They want us fighting and divided and loud, while they sell tokens and keys to a cloud
Every week our feeds fill with people brawling over whether Suno or Udio can “really” sing the blues. The latest Google Ai video tool is being shown widely online, and it’s getting pretty good.
It’s fun theater, heck, I am often arguing and participating in this dramatic debate, but as I was about to launch into another passionate online tirade about what it means to be an artist – I started to think, that maybe the decibels in this shouting match hide a quieter story: while we argue about authenticity, a handful of firms are locking down the infrastructure, data, and laws that are making them massive money and allow them to meter culture itself.
Four silent land‑grabs happening right now
Compute Monopoly
Nvidia’s data‑center revenue hit $22.6 billion, up 427 % year‑over‑year—an explosion powered almost entirely by AI training demand NVIDIA Newsroom.
Argue about what’s on the car radio all you want, whoever owns the GPU clusters owns the toll road.Token Tolls
Large‑model APIs are sold by the syllable. OpenAI’s flagship “reasoning” tier charges $10 per million input tokens and $40 per million output tokens OpenAI.
The more hype and hope, the more haters and “I’ll show them” types, the more prompts, the richer the meter, no matter the chatter.IP Accumulation
While musicians debate ethics, major labels are suing—and simultaneously cutting side deals with—AI startups for mass infringement Reuters.
Catalogs are being hoovered into private vaults or training sets at fire‑sale prices.Rule‑Book Capture
A draft U.S. bill would freeze state‑level AI regulation for ten years, a gift to companies that already set the technical standards Politico.
No guardrails, no problem—if you’re the one selling the steering wheel.
Why the shouting is useful to them
Attention solvent – Culture‑war headlines keep journalists busy, regulators sleepy.
Free R&D – Every prompt and playlist becomes unlabeled training data.
Demand inflation – “Proving” AI’s creative prowess justifies the next GPU order.
Missed coalitions – Artists and users stay fragmented, so bargaining power never aggregates.
A recent $10 million streaming‑fraud indictment—thousands of AI‑generated tracks, zero real fans—shows how quickly this playbook pays off WIRED.
How to step out of the distraction loop
My thought is, I am passionate and emotionally charged on this topic, and that is exactly the WRONG place to come from if I’m thinking about ways to confront this. When I posited what could be done, I realized I hadn’t done any research on action steps to untangle this new nexus of cloud selling and cloud yelling.
First off, I think we should look squarely at where all the money is being made, and HOW it is being made, and that is by selling data and access and compute and cloud, not fighting for art or culture or even stealing art and culture – they don’t care. So we have to. But how?
What follows is a 3o GPT model response to my question. When it spit this out I realized I have no familiarity in this space, so I’m also including the suggestions for action steps to take these suggestions and do something below.
Follow the money – Track royalty flows and publish compute mark‑ups next to subscription fees.
Make licences revocable – Time‑bound dataset deals that dissolve if audits fail.
Tax the choke‑points – Per‑token or per‑kilowatt levies to fund independent art and open models.
Co‑own the stack – Artist‑run GPU co‑ops or collective bargaining for cloud credits.
Shift the story – Move the question from “Is it art?” to “Who gets paid, who gets policed, and who sets the throttle?”
Authenticity arguments are emotionally real, but economically they’re a smokescreen. The decisive struggle isn’t over what counts as “real music”; it’s over who controls the chips, the tokens, the catalogs, and the laws that govern them. Keep enjoying the debate—but keep one eye on the ledger where the actual chorus is being written.
Where to Plug In: 10+ Groups Turning AI Culture-Wars into Action
Below is a starter map. None of these orgs is a silver bullet, but each tackles a slice of the problem so you don’t have to start from zero.
1. Follow the Money — Royalty & Compute Transparency
Future of Music Coalition (FMC) – digs into payment data and lobbies for musician‑first copyright reform
Mechanical Licensing Collective (MLC) – runs the U.S. song‑royalty database and now publishes unmatched payouts, letting artists see where streaming pennies hide
Electronic Frontier Foundation (EFF) – litigates for disclosure of how copyrighted works and user data train Gen‑AI, pressing agencies and courts for full accounting eff.org
2. Make the Licence Fight Back
Spawning.ai – offers the Do Not Train registry that artists can embed in files; models respecting it must drop your work on request
Authors Guild – spearheads class‑action lawsuits demanding consent‑based, time‑bound licences for text corpora (same playbook musicians could copy) authorsguild.org
Writers Guild of America (WGA) – negotiated the first Hollywood contract reserving writers’ right to sue studios if scripts feed AIs without permission cdt.org
3. Tax or Regulate the Choke‑Points
AI Now Institute – publishes policy toolkits on breaking cloud compute monopolies with antitrust, export‑control, and public‑interest tariffs
Public Knowledge – Washington advocacy shop linking AI hype to old‑school antitrust; pushes Congress for utility‑style oversight of cloud giants publicknowledge.org
Tucker United (WV) – grassroots coalition fighting a 1 GW gas‑powered data‑center; their playbook blends local environmental law with national media pressure
4. Co‑Own the Stack
Resonate.co‑op – a democratic streaming service where artists, listeners, and workers split governance and revenue
GPU.net & similar decentralised GPU networks – pool spare graphics cards into a member‑run cloud, cutting hyperscaler dependence for open‑source model training
5. Shift the Story — Accountability & Provenance
Algorithmic Justice League – blends research, art, and protest to expose bias and rally legislators around community‑led AI audits
Content Authenticity Initiative (CAI) – builds an open standard (C2PA) that watermarks provenance into images, audio, and video so audiences can trace what’s human, what’s machine
Now what….
Pick a lane—royalty data, licensing, antitrust, local land‑use, or open infrastructure.
Join their mailing list / Slack / Discord. Most welcome skill‑based volunteers (law, comms, dev, design).
Borrow & remix their templates—opt‑out tags, FOIA request letters, city‑council testimony scripts.
Cross‑pollinate—connect the compute‑tax folks with the royalty auditors so money trails and carbon trails become the same story.
The cultural debate stays interesting; the power struggle stays hidden—unless enough of us turn debate into dues‑paying, code‑writing, phone‑dialing work. These orgs give you a door in.
DISCLAIMER:
I used GPT 3o for this research and to tighten the composition – links have all been checked and vetted, words edited; anything I missed or got wrong, let me know!
POSMarketing 