Author: Ram Kumar, Core Contributor at OpenLedger

The public has unknowingly contributed to the rise of artificial intelligence, often without realizing it. With AI models expected to generate trillions of dollars in value, it is time to view data as labor and establish an on-chain attribution system to pay those who made it possible.

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

While these companies are reaping billions in profits, end users receive nothing. No checks, no credits, not even a thank you.

This is what invisible labor looks like in the 21st century. Billions of people have become unpaid laborers behind the AI revolution. The data they generate—from text, code, faces to actions—has been scraped, cleaned, and used to teach machines how to sound more human, sell more ads, and complete more transactions.

However, the humans who make all this possible are completely excluded from the economic cycle driving AI.

This story is not new. The same pattern has built empires on the basis of uncredited creative labor. Only now, the scale is global. This is not just about fairness; it is about power, and whether we want a future where intelligence is owned by three companies or shared by all of us.

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

Payable AI proposes a future where there are no secret-trained black box models, but openly built AI, with every contributor traceable and compensated for each use. Every post, video, or image used to train a model should come with a label or digital receipt. Each time the model is used, small payments should be sent to the original creators of the data. This is the attribution of embedded systems.

There is a precedent for this. Musicians now earn royalties when their songs are streamed, and developers receive credit when their open-source code is reused. AI should follow the same rules. Just because training data is digital does not mean it is free. If anything, it is the most valuable commodity we have left.

The problem is that we have always viewed AI as traditional software—something built once and sold a million times. However, this analogy quickly becomes untenable.

AI is not static. It learns, decays, and improves with each interaction, and it weakens when data runs dry. In this sense, AI is more like a living ecosystem, feeding on continuous human input, from language and behavior to creativity. Yet, there is no system to explain this supply chain, nor any mechanism to reward those who nourish it.

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

Years from now, autonomous AI agents will be ubiquitous: booking services, negotiating contracts, and running businesses. These agents will conduct transactions, and they will need wallets. They will also need access to fine-tuned models, which must be paid for in datasets, APIs, and human guidance.

We are heading towards machine-to-machine commerce, but the infrastructure is not ready.

The world needs a system to track what agents have used, where this intelligence comes from, and who should be compensated. Without it, the entire AI ecosystem becomes a black market of stolen insights and untraceable decisions.

Compared to autonomous agents acting on behalf of people, today's complex AI issues pale in comparison, as we cannot audit where their "intelligence" comes from.

However, the deeper issue is control.

Companies like OpenAI, Meta, and Google are building models that will power everything from education to defense to economic forecasting. They increasingly own this space. Meanwhile, governments—whether in Washington, Brussels, or Beijing—are scrambling to catch up. XAI is being integrated into Telegram, and messaging, identity, and cryptocurrency are increasingly merging.

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

This requires more than just new terms of service. It will demand new rights, such as the right to attribution, the right to compensation, and the right to audit systems built on our data. It will need new infrastructure—wallets, identity layers, and permission systems—that treat data as labor rather than waste.

It will also require a legal framework that acknowledges what is happening: people are creating value, and that deserves recognition.

Right now, the world is working for free. But not for long. Because once people understand what they are giving away, they will ask what they deserve in return.

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

We risk a future where the most powerful force on Earth—intelligence itself—is privatized, irresponsible, and completely beyond our control.

We can build something better. First, we must acknowledge that the current system is broken.

Author: Ram Kumar, Core Contributor at OpenLedger.

Related: OpenAI states that tokenized stocks on Robinhood do not represent company equity.

This article is for general informational purposes only and does not constitute legal or investment advice. The views, thoughts, and opinions expressed here are solely those of the author and do not necessarily reflect or represent the views and opinions of Cointelegraph.

Original article: “Solving AI Data Theft Through On-Chain Attribution”

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