Fix AI’s data theft problem with onchain attribution

Opinion by: Ram Kumar, core contributor at OpenLedger

The public has knowingly contributed to the rise of artificial intelligence, often without realizing it. As AI models are projected to generate trillions of dollars in value, it’s time to start treating data like labor and building onchain attribution systems to pay the ones making it possible

X posts by users helped train ChatGPT, and their blog posts and forum replies shaped models that are now monetized by some of the most powerful companies in the world.

While those companies are reaping billions, the end-users get nothing. Not a check, a credit or even a thank you.

Data is work that deserves pay

This is what invisible labor looks like in the 21st century. Billions of people have become the unpaid workforce behind the AI revolution. The data they generate, from words, code, faces and movement, is scraped, cleaned and used to teach machines how to sound more human, sell more ads and close more trades.

And yet, in the economic loop that powers AI, the humans who make it all possible have been cut out entirely.

This story is not new. The same model built empires on the backs of uncredited creative labor. Only now, the scale is planetary. This isn’t just about fairness but about power and whether we want a future where intelligence is owned by three corporations or shared by all of us.

The only way to redefine the economics of intelligence is through Payable AI.

A new economic model for intelligence

Instead of black-box models trained in secret, Payable AI proposes a future where AI is built openly, with every contributor traceable and every use compensated. Every post, video or image used to train a model should carry a tag or a digital receipt. Every time that model is used, a small payment should be sent to the data’s original creator. That’s attribution, baked into the system.

This has precedent. Musicians now earn royalties when their tracks stream, and developers get credited when their open-source code is reused. AI should follow the same rules. Just because training data is digital doesn’t mean it’s free. If anything, it’s the most valuable commodity we have left.

The problem is that we’ve been treating AI like traditional software — something you build once and sell a million times. That metaphor, however, falls apart fast.

AI isn’t static. It learns, decays and improves with every interaction, weakening when data dries up. In this way, AI is more like a living ecosystem feeding on a continuous supply of human input, from language and behavior to creativity. Yet there’s no system to account for that supply chain and no mechanism to reward those who nourish it.

Related: AI race between US and China resembles Cold War — Marc Andreessen

Payable AI creates a circular economy of knowledge — an economic structure where participation equals ownership and where every interaction has traceable value.

Autonomous AI agents will be everywhere: booking services, negotiating contracts and running businesses in a few years from now. These agents will be transacting, and they’ll need wallets. They will also need access to fine-tuned models and must pay for data sets, APIs and human guidance.

We are headed toward machine-to-machine commerce, and the infrastructure isn’t ready.

The world needs a system to track what an agent used, where that intelligence came from, and who deserves to be paid. Without it, the entire AI ecosystem becomes a black market of stolen insights and untraceable decisions.

Who controls AI today?

Today’s complicated problems with AI pale compared to autonomous agents acting on people’s behalf, with no way to audit where their “intelligence” came from.

The deeper issue, though, is control.

Companies like OpenAI, Meta and Google are building models that will power everything from education to defense to economic forecasting. Increasingly, they own the terrain. And governments — whether in Washington, Brussels or Beijing — are rushing to catch up. XAI is being integrated into Telegram, and messaging, identity and crypto are increasingly merging

We have a choice. We can continue down this consolidation path, where intelligence is shaped and governed by a handful of platforms. Or we can build something more equitable: an open system where models are transparent, attribution is automatic and value flows back to the people who made it possible.

Laying the foundation for ethical AI

That will require more than new terms of service. It will demand new rights, like the right to attribution, the right to compensation and the right to audit the systems built on our data. It will require new infrastructure — wallets, identity layers and permission systems — that treat data not as exhaust but as labor.

It will also demand a legal framework that recognizes what’s happening: People are building value, which deserves recognition.

Right now, the world is working for free. But not for long. Because once people understand what they’ve given, they’ll ask what they’re owed.

The question is: Will we have a system ready to pay them?

We’re risking a future where the most powerful force on Earth — intelligence itself — is privatized, unaccountable and entirely beyond our reach.

We can build something better. First, we have to admit the current system is broken.

Opinion by: Ram Kumar, core contributor at OpenLedger.

This article is for general information purposes and is not intended to be and should not be taken as legal or investment advice. The views, thoughts, and opinions expressed here are the author’s alone and do not necessarily reflect or represent the views and opinions of Cointelegraph.

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