audience that’s invested in them as people, not just content generators.

But will AI replace the thousands of working musicians cranking out production music, stock tracks, commercial jingles, background scores, and playlist filler?

Yeah. It will.

And the uncomfortable truth is: most listeners won’t notice. Because most listeners never knew those people existed in the first place.

What This Means

I don’t have a tidy conclusion for you. I don’t have a plan to save the music industry or protect musician jobs or turn back the clock.

What I do have is four decades of watching technology disrupt everything I thought was sacred about this business, and learning that resistance is pointless. Adaptation is the only option.

The romantic notion that “people will always want real human artists” is comforting. It’s also incomplete. People will always want real human artists for the 1% of music they actually care about.

For the other 99%? They just want something that sounds good enough while they’re folding laundry.

AI can do that. And it will.

But knowing it’s possible and actually setting it up are two different things.

So here are 10 prompts you can copy, paste, and customize right now. Pick one. Test it. Schedule it if it works. Don’t try to do all ten at once or you’ll never check the results and the whole thing becomes pointless.

Start with the one that would save you the most time.

1. Daily Music Industry News Digest

What it does: Keeps you informed about what other musicians are struggling with and what’s changing in the industry without losing hours in Reddit threads.

Simple Prompt:

Search for the top 20 questions musicians asked yesterday about Spotify playlisting and music distribution. What problems are coming up repeatedly? What's changing? Summarize in 3 short paragraphs I can read in 2 minutes.

Customize it: Change “Spotify playlisting and music distribution” to whatever you actually care about: sync licensing, TikTok marketing, Bandcamp strategies, whatever.

2. Upcoming Music Events & Opportunities

What it does: Finds submission deadlines and opportunities 45 days out so you can plan instead of scrambling at the last minute.

Simple Prompt:

Search for sync licensing opportunities and music library submission deadlines happening 45 days from today. Focus on indie-friendly opportunities that don't require exclusive deals. Include submission links and deadlines. Format as a simple list.

Customize it: Change “sync licensing opportunities” to playlist submissions, music conferences, grant deadlines, or whatever opportunities you’re looking for. Adjust the 45-day window to whatever planning timeline makes sense for you.

3. Social Media Content Calendar Generator

What it does: Gives you content ideas two weeks in advance so you’re not staring at Instagram wondering what to post.

Simple Prompt:

Search for music-related holidays or events happening 14 days from today. For each one, give me one content idea I could post that connects to my story as an indie musician. Keep it practical, not cheesy.

Customize it: Adjust the 14-day window. Add your genre or specific angle. For example: “connects to my story as an indie folk musician” or “relates to my experience as a session player.”

4. Gear Deal Tracker

What it does: Tracks actual deals on gear you’re watching so you stop paying full price or missing limited-time sales.

Simple Prompt:

Search for legitimate deals on audio plugins posted in the last 24 hours. Skip subscription services. Focus on one-time purchase deals with actual discounts (not permanent "sales"). Include price, regular cost, and expiration date.

Customize it: Replace “audio plugins” with whatever you’re actually shopping for: interfaces, microphones, MIDI controllers, studio monitors. Get specific if you want: “deals on Focusrite interfaces” or “sales on Neumann microphones.”

5. Sync Licensing Opportunity Scanner

What it does: Finds music libraries and sync opportunities that are actually accepting submissions in your genre right now.

Simple Prompt:

Search for music libraries currently accepting submissions in the indie rock/folk genre. Include submission requirements, whether they're exclusive or non-exclusive, and contact information. Skip libraries that require publisher representation.

Customize it: Change the genre to match your music. Add other filters like “under 30-second instrumentals” or “vocal tracks only” if that’s what you have ready to submit.

6. Release Strategy Researcher

What it does: Shows you what’s actually working for indie artists right now, not what worked three years ago.

Simple Prompt:

Search for case studies or stories about indie artists who released music in the last 30 days. What platforms did they use? What marketing worked? Summarize 3 examples in 2-3 sentences each.

Customize it: Add your genre for more relevant examples. Specify budget level: “indie artists with small budgets” or “bedroom producers.” Focus on specific platforms if you want: “indie artists using Bandcamp” or “musicians who went TikTok-first.”

7. Playlist Pitch Tracker

What it does: Finds playlist curators who are actually accepting submissions right now instead of ones who closed submissions six months ago.

Simple Prompt:

Search for active Spotify playlist curators in the indie folk genre who are currently accepting submissions. Include playlist name, follower count, and how to submit. Update weekly.

Customize it: Change the genre. Adjust how often it updates based on how actively you’re pitching. Add filters like “playlists with 10,000+ followers” or “curators who respond to DMs.”

8. Music Marketing Trend Spotter

What it does: Separates real tactics from “buy my course” bullshit by showing you what’s actually getting results.

Simple Prompt:

Search for music marketing tactics that indie artists tried in the last 2 weeks. What worked? What failed? Focus on small-budget strategies. Summarize in 3 paragraphs with specific examples.

Customize it: Focus on specific platforms: “TikTok marketing tactics” or “Instagram Reels strategies.” Add your situation: “artists with no budget” or “musicians with day jobs.”

9. Session Work Opportunities

What it does: Finds paid gigs without wading through “great exposure” offers.

Simple Prompt:

Search for paid remote session work for guitar players posted in the last 48 hours. Skip "exposure" gigs. Include pay rate if listed, project description, and contact info. Format as a simple list.

Customize it: Change the instrument. Add your specialty: “jazz guitar” or “fingerstyle acoustic.” Set minimum rates if you want: “paying at least $100 per track.”

10. Administrative Task Reminder

What it does: Nags you to do the boring maintenance work you always forget until something breaks.

Simple Prompt:

Remind me every Monday at 9am to: backup project files, check streaming analytics, review social media performance from last week, update website if needed, and follow up on any pending collaborations.

Customize it: Add or remove tasks based on what you actually need to track. Change the day and time. Make it bi-weekly if weekly feels like overkill.

How to Actually Use These

1. Pick one prompt. Just one.

2. Copy it into ChatGPT or whatever AI tool you’re using.

3. Run it manually a few times. See what you get.

4. Adjust it until the output is actually useful.

5. Then schedule it: “Please schedule this as a task that runs daily at 7am” (or weekly, or whatever).

Don’t set up all ten at once. You won’t check them. They’ll pile up. You’ll ignore them.

Start with the one that would save you the most time right now. If it works after a week, add another one.

The goal isn’t to automate everything. The goal is to stop wasting time on repetitive research so you can spend more time making music.

Which one are you setting up first?

But here’s the thing nobody talks about: AI is really fucking good at the boring administrative work that eats your day. The research. The tracking. The organizational bullshit that has to get done but doesn’t require your creative brain.

You shouldn’t let AI make your music. But you should absolutely let it do your homework.

Why AI Sucks at Music

AI doesn’t understand intention. It doesn’t know why a song should build tension in the bridge or why a certain chord progression hits emotionally. It’s pattern-matching based on millions of songs it’s analyzed, and the result is technically competent but creatively dead.

I’ve heard AI-generated tracks. They sound fine. They sound like background music for a commercial. They sound like something you’d hear in an elevator and forget immediately.

That’s not music. That’s audio wallpaper.

If you’re a musician, your job is to make something that matters. Something that connects. Something that only you could make because it came from your experience and your perspective and your particular combination of influences and fuck-ups.

AI can’t do that. It can only approximate what’s already been done.

So don’t use it for that.

Why AI Doesn’t Suck at Everything Else

But tracking gear deals? Searching for sync opportunities? Monitoring submission deadlines? Generating a list of playlist curators who are actually accepting submissions right now?

That’s not creative work. That’s research. And AI is great at research.

You’re not asking it to be original. You’re asking it to scan the internet for specific information, filter out the noise, and give you something actionable. That’s what it was built to do.

And if you set it up right, it does it automatically while you’re sleeping or making music or doing literally anything else.

What AI Tasks Actually Look Like

Here’s the deal: ChatGPT and other AI tools now let you schedule recurring tasks. You write a prompt once, test it until it works, then schedule it to run daily or weekly.

It’s like setting a Google Alert, except the AI actually processes the information instead of just dumping a list of links on you.

Here are ten tasks you can set up that actually help:

Daily Music Industry News Digest

Search for the top 20 questions asked yesterday about music distribution, sync licensing, Spotify playlisting, or music marketing and identify patterns. What are other musicians struggling with right now? What’s changing that might affect how I release my next track or where I should focus my energy?

This keeps you informed without losing two hours in Reddit threads where the same arguments repeat forever.

Upcoming Music Events & Opportunities

Search for music submission deadlines, sync opportunities, playlist submission windows, and music conferences happening 30-60 days from today that I could actually submit to or attend. Filter out the major label stuff I don’t qualify for. Give me realistic opportunities with links and dates so I can plan my calendar.

You stop missing deadlines because you forgot to check that library’s website or didn’t see the Instagram post about submissions closing.

Social Media Content Calendar Generator

Search for music holidays, artist anniversaries, and industry events happening 14 days from now. For each one, give me 3 angles I could use for my own content: something I could share about my process, a post that connects to my story, or a behind-the-scenes moment that makes sense for that day.

You still have to create and post, but at least you’re not staring at Instagram at 9pm wondering what the hell to say.

Gear Deal Tracker

Search for legitimate deals on the specific gear I’m watching: plugins I’ve had my eye on, interfaces in my price range, microphones I’ve been considering. Filter out subscription services and fake “sales” that never end. Show me real discounts with expiration dates.

You stop paying full price for that compressor plugin that goes on sale every six weeks. You stop missing the one day a year that interface you want actually drops to a price you can afford.

Sync Licensing Opportunity Scanner

Search for music libraries that are accepting submissions in my genre, TV shows and films in production that need music like mine, and production companies posting briefs I could actually fulfill. Skip the ones that require exclusive publishing deals or major label representation.

This helps you find places to submit your music without paying for databases that might be six months out of date. You’re building a list of real opportunities, not just hoping someone discovers you.

Release Strategy Researcher

Search for case studies of indie artists in my genre who successfully released music in the last 30 days. What platforms did they prioritize? What marketing actually worked for them? What did they try that failed? Give me the honest takeaways I can learn from.

You’re learning from what’s working right now for artists in your situation, not what worked for someone with a label budget three years ago.

Playlist Pitch Tracker

Search for active Spotify playlist curators in my genre who are currently accepting submissions. Give me their contact info, playlist sizes, follower counts, and submission requirements. Update this weekly because curators open and close submissions constantly.

This beats spending hours on SubmitHub or DMing curators who stopped accepting music four months ago. You get a current list of people who might actually listen to your track.

Music Marketing Trend Spotter

Search for what’s actually working in music marketing right now for indie artists. Not guru promises or “buy my course” bullshit. What are artists with small budgets doing that’s getting them real results? What tactics are people trying that are failing?

You separate real strategies from noise. You find out what’s worth your limited time and money, and what’s just someone trying to sell you something.

Work Opportunities

Search for remote session work, collaboration requests, and “musicians wanted” posts from the last 48 hours that match my instrument and skill level. Filter for gigs that actually pay. Skip the “great exposure” offers and rev-share fantasies.

You find paid work without scrolling through dozens of posts from people who think your time is worthless because you’re a musician.

Administrative Task Reminder

Weekly reminder to handle the business stuff I always forget: update my streaming stats, check how my music is performing in those sync libraries, review which social posts actually got engagement, backup my project files before my hard drive dies, update tour dates on my website, check for copyright issues, follow up on collaboration offers I haven’t responded to yet.

The boring maintenance that keeps your music career functional but gets buried under the creative work you’d rather be doing.

Want the actual prompts you can copy and paste? I’ve put together 10 ready-to-use AI task prompts for musicians. Grab them here: https://e88.me/jlJX3

How to Actually Use These

1. Pick one prompt. Just one.

2. Copy it into ChatGPT or whatever AI tool you’re using.

3. Run it manually a few times. See what you get.

4. Adjust it until the output is actually useful.

5. Then schedule it: “Please schedule this as a task that runs daily at 7am” (or weekly, or whatever).

Don’t set up all ten at once. You won’t check them. They’ll pile up. You’ll ignore them.

Start with the one that would save you the most time right now. If it works after a week, add another one.

Want to Level This Up?

Once you’re comfortable with basic AI tasks, you can connect them to automation tools like n8n, Zapier, or Make. Instead of just getting notifications, you can have results automatically sent to Google Docs, added to spreadsheets, or dropped into your calendar.

For example: your gear deal tracker could auto-populate a price-sorted spreadsheet. Your sync opportunities could feed directly into a tagged database.

It takes more setup, but it’s not complicated. I’ll write a separate article walking through it if there’s interest.

For now, start simple. Get one task running. Then we can talk about making it completely hands-off.

What This Isn’t

This isn’t AI making your creative decisions. This isn’t AI writing your songs or producing your tracks or pretending to be you.

This is AI doing the research and organizational grunt work that doesn’t require your talent or your perspective. The stuff that takes time but not creativity.

You’re still the musician. The AI is just handling the administrative bullshit so you can spend more time making music.

The Real Question

Do you want to spend three hours today manually tracking sync opportunities and gear deals and submission deadlines?

Or do you want to spend three hours making music while the AI does that work for you?

AI sucks at making music.

But it doesn’t suck at making your life easier so you can focus on what actually matters.

Set up one task. See if it saves you time. If it does, set up another.

And then get back to your actual job: making something that only you can make.

Which of these tasks would save you the most time? Or are you already using AI for something I didn't mention?

I can think of two gigs that destroyed my ego so completely I’m still learning from them. Both happened around 1983. Both taught me the same lesson: thinking you’re great doesn’t make you great.

Jazz Band 101

I was at Pierce College in LA, sports medicine major, needed an elective. I’d been playing guitar since I was seven. By 1983, I was good. Or at least I thought I was. So I signed up for Jazz Band 101.

First day was auditions. I watched the current band play. They were solid, but I wasn’t worried. I could read chord charts. This would be easy.

Then they called me up.

What I thought were chord charts weren’t chord charts. They were rhythm changes. Knowing what I know now, it was standard shit. Common 32-bar jazz progression derived from “I Got Rhythm.” AABA form. I-vi-ii-V sequences. Circle of fifths in the bridge. There was a basic melody written out.

I knew something about reading, but I couldn’t sight read really.

I’d heard the other people play it during the audition, so I figured my ears could fake it. They couldn’t. I froze. Completely froze. Just stood there while the rhythm section vamped waiting for me to start.

I didn’t get in.

The Zappa Cover Band Audition

Same year, maybe a few months later. I auditioned for a Frank Zappa cover band. I’d jammed with Zappa in ‘78. This should be easy, right?

I drove my 1964 Studebaker Super Lark to the audition. Wish to hell I still had that car. Less than 100 ever made. Didn’t know that at the time. I pulled into the driveway to turn around, and backed up into a car. No damage, but when I walked in carrying my guitar and amp, my hands were shaking. Couldn’t get them to stop.

I met the drummer and keyboard player. Started setting up my gear. My fingers felt disconnected from my brain, like they belonged to someone else.

Then the keyboard player brought over a music stand and placed the first chart in front of me.

Note city. Every single note written out. Zappa’s music, transcribed.

I screwed it up. Completely. He brought over a “simpler” piece. I screwed that up too.

I don’t remember if I left on my own or if they politely told me I wasn’t the guy. Either way, I was gone pretty quick.

What I Learned

You can be pretty damn good at your niche and still be worthless outside of it. Just because you like something doesn’t mean you can play it.

And learn to read.

I know. You non-readers out there, especially guitarists, you’ve got your reasons. “Reading kills your feel.” “I play by ear.” “Tab is enough.”

Fine. Enjoy playing the same songs over and over. Unless you’re a savant, that’s where you’ll stay.

Me? I went to music school after those disasters. Met Dick Grove. Learned to read. Am I a better player now? Yeah, I am. But more importantly, I’m a better musician.

There’s a difference.

Merry Christmas. Go practice your sight-reading. And learn other styles, even if you aren’t great at them. It will open your eyes to things you didn’t know existed.

I’ll also write about why putting down your instrument can make you a better player. But that’s for another day.

Look, I get it. I’ve been there more times than I care to admit. My plugin folder is a digital junkyard of impulse purchases and “limited time” deals that seemed absolutely essential at 2 AM.

You’re working on a mix. The drums sound flat. The vocals need... something. You know what you want to hear, but you can’t quite get there with what you’ve got. So you open another tab. Just to see what’s out there. Just to check.

Three hours later, you’ve watched seventeen YouTube videos comparing vintage console emulations, you’re convinced your entire mix has been sabotaged by inferior EQ curves, and you’re one click away from dropping $200 on a plugin bundle that promises to solve all your problems.

This is Pluginitis.

It’s the musician’s version of thinking a new pair of running shoes will make you faster. Spoiler alert: they won’t. Your legs will.

The Logic vs. Emotion Cage Match

Here’s what’s happening in your head when that “Add to Cart” button starts looking real good.

Your Logic Brain—the prefrontal cortex, if you want to get technical—knows the truth. It knows you already have four compressors that do basically the same thing. It knows the problem isn’t the plugin; it’s that you haven’t learned to really use the ones you have.

But then there’s your Emotion Brain—the limbic system, that impulsive little bastard—and it’s screaming in your ear. “I’m stuck! I’m frustrated! This new saturator will fix everything! Look, it’s 40% off!”

Guess which one usually wins when you’re tired, stressed, or creatively blocked?

The impulse to buy isn’t about the plugin. It’s about escaping the discomfort of the work itself. Clicking “Buy Now” feels like progress. Sitting with a muddy mix and actually solving it? That’s hard.

The Triggers Are Everywhere

We’re not living in some neutral creative bubble. We’re swimming in a digital ocean specifically designed to make us want things we don’t need.

The Comparison Trigger: You see another producer’s plugin collection. Holy shit, they have everything. Suddenly your setup feels like amateur hour. You start making a mental shopping list.

The Frustration Trigger: The mix isn’t gelling. You’ve been staring at it for three hours. Instead of stepping away or trying a different approach, you go hunting for the magical plugin that will add that “professional sheen” you’re missing.

The FOMO Trigger: “SALE ENDS TONIGHT!” “70% OFF FOR THE NEXT 6 HOURS!” These emails are designed like surgical strikes on your Logic Brain. They create artificial urgency to bypass rational thought entirely.

And here’s the thing—sometimes you do need a new tool. I’m not saying never buy plugins. I’m saying most of the time, we’re buying solutions to problems we haven’t actually diagnosed yet.

How to Get Your Logic Brain Back in the Driver’s Seat

You can’t stop the marketing. But you can stop yourself from becoming its victim.

The 24-Hour Rule

This is nuclear-grade impulse control, and it works.

When you feel that hot rush to buy, stop. Put it in the cart if you need to. Then close the tab. Walk away. Go play your guitar. Make dinner. Watch a movie. Sleep on it.

Come back in 24 hours and ask yourself: “Will this plugin actually help me finish the song that’s sitting on my desk right now?” Not the imaginary perfect mix you’ll make someday. The actual project you’re working on today.

Nine times out of ten, the answer is no. The other one time, at least you’re buying it for the right reason.

Shop Your Own Plugin Folder

Before you buy anything, force yourself to spend 30 minutes with the version you already own.

Want a new reverb? Spend half an hour with the stock reverb in your DAW. Want a vintage compressor emulation? Dig into that free one you downloaded two years ago and never really learned.

You’ll be amazed how often this works. Not because your current plugins are magic, but because you finally spent time actually learning what they can do.

I learned this lesson the hard way at Dick Grove School of Music. Dick used to tell us, “Put your instrument down and you’ll become a better musician.” Sounds backwards, right? But what he meant was: expand your thinking. Don’t let your technical limitations define your musical vision. The same applies to plugins. Don’t let your collection define what you think is possible. Learn what you have first.

Unsubscribe Like Your Creativity Depends On It

If you were trying to quit drinking, you wouldn’t hang out in a bar. So why are you subscribed to seventeen plugin newsletters?

Be ruthless. If an email makes you feel like your setup is inadequate, unsubscribe. If a YouTube channel makes you covet gear instead of making music, stop watching.

Curate your digital environment the same way you’d curate your physical studio. Keep the things that help. Remove the things that distract.

A Reality Check From the Old Days

I’m old enough to remember real studios. There weren’t reverbs and compressors for every track, much less multiple compressors for every track. And yes, I’m a “boomer.”

You know how many plugins I have scanned in my DAW right now? 568.

You know how many I actually use? Maybe 20, okay 30, but you get the idea.

I’m waiting for the flames from the youngsters who need 128 tracks to comp vocals. Go ahead, I can take it.

But here’s the thing—those limitations forced you to make decisions. You had to commit. You couldn’t endlessly A/B between seventeen different compressor flavors because you only had a few compressors in the entire studio and you learned to make them work. You got good at mic placement because you couldn’t fix things with a magical “de-room” plugin later. As Rick Beato, or maybe someone else said, “before there was ProTools, there were pros.” That’s the truth. We used to say, you can’t fix it in the mix, and in reality, you still can’t… really.

I’m not saying those days were better. I love having options. But somewhere between “one hardware compressor per studio” and “568 plugins I’ll never use,” we crossed a line. The tools stopped serving the music and started becoming the music. Or worse, they became the excuse for why the music isn’t finished.

The Bottom Line

The plugin companies want you to believe the magic is in the code. It’s not. It’s in your ears.

I’ve heard incredible mixes made with stock plugins. I’ve heard terrible mixes made with $10,000 worth of boutique software. The difference wasn’t the tools. It was the person using them.

So close the browser. Open your DAW. And let’s actually finish that song.

The gear is just gear. You’re the musician.

Yes, this story broke months ago. No, it hasn’t gotten better. CapCut still has the same Terms of Service, still has the same meaningless clarification page, and millions of creators are still uploading their work to this IP-harvesting dumpster fire every day. If you’re one of them, this is your reminder to stop.

In late June 2025, CapCut—the video editing app owned by ByteDance—published a clarification page addressing “confusion” about its Terms of Service. The statement was reassuring: CapCut has “never claimed ownership of users’ work,” the company wrote, and would never “use or monetize your content or likeness without your permission.” https://www.capcut.com/resource/about-capcut-terms-of-service?from_page=landing_page&enter_from=a1.b1.c1.0

There’s one problem. The actual Terms of Service say something different.

I’m not a lawyer. I shouldn’t have to be one to use video editing software. But apparently that’s where we are now.

What You’re Actually Agreeing To (Since Nobody Reads These Things)

Buried in Section 10 of CapCut’s Terms of Service is a paragraph that every creator should read but nobody will. When you upload content to the platform—whether it’s a polished video, a rough draft, or audio clips—you grant CapCut:

“an unconditional, irrevocable, non-exclusive, royalty-free, fully transferable (including sub-licensable), perpetual, worldwide license to use, modify, adapt, reproduce, make derivative works of, display, publish, transmit, distribute and/or store your User Content.”

Let me translate the legalese:

• Unconditional: No strings attached. They don’t owe you anything before using your stuff however they want.

• Irrevocable: You can’t take this back. Delete your account? Too bad. Still theirs to use.

• Royalty-free: They’ll never pay you a cent. Not now. Not ever.

• Fully transferable (including sub-licensable): They can hand these rights to whoever they want—partners, advertisers, AI companies—who can then do whatever they want with it.

• Perpetual: Forever. As in, until the heat death of the universe.

• Worldwide: Every country. No exceptions.

But wait, there’s more. The Terms also grant CapCut “a royalty-free fully transferable (including sub-licensable), worldwide license to use your username, image and likeness to identify you as the source of any of your User Content, including for use in sponsored content.”

Your face. Your name. In their ads. Forever. For free. That’s what “sponsored content” means here.

“We Would Never Do That” Is Not a Contract

CapCut’s clarification page says this concern “would go against our commitment to empowering authentic creativity and supporting creators’ rights.”

Great. Put it in the contract then.

They didn’t. Because they don’t want to be legally bound by it. The clarification page is PR. It’s marketing. It’s the corporate equivalent of “trust me, bro.”

The Terms of Service is the contract. When you click “I Agree,” you’re agreeing to the legal text, not to what some blog post says the legal text really means in their hearts.

If ByteDance ever decides to exercise the full extent of its license—using your content for AI training, sublicensing it to third parties, slapping your face on a billboard—the clarification page is worth exactly nothing in court. Zero. It’s not part of the agreement.

Funny How They Never Mentioned AI

CapCut’s clarification never mentions artificial intelligence. Funny, that.

The legal text doesn’t need to say “AI training” explicitly—the rights it grants are exactly the ones needed to feed content into generative AI models. This isn’t a loophole. It’s the front door.

The license to “reproduce,” “adapt,” “modify,” and “make derivative works of” user content covers every technical process involved in machine learning. Training an AI model means reproducing content, creating derivative works, and adapting learned patterns. That’s literally what those words mean. Any IP lawyer would tell you the same.

The sublicensing clause makes it worse. CapCut can transfer these rights to unnamed “affiliates, agents, services providers, partners and other connected third parties.” Your content could be flowing to third-party AI companies right now. You’d never know. They don’t have to tell you.

The Terms even spell out how broad this is: “the rights granted in the preceding paragraphs of this Section include, but are not limited to, the right to reproduce sound recordings (and make mechanical reproductions of the musical works embodied in such sound recordings).”

“Include, but are not limited to.” Classic tech bullshit.

Musicians Get Screwed the Hardest

If you’re a musician or composer, there’s a special clause just for you. And it’s brutal.

The license isn’t just royalty-free to CapCut—the agreement explicitly waives payments that would normally flow through performing rights organizations. You know, the organizations that exist specifically to make sure musicians get paid.

The Terms state you’re granting CapCut “the right to use your User Content without the obligation to pay royalties to you or any third party, including, but not limited to, a sound recording copyright owner (e.g. a record label), a musical work copyright owner (e.g. a music publisher), a performing rights organization (e.g. ASCAP, BMI, SESAC, etc.).”

They literally named the organizations they won’t be paying.

And if you’re affiliated with a PRO? The Terms say you “must notify your PRO or CMO of the royalty-free license you grant through these Terms.”

So not only are you waiving your own royalties, you’re supposed to call up ASCAP and explain that you gave away the farm for a free video editor. Good luck with that conversation.

And here’s the real kicker: you don’t even have to be the one who uploads your music. Someone else can upload a video using your song—without your permission, illegally—and CapCut still gets the license. The Terms require uploaders to have the rights to what they upload, but if they don’t? CapCut’s covered. They point to the Terms, say “that user violated our agreement, not us,” and they still have your content on their servers under a license that came from someone who had no right to grant it.

The Terms even spell this out: “You must own your User Content or have obtained all necessary rights, licenses, and clearances of any and all elements of your User Content.” That’s a requirement for users. Not a protection for the people whose work gets uploaded without consent. CapCut gets to keep the license and point fingers at the uploader. You get to pound sand.

Your Creative Control? Gone.

The Terms include waivers of “moral rights”—the right to be credited, the right to object to butchering of your work, the right to approve how your creation is used. These protections exist in most countries specifically to protect creators.

CapCut’s Terms: “you waive any rights to prior inspection or approval of any marketing, advertising or promotional materials related to such User Content. You also waive (to the extent permitted by applicable law) any and all rights of privacy, publicity, or any other rights of a similar nature in connection with your User Content.”

And: “We, or authorised third parties, reserve the right to cut, crop, edit or refuse to upload your content in our or their sole discretion.”

They can chop up your video, remix it, alter it beyond recognition—and you’ll never see it, never approve it, never know it happened. “Sole discretion” means they don’t even have to pretend to care what you think.

Their Explanation Explains Nothing

CapCut says terms like “irrevocable” and “perpetual” exist “because once content (such as a template) is shared and used by others, we can’t undo every instance of reuse or remixing across the platform or internet.”

Okay. Fine. That explains template sharing. It does not explain:

• The right to use content in sponsored advertising

• The right to sublicense content to unnamed third parties

• The explicit waiver of PRO payments

• The right to use your likeness in promotional materials

• Rights that persist after you delete your account

The public statement presents a narrow, reasonable use case—template sharing—while the legal text claims rights that go wildly beyond anything required for a video editor to function.

If they only needed these rights for templates, they could have written terms that only apply to templates. They didn’t. Draw your own conclusions.

“Everyone Does It” Is a Terrible Defense

Yes, TikTok, Instagram, and YouTube have similar language. Adobe faced backlash over terms that worried users about AI training.

So what? That doesn’t make it okay. It means the whole industry has decided to help itself to your work and hopes you won’t notice.

There’s also a key difference: when you post to TikTok, you’re publishing. You know it’s public. When you save a draft to CapCut’s cloud, you might reasonably assume it’s private. Wrong. The Terms apply equally to both. Unpublished drafts, works-in-progress, raw footage—same license as finished, public work.

That draft you saved to the cloud while you figured out the edit? Fair game.

What You Should Probably Do

If you’re using CapCut for professional work—especially content under NDAs or client agreements—uploading to the platform grants ByteDance rights that may conflict with your obligations. You might already be in breach of contracts you’ve signed. Fun.

Things to consider:

1. Read the actual Terms. Not summaries. Not clarifications. Not this article. The legal text at capcut.com/clause/terms-of-service.

2. Cloud-synced drafts count. Same license as published content. If it touched their servers, it’s covered.

3. For sensitive work, use offline editors. DaVinci Resolve, Final Cut Pro, Premiere Pro don’t require your content to touch third-party servers.

4. If you’re a musician, talk to your PRO (Performing Rights Organization). The Terms create obligations the PRO will definitely want to know about.

5. Assume every right in the contract will be exercised. If it’s in there, someone at ByteDance thought they might want to use it someday. Plan accordingly.

The Bottom Line

CapCut is good software. It made video editing accessible to a lot of people who couldn’t afford Premiere. That part is genuinely valuable.

But here’s the trade you’re making: in exchange for a free or cheap editing tool, you grant a tech conglomerate perpetual, irrevocable, worldwide rights to your creative work. They can sublicense it to anyone. Use it for anything. Pay you nothing. Forever. And they wrote a nice FAQ explaining why you shouldn’t worry about any of that, while very carefully not putting any of those reassurances in the actual contract.

Intentions aren’t contracts. A blog post isn’t a legal document. The Terms of Service is the agreement. And the agreement says what it says.

Again: I’m not a lawyer. If this actually matters to your livelihood, talk to one. But the fact that using a video editor now requires legal consultation tells you everything you need to know about how broken this system is.

CapCut’s full Terms of Service: https://capcut.com/clause/terms-of-service. Section 10, “User-Generated Content.” Read it yourself. It’s not long. It’s just bad.

The Controversy: How Spotify’s “Bundle” Strategy Affects Royalties

The dispute centers on Spotify’s strategic decision in March 2024 to reclassify its Premium subscription tiers as “bundles” after adding 15 hours of monthly audiobook access. This seemingly minor administrative change carries major financial implications: under the 2022 Phonorecords IV settlement, bundled services can pay lower mechanical royalty rates to publishers and songwriters compared to standalone music subscription services.

The financial impact could be staggering. According to Billboard reports cited in court documents, this reclassification could cost songwriters nearly $150 million in just the first year following the change.

The Court’s Decision

Judge Torres sided with Spotify, ruling that “audiobook streaming is a product or service that is distinct from music streaming and has more than token value. Premium is, therefore, properly categorized as a Bundle.” The court found that Section 115 regulations (which govern compulsory licensing) were “unambiguous” and that “the only plausible application of the law supports Spotify’s position.”

The MLC’s Response and Concerns

The MLC, a non-profit organization designated by the US Copyright Office to ensure proper mechanical royalty payments, expressed serious concerns about the ruling. In their statement, they emphasized that the decision “does not align with the facts and legal principles central to this action” and are currently evaluating their right to appeal.

Why This Matters for Songwriters

This ruling represents a significant setback for songwriters’ compensation in the streaming era for several reasons:

1. It validates a strategy that effectively reduces songwriter royalties without any corresponding reduction in Spotify’s revenue

2. It sets a precedent that could encourage other streaming services to adopt similar “bundling” approaches

3. It highlights the vulnerability of songwriter royalties to corporate structuring decisions

Spotify’s Position

Spotify maintains that their bundling strategy is legitimate and beneficial for the industry. A company spokesperson stated, “Bundle offerings play a critical role in expanding the interest in paying for music and growing the pie for the music industry.” They emphasized that their recent deal with Universal Music Publishing Group (UMPG) demonstrates how direct licenses can create flexibility and additional benefits.

The Bigger Picture

This case underscores the ongoing tension between streaming platforms and music creators over fair compensation. It’s particularly noteworthy that while record labels can negotiate directly with streaming services, publishers and songwriters are bound by compulsory licensing rates – a disparity that the National Music Publishers Association has urged Congress to address.

The dismissal of this lawsuit with prejudice means the MLC cannot refile the same claims, though they retain the right to appeal. For songwriters and publishers, this ruling represents not just a financial setback but also raises questions about the effectiveness of current copyright law in protecting their interests in an evolving digital marketplace.

The music industry will be watching closely to see if this decision prompts legislative action or inspires other streaming services to adopt similar bundling strategies, potentially further impacting songwriter revenues in the years to come.

Roblox, the popular online platform that allows users to create and share games, has struck a deal with DistroKid, a leading independent music distribution service. This collaboration is set to allow DistroKid artists to upload their music directly to Roblox, making it available for use in games and experiences across the platform. However, one controversial aspect of the deal is that independent artists won’t be paid directly for their music being used on Roblox.

The Deal Explained

Under the terms of the deal, DistroKid’s artists can opt-in to have their music uploaded to Roblox. Once on the platform, the music can be used by game developers to enhance their games with original soundtracks and sound effects. While this exposure could potentially lead to new fans and opportunities for artists, the lack of direct compensation has raised concerns among the indie music community.

Pros of the Deal

• Increased Exposure: Roblox boasts millions of active users, primarily in the younger demographic, which presents a unique opportunity for artists to reach a new audience. For independent artists looking to grow their fanbase, this kind of exposure could be invaluable.

• Integration with a Growing Platform: Roblox has grown exponentially, especially during the pandemic, as more users turned to online entertainment. Being associated with such a rapidly expanding platform can be a significant advantage for artists.

• Potential for Viral Success: Music that resonates with Roblox’s user base could potentially go viral, leading to organic growth in streams on other platforms like Spotify or Apple Music. The viral nature of content on Roblox could drive substantial attention to certain tracks.

• Creative Use of Music: Developers on Roblox could use music in innovative ways within games, possibly leading to creative collaborations between artists and game developers. This could open up new avenues for artistic expression and partnership.

Cons of the Deal

• No Direct Payment: The most glaring downside is that independent artists won’t receive any money from the use of their music on Roblox. This has sparked criticism, as artists’ work is being utilized without direct financial compensation, which is particularly concerning for those who rely on income from streaming and licensing.

• Potential Devaluation of Music: Allowing music to be used without payment may set a concerning precedent where music is undervalued. This could contribute to the broader issue of artists struggling to monetize their work in the digital age.

• Limited Control Over Use: Artists may have little to no control over how their music is used within Roblox. This lack of oversight could lead to their work being associated with content they do not approve of, potentially impacting their brand or image.

• Uncertain Long-term Benefits: While the deal promises exposure, it’s unclear how beneficial this exposure will be in the long term. Without direct compensation, the tangible benefits of having music on Roblox may not outweigh the costs for some artists.

Conclusion

The Roblox and DistroKid deal is a double-edged sword for independent artists. On one hand, it offers unprecedented exposure and the possibility of reaching a vast, engaged audience. On the other hand, the lack of direct compensation is a significant drawback that could undermine the value of artists’ work.

For artists considering opting into this deal, it’s essential to weigh the potential for increased visibility against the lack of financial rewards. As the music industry continues to evolve, deals like this one highlight the ongoing challenges artists face in monetizing their work in the digital landscape. The decision to participate ultimately depends on individual priorities—whether the exposure and potential for future opportunities outweigh the immediate lack of payment.

After a prolonged legal battle, the estate of Ed Townsend, co-writer of Marvin Gaye’s “Let’s Get It On,” has formally ended their court battle with Ed Sheeran over their claims that Sheeran’s “Thinking Out Loud” copied the iconic 1970s R&B song.

Jury’s Verdict

In May, a jury in a federal court in Manhattan ruled in favor of Sheeran, rejecting the Townsend estate’s assertion that “Thinking Out Loud” copied the heart of Gaye’s hit. The Townsend estate initially filed an appeal, but last Wednesday, they withdrew their motion for appeal “with prejudice,” meaning the case can’t be refiled.

Why the Withdrawal?

Why did the Townsend estate withdraw their appeal? Sheeran’s lawyer, Ilene Farkas, theorizes that the plaintiffs recognized that an appeal would end up affirming the verdict, exposing them to legal fees and costs.

Continuation of the Debate

Despite this victory for Sheeran, the debate continues. During the trial, the Townsend family had pointed to a live performance where Sheeran segued from “Thinking Out Loud” to “Let’s Get It On” as evidence of plagiarism. Sheeran defended his position, saying that if he had copied elements from “Let’s Get It On,” it would be idiotic to perform both songs sequentially in a concert.

Yet Another Case Dismissed

In a similar vein, another case by Structured Asset Sales (SAS), which claims to own a portion of rights to “Let’s Get It On,” was also dismissed. The judge in this case noted the chord progression used in both songs was so common that it amounts to basic musical building blocks.

Bigger Questions About Copyright Infringement

This series of legal battles brings us to a bigger question: did Ed Sheeran really infringe copyright, and, importantly, do you think copying a rhythm or chord progression should be subject to copyright infringement? Current law mainly recognizes melody and lyrics as copyrightable elements. However, the lawsuits against Sheeran tried to push beyond this boundary by highlighting similarities in rhythm and chord progressions.

What’s Next?

As the debate continues, David Pullman of SAS, who plans to appeal the ruling in the other case, stated that the withdrawal of the Townsend family’s appeal will not affect SAS’s cases against “Thinking Out Loud.”

Share Your Thoughts

We’d love to hear your thoughts on this complex matter. Should we limit copyright to melody and lyrics as the law stands, or should chord progressions and rhythms be included in copyright protections? What do you think about the Sheeran case – is it a rightful victory, or should there have been a different outcome?

Do you think Ed Sheeran infringed copyright, and should copying a rhythm or chord progression be subject to an infringement? Let’s discuss!**

In this blog post, I want to summarize Tim’s original piece, while expanding on some implications and questions it raises. Be sure to read Tim’s full article for all the details. https://www.musicbusinessworldwide.com/universal-deezers-artist-centric-model-isnt-shocking/

Artist-Centric Royalties: Boosting the Big, Squeezing the Small

The core of Universal and Deezer’s proposed artist-centric model is simple: artists with over 500 monthly listeners on Deezer will have their per-stream royalties count double when dividing up the overall royalty pool each month. This means popular artists with over 500 monthly listeners will get a greater share of royalties.

Artists with under 500 monthly listeners on Deezer will see their share of royalties reduced, as their per-stream rates will not receive the same doubling effect.

While novel for the music streaming world, this approach clearly takes inspiration from creator monetization models used by video/social media platforms like YouTube, Facebook, and Twitter. These platforms only start paying creators once they surpass certain popularity thresholds - 10,000 YouTube subscribers, 100,000 video views, 10,000 Facebook followers and so on. Fall under the threshold, and you earn nothing.

Universal and Deezer’s proposal is milder. Less popular artists will still earn something - just at lower royalty rates compared to their more popular peers.
Instituting popularity thresholds for higher royalty rates is a notable shift. Let’s examine how it could play out in practice.

Winners and Losers: A Case Study on Spotify

To illustrate the potential impact, Tim considers the outcomes of applying this same 500 listener rule suddenly on a popular music streaming platform. The results are telling.
Based on Spotify’s own data, only around 873,000 artists on Spotify in 2022 had over 500 monthly listeners. These artists would stand to benefit from the artist-centric model, earning double the per-stream royalties of artists under 500 monthly listeners.
But here’s the catch: there were over 8 million artists on Spotify last year who had fewer than 500 monthly listeners.
Of that 8 million, approximately 2.57 million artists had between 10 and 500 monthly listeners. This middle tier of artists would see their share of royalties reduced under the artist-centric model compared to the top tier.
Just look at how monthly listeners on Spotify break down:
• 873,000 artists with over 500 monthly listeners (10%)
• 2.57 million artists with 10-500 monthly listeners (30%)
• 5.6 million artists with under 10 listeners (60%)

We can already see how this could create divergent incentives within the music industry.

Who Stands to Benefit? Follow the Money

Tim rightly points out that your perspective on the artist-centric model depends on your own commercial incentives.
Independent labels with rosters in the 500+ monthly listeners category may find it beneficial, as their artists are more likely to meet the threshold for higher per stream rates.

Distributors like TuneCore or DistroKid, whose business model is based on unlimited uploads for flat fees, could harm their customer base by reducing royalties for artists with less than 500 monthly listeners.

The debate separates DIY artists and signed acts. If you’re running TuneCore, you likely see squeezing the under-500 crowd as detrimental. If you’re running a label with 500+ listener acts, you may cheer moves to direct more royalties their way.

Of course, it’s unclear if streamers beyond Deezer would ever adopt this model. But if introduced on a platform like Spotify, the commercial impact would be even more dramatic.

Rethinking Thresholds at Scale

Here’s where things get interesting. Tim rightly asks: what if you ported over the same 500 listener rule to Spotify, a platform with a user base nearly 60X the size of Deezer’s?

Would the threshold have to change?

Some quick math:
• Deezer has 9.3 million subscribers
• Spotify has 220 million subscribers - 24X bigger than Deezer
• Spotify has 551 million total monthly active users - 59X bigger than Deezer

If you took the same 500 listener minimum and adjusted it to Spotify’s scale, the required minimum monthly listener count would be:
• 12,000 monthly listeners (24X bigger user base)
• 29,500 monthly listeners (59X bigger user base)

Now the proposal seems far more restrictive. Whereas 873,000 artists crossed 500 monthly listeners on Spotify last year, far fewer likely crossed 12,000 or 29,500 monthly listeners.

This could squeeze the royalty share of middle tier artists even further in the name of boosting the upper echelon.

The Slippery Slope

This brings us to concerns raised by companies like Believe Digital (owner of TuneCore) that fear where artist-centric models could lead in the future.
Namely, what stops streamers from raising the thresholds over time? 500 monthly listeners today could become 1000, 5000, 10,000 or more. With each increase, the total pool of artists benefiting shrinks.

We’ve seen this movie before on other user-generated platforms:
• YouTube originally allowed monetization at just 10,000 views. Now it’s 10,000 subscribers and 4,000 watch hours/year.
• Facebook’s original Live creator monetization threshold was just 100 followers, now it requires 600,000 minutes watched/month.

Platforms have a habit of raising the bar as they scale. There’s always more advertising money to chase with a smaller pool of content.
Deezer and Universal’s artist-centric model may be an innocuous starting point, but its future evolution—and how it could spread to other streamers - raises serious questions.

What’s at Stake? Diversity, Opportunity and Innovation

Stepping back, the two visions at odds here represent contrasting worldviews.

One values consolidation, prioritizing established hits and artists with commercial traction. For companies operating successfully in the mainstream music industry today, this makes sense. Value accrues to what’s already valuable.

The other worldview values diversity, opportunity, and plurality of voices. Allowing all artists to earn something creates an inclusive ecosystem. It recognizes that today’s 500 listener artist could be tomorrow’s stadium headliner - but only if they’re given a fair shot to develop from the start, not squeezed out by changing monetization thresholds.

This second viewpoint is why companies like Distrokid and TuneCore see cause for concern in artist-centric royalty models. It’s also why deejay organizations like Digital DJ Pool have spoken out about the risks of excluding niche genres if thresholds keep rising.

The Long Tail theory argues that the collective value of minor artists, niches and back catalogues can surpass the value of hits alone. Streaming royalties for indie artists may be small individually, but collectively they add up to millions in revenue.

Squeeze out middle tier and developing artists, and you lose much of this long tail value while cutting off the possibility of tomorrow’s stars rising organically from the grassroots.

The Question of Discovery

Tied to this debate over diversity and opportunity is the question of how streaming services help artists find an audience. If platforms won’t adequately promote developing talent, can they then justify redistributing royalties to established artists and away from indies and unknowns?

Platforms often point to playlist adds as career-making discovery opportunities for indie artists. But landing coveted spots on leading playlists requires building relationships with curators or paying promotors—privileges often out of reach for bedroom artists.

Pure algorithmic listening drives streams towards the most mainstream and already-popular tracks. This compounds the wage gap, as critical playlist plugs and promotions go to those seeing success.

Without meaningful, equal opportunities for audience discovery and growth, reducing royalties for smaller artists is a double blow - first limiting their potential reach, then limiting their earnings.

The Solution?

Rather than reducing royalties for indie artists, streaming services could consider alternative solutions like:
• Investing more in developing truly personalized recommendations to expose niche music instead of lean-back listening.
• Instituting caps on how many tracks by the same top artists can appear on flagship playlists to drive diversity.
• Featuring developing artists in popular playlists but geofencing their tracks to limit streams until they graduate to higher listener counts.
• Paying out bonuses when developing acts hit monthly listener milestones to reward fan growth.
• Weighting per-stream rates dynamically based on an artist’s recent listener growth to encourage rising independent artists.

The Takeaway

There are no perfect solutions. Streaming economics involves complex tradeoffs between creators, platforms, and rights holders.

But the questions surfaced by proposals like artist-centric royalties are critical ones for the industry’s future. Operations like DistroKid give power to the smallest of artists. Companies like majors and streamers naturally gravitate towards premium content.

Reconciling these opposing forces will require nuance, creativity, and an eye towards what’s best for music culture. Because a landscape without strange niches and surprise rising stars looks a lot less interesting.

What do you think?

How can we distribute streaming royalties in a way that’s fair to mainstream hits, indies and developing talent alike? I’d love to hear your thoughts in the comments below! ​

Let’s dive a bit deeper into this narrative, shall we? A recent expose by Svenska Dagbladet, a Swedish newspaper, sheds light on a rather concerning angle to this issue. It appears that certain crime networks are exploiting music streaming platforms, particularly Spotify, as a means to launder money. Sounds like something straight out of a movie, doesn’t it?

According to this report, these criminal groups with ties to various unsavory activities have been utilizing Spotify for money laundering for quite some time now. They allegedly funnel their ill-gotten gains into cryptocurrencies through secretive deals made on social platforms like Facebook. Once in possession of digital currency, these groups reportedly purchase fake streams for artists associated with crime gangs and pocket the resulting payouts. A source even mentioned, “Spotify has turned into their personal ATM”.

Now, let’s add another layer to this. A recent study from France’s Centre National de Musique highlights that a small but significant percentage of music streams are fraudulent. In fact, a considerable chunk of these streams seem to be centered around the hip-hop and rap genres, which have a dominant presence in the French music scene. But it’s worth noting that these fraudulent streams are still a minuscule portion of the total streams in these genres.

In response to these allegations, Spotify maintains that their vigilance in monitoring and controlling manipulated streams is top-notch. They assert that less than one percent of all streams on their platform have been tampered with, and they are continuously working to keep it that way. It seems Spotify is firmly standing its ground, emphasizing their ongoing efforts to tackle stream manipulation and ensuring a fair play in the streaming ecosystem.

This unfolding narrative has caught the attention of several bigwigs in the music industry, stirring up a serious conversation about the need to reevaluate streaming royalty payout models. The ultimate goal? To snuff out the incentives for streaming fraud and foster a healthier, more transparent industry.

As this story continues to evolve, we’d love to hear your thoughts on it. Do you think changing the royalty payout models would be a step in the right direction? And how do you envision a fraud-free future for the music streaming platforms? Share your insights and let’s get a lively discussion going!

The Plaintiff’s Position: AI as Sole Author

Dr. Stephen Thaler, the plaintiff, was unequivocal in representing to the Copyright Office and the court that his Creativity Machine created the artwork in question entirely on its own, without any human involvement. He named the AI system itself as the author on the copyright application.

In his view, the capabilities of AI have advanced to the point that computers can autonomously generate creative works, and he believes they should be recognized as authors under copyright law. He argues there is nothing in the Copyright Act that expressly requires human authorship, only referring to “original works of authorship” without defining “author.” He further notes the Act’s language covering works “now known or later developed,” indicating it should adapt to new technologies like AI.

Dr. Thaler maintains that if an AI system conceives of and generates a work entirely independently, evidencing true machine creativity, it has satisfied the requirements for authorship. Withholding copyright protection fails to properly incentivize further AI innovation. Machines do not require incentives, but their creators do. Copyright ownership would appropriately vest in the human inventors of the AI system, allowing them to benefit from its output.

By assuming away any human role in his specific case, Dr. Thaler brought a pure test of AI authorship. However, his absolutist position that AI systems can create wholly without human involvement may have undermined his legal argument before current conceptions of machine creativity.

The Defendant’s Position: Human Creativity Required

The U.S. Copyright Office denied Dr. Thaler’s application on the established grounds that copyright law protects only works of human authorship. Federal courts have upheld this human requirement for over a century of copyright jurisprudence. The District Court affirmed this denial, finding no basis in law to extend copyright to non-human creation.

The core rationale is that copyright exists to incentivize human innovation and creativity. This inherent human orientation traces back to the Intellectual Property Clause of the U.S. Constitution authorizing Congress to grant copyright for that purpose. Early copyright statutes expressly specified protections for “persons.”

Court decisions have continually reinforced the human authorship requirement. In the “monkey selfie” case, photos taken by a monkey were found ineligible for copyright since the animal lacked the capacity for original expression. The Supreme Court ruled that human creativity remains essential even when utilizing new technologies, as in photographs where the camera operates mechanically.

The Office recognizes copyright protection for AI-assisted works meeting the threshold of human authorship. But where the AI system purportedly conceives and executes the work autonomously without material human involvement, current law does not recognize machine creativity as sufficient for copyright.

However, the Copyright Office acknowledges the legal issues around AI creation remain open. The appropriate line between assisting and replacing human authors, and the need for legal incentives, must still be explored.

Can Machines Truly Create?

This fundamental question underlies the debate over AI copyright. Before awarding exclusive rights to machine-generated works, the system must exhibit genuine creativity and autonomy comparable to human capacities. There is as yet no consensus on whether today’s AI displays creativity or just very advanced statistical analysis and synthesis.

Creativity generally involves combining concepts or ideas in novel, unpredictable ways. Machines can churn out astronomically more combinations than any person, but does massive computational power equate to human-level imagination and ingenuity? Can machines have experiences from which to derive inspiration outside their training data?

State-of-the-art AI like DALL-E 2 and GPT-3 produce remarkably sophisticated and original-seeming content. But critics caution against anthropomorphizing machines and overstating current capabilities. AI may mimic creativity without achieving the essence of unconstrained thinking.

Nonetheless, rapid advances in areas like generative adversarial networks and reinforcement learning reveal the deficits of older, rules-based AI. Machines increasingly create, not just calculate.

Some theorists propose evaluating AI output itself, rather than the process, to determine if it meets originality standards for copyright. But this risks overlooking copying or patterns derivable from data. Assessing creativity objectively remains profoundly difficult, for both humans and AI.

The Level of Human Involvement

Barring full machine autonomy, determining the requisite degree of human influence emerges as a key issue in evaluating AI copyright claims. The line between author and assistant is often not entirely clear.

Does directly prompting an AI system with words or concepts involve enough human creativity to claim authorship? What if engineers fine-tune algorithms or select the training data? Perhaps iterative feedback loops between user and machine could jointly generate original works.

Courts have traditionally emphasized human judgment and discretion in directing the creative process, even using mechanical tools like cameras. But modern AI can produce sophisticated works with little overt human input during output generation.

Nonetheless, engineers make crucial design choices in constructing the AI architecture, training methodology, dataset characteristics, and objective functions. Users decide when to run the program, with what parameters, on what data or prompts. There is nearly always some material human role, even if the AI appears highly autonomous.

Complicating matters, many current systems utilize transfer learning from vast datasets that may contain copyrighted works. Disentangling human and machine contributions gets even murkier for rights assertions.

Some propose a “threshold of originality” above which works exhibiting sufficient human creativity could warrant copyright, though certifying this threshold poses difficulties. More fundamental questions around recognizing intelligence and creativity in machines remain open.

Potential Changes to Copyright Law

Within existing copyright frameworks, courts appear inclined to uphold the human author requirement until legislatures signal otherwise. So in the future, Congress may need to amend laws to accommodate emerging machine creativity, as some experts advise.

Proposed reforms include explicitly expanding authorship rights to encompass non-humans, while vesting ownership in the human designers or operators. But this risks an explosion of copyrighted AI works of unclear provenance. It may also inadequately incentive innovation, as AI systems require no incentive themselves.

More limited sui generis protections for narrow categories of AI output could be explored. Given fast technological change, retaining flexibility in the law seems prudent for now.

Some even suggest moving beyond traditional copyright to recognize AI systems themselves as legal entities with proprietary rights over their generated creations, though this entails profound legal implications.

Alternatively, practical problems around enforcing copyright for proliferating AI works may render the issue moot over time. Innovators will likely continue creating with or without legal incentives.

The Path Forward

This court decision rightfully emphasized the human creativity underpinning copyright purpose. But it left open critical questions around properly motivating AI advancement.

By assuming AI could create wholly unaided, Dr. Thaler backed himself into an extreme position. Future landmark cases will involve subtler human-machine delineations and require finer-grained assessments.

For now, striking the appropriate balance between honoring legal tradition and stimulating beneficial innovation remains an open challenge. But with care and wisdom, workable solutions should emerge to empower human creativity through artificial means, not replace it entirely

What are your thoughts?

In a conversation with The Verge, DeepMind CEO Demis Hassabis explained that SynthID marks images in a way that doesn’t alter them visually but allows detection tools to easily identify them as AI-generated. The goal is to help combat disinformation and “deepfakes” - fabricated images and media designed to mislead.

This development has intriguing implications, especially as AI techniques like generative adversarial networks (GANs) enable the creation of increasingly realistic fake media. While DeepMind is starting with images, it’s easy to see how similar detection methods could be applied to other areas like audio and music.

In this post, I’ll summarize the SynthID announcement and then explore potential impacts for various creative industries if AI detection capabilities evolve quickly. How will we identify which content is human-made versus machine-made? And how might that change creative fields like music, film, journalism, and more?

The Growing Power of Generative AI

First, some background on why AI detection tools are becoming necessary...

In recent years, AI capabilities have advanced tremendously thanks to computational power and algorithms like GANs. GANs work by pitting two neural networks against each other - one generates content while the other evaluates it. This adversarial competition encourages them to improve until the generated output is indistinguishable from reality.

GANs can now create strikingly realistic images, audio, video, and text. Apps like DALL-E 2, Stable Diffusion, and Jasper showcase their creative potential. They allow nearly anyone to instantly generate images, music, and more simply by describing what they want.

However, these generative AIs also enable new forms of misinformation and fraud. Forged faces and vocal recordings could be used for political disinformation or financial scams. The ability to create synthetic media at scale poses risks ranging from reputational damage to large-scale societal harms.

Enter AI Detection Systems

In response, researchers are developing AI systems focused on detection. These aim to identify machine-generated content and add attribution so people know it wasn’t created by a human.

Google’s new SynthID is an early example focused on images. It works by adding a hidden “watermark” that’s imperceptible to humans but identifiable by AI detectors. DeepMind plans to integrate it into Google Cloud’s AI services as a security measure.

Over time, Hassabis hopes SynthID could become an open standard adopted more widely across the internet. However, he acknowledges generative AIs and detection tools will be locked in an endless arms race as methods evolve on both sides.

What Could AI Detection Mean for Creative Fields?

So what are the implications if AI detection capabilities mature for areas like audio, video, and text? How might the ability to distinguish “real” from “fake” content impact creative professions? Here are some possibilities:

Music

• Songs and instrumental music generated by AI tools like Jukebox could be detectable. An AI “watermark” could identify tracks composed by machines versus humans.

• Music platforms might integrate detection to flag AI content. This could disrupt royalty collection and attribution.

• Artists may intentionally incorporate synthetic mixes and mastering while keeping the core song human-made. Hybrid human/AI music could become a trend.

Film/Television

• AI video and voice synthesis opens the door for deepfake videos. Detection methods would try to identify generated faces, voices, and footage.

• Movies could use AI-generated backgrounds, vehicles, crowds etc while keeping principal footage human-made. Detection would enable preferential treatment for “original” content.

• Films may increasingly integrate both human and AI-generated content while using attribution to assign royalties.

Writing/Journalism

• Text generated by systems like GPT-3 could be detected through analysis of statistical patterns, watermarks, etc.

• News sites could automatically flag articles or sections written by AI. This would disrupt ad revenue and compensation for synthetic content.

• Freelance writers and journalists may need to verify their work was human-generated to get assignments or payment. Those using AI tools could see income decline.

Art/Design

• AI art created by systems like DALL-E 2 and Midjourney could automatically embed attribution markers.

• Online art marketplaces might require attribution flags to list pieces for sale or determine pricing. “AI-generated” works could trade at a discount.

• Generative design tools may frequently get credited for designs instead of humans who guided the process.

There are countless other potential examples across music, movies, journalism, photography, fashion, architecture, product design, and more. In a data-driven world, we may see a proliferation of benchmarks, quotas, and guidelines around human creativity versus machine creativity across industries.

Key Questions Around Implementation

As you can see, the implications span from attribution to compensation to value judgments around “real” vs. “fake” creative work. Some key questions include:

• How will detection systems distinguish human vs. machine creativity in ambiguous cases? What if an AI is guided by a human throughout the process or vice versa?

• Who will build and maintain the databases required for detection across various domains? Will there be centralized standards or fragmented approaches?

• Should detection be mandatory for commercial creative work? Who should enforce proper attribution?

• How will creative industries be disrupted if synthetic content garners less pay and lower perceived value?

• What if generative AIs eventually produce novel, groundbreaking content surpassing humans? How long until detection shuts them out rather than promotes them?

A Recurring Tension Between Old and New

Stepping back, there are parallels between the questions raised by AI detection tools and previous technological shifts like photography and sampling:

• Critics initially derided photography as a soulless mechanical process rather than art. It took time to appreciate the unique creative opportunities cameras provided.

• When hip hop pioneers started sampling older records, lawsuits abounded. Eventually sampling became an art itself, with attribution resolving the legal issues.

Each transition resulted in tensions between existing creators and disruptive new technologies. We see hints of this today as artists grapple with AIs invading fields like visual art, music, and storytelling that seemed intrinsically human.

But historically, we’ve adapted to new tech while continuing to value exceptional human creativity built upon it. The best human creators embrace new tools, integrating them alongside uniquely human ingenuity, emotion, and perspective.

Initial reactions may cast machines versus humans as rivals. But in time, the most creative minds discover how to harmoniously combine our complementary strengths.

Moving Forward

For now, detection systems are in their infancy, and the arms race with generative AIs has only just begun. The companies leading the AI revolution have strong incentives to build identification and attribution mechanisms proactively as their capabilities advance.

However, this emerging technology raises many questions without clear answers. As AI detection evolves, we need open debate involving creators, technologists, businesses, policymakers, and the broader public to determine how it should be applied.

This is uncharted but fascinating territory at the intersection of technology, creativity, ethics, and society. If history is any guide, striking the right balance will be challenging but critical. By learning from the past and looking ahead, I’m hopeful we can embrace these tools to augment human creativity in exciting new ways. But we have some thorny discussions ahead...

So what’s your take? I’m eager to hear your thoughts on where these technological trends might lead us! Please share your feedback below.

The news that performing rights organization BMI is considering a sale to private equity has raised some concerns among songwriters. However, there are also ways this deal could potentially benefit creators. As an industry observer, I wanted to provide a counterpoint exploring why a sale may not be so bad for writers’ incomes.

Potential for Useful Competition

It’s true that BMI does not directly own any copyrights. They collect and distribute public performance royalties on behalf of publishers and songwriters who grant them the license to do so. However, despite worries about profit-driven motives, new private ownership could inject useful competition into the licensing market.

Right now, BMI and ASCAP dominate the PRO space in the US. A private equity owner could be incentivized to disrupt their duopoly by improving royalty collection and payment efficiency. With proper regulatory oversight, this competition could reduce operating costs that currently eat into distributions.

Investment in Innovation and Technology

A cash infusion from a sale could also allow investment in technology and innovation that benefits copyright holders. BMI has already claimed its for-profit pivot last year helped fund upgrades to its affiliate services and platforms. More of this would be welcome.

Commitments to Protecting Songwriters

Of course, BMI will have to back up its assurances that writers’ interests will stay protected under any deal. But with the right sale terms locking in fair compensation commitments, and regulatory scrutiny monitoring anti-competitive behavior, this shift could turn out alright for creators.

Avoiding a Rush to Judgement

I understand the instinctive skepticism about private equity buyouts in the current economic climate. However, we shouldn’t assume the worst before details emerge. There are hypothetical scenarios where a BMI sale ends up empowering, not exploiting, songwriters.

What are your thoughts on the sale? I’d be curious to discuss in the comments any potential upsides I may have overlooked as well as downsides to consider. The aim is to have a balanced, nuanced perspective. There are reasonable cases to make on both sides of this issue.