Universal Basic Intelligence: Who Gets Access, on What Terms

The earlier parts of The Age of Agency are about organisations: what agents do, which decisions they may make, how work and value move, how to measure what agents contribute and how to govern them. The final part widens the lens to society.

If capable intelligence becomes a basic input to work, learning and public services, then access to it begins to resemble access to electricity, literacy or the internet. It becomes a condition for taking part. Those without it are not simply less efficient. They are excluded from opportunities that others take for granted.

I call the response to this Universal Basic Intelligence: the idea that capable AI should be treated as essential infrastructure, available to everyone on fair terms. This essay sets out what that means, and what it does not.

Intelligence as infrastructure

Every era has its essential infrastructure. Roads and ports determined which towns grew. Electricity determined which industries could exist. Literacy determined who could take part in public life. The internet determined who could reach markets, information and services.

In each case, the infrastructure began as a luxury and became a necessity. And in each case, societies had to decide how it would be provided: by the state, by private firms, or by some combination, and on what terms.

Capable AI is following the same path. It is already changing how people learn, how small firms compete, how public services are delivered and how professionals work. As agents become more capable, the gap between those who have access to them and those who do not will widen.

What Universal Basic Intelligence means

Universal Basic Intelligence is not a promise that everyone receives the most advanced system for free. Nor is it a call for any particular technology or provider.

It is a principle with three parts.

A baseline of capability. Everyone should have access to AI capable enough to help them learn, work, deal with public services and make informed decisions, in their own language and context.

Fair terms. Access should come on terms that do not exploit the people who depend on it: transparent pricing, protection of personal data, and freedom from manipulation designed to serve the provider rather than the user.

Real usefulness. Access only matters if people can use it well. That requires skills, local relevance and systems that work for people whose language, culture or circumstances differ from those of the people who built them.

Who provides it, and on whose terms

The most capable AI systems are currently developed by a small number of organisations with access to enormous amounts of computing power, data and capital. That concentration raises legitimate questions.

What happens to small firms if the tools they depend on are owned by companies that may also compete with them? What happens to smaller economies if the systems their citizens rely on are built elsewhere, priced elsewhere and governed by rules written elsewhere? What happens to individuals if the terms of access change, or if the systems reflect values and assumptions that are not their own?

There is no single answer. Some countries will invest in their own capabilities. Others will rely on international providers, open models or regional partnerships. Many will combine approaches. What matters is that these choices are made deliberately, with an eye to resilience, competition and public interest, rather than by default.

Smaller firms and smaller economies

The promise of AI for smaller firms is considerable. An agent can give a business of ten people capabilities that once required a much larger organisation: analysis, marketing, customer service, compliance. Universal Basic Intelligence, in this sense, could reduce the advantages of scale.

But that promise depends on access, cost and skills. If capable systems are expensive, or require expertise smaller firms lack, AI will instead widen the gap between large and small. The same is true between economies. Policy choices about access, skills and competition will decide which outcome prevails.

Preparing people to work alongside agents

Education is where Universal Basic Intelligence becomes practical. If people will work alongside agents throughout their lives, they need more than the ability to use them. They need judgement about when to trust them, the ability to check their work, an understanding of their limits and the confidence to overrule them.

That suggests an education that places more weight on reasoning, evaluation, communication and ethics, and less on memorising what a machine can retrieve instantly. It also suggests lifelong learning, because the capabilities of agents, and the work they change, will keep moving throughout a career.

The role of business

Governments will make many of the decisions that shape access to AI. But business has a role too. Organisations decide how they deploy agents, what terms they offer customers, how they treat the people whose work changes, and whether they invest in the skills of their staff and communities.

Businesses that treat capable AI as something to extend to their customers, suppliers and employees, rather than only as a source of advantage over them, will help build the conditions in which they themselves can thrive.

The question that runs through the book

The Age of Agency closes where it began. The shift from AI that answers to AI that acts is not something that simply happens to us. Its shape depends on decisions made now: which decisions machines may make, how work is redesigned, how value is measured, how agents are governed and who has access to them.

None of these decisions is technical at heart. They are decisions about responsibility, fairness and the kind of organisations and societies we want to build. They belong to leaders, and the time to make them is now.

This essay introduces Part VI of the forthcoming book The Age of Agency. Universal Basic Intelligence is a framework originated by Dr. Elias Kairos Chen.

Views are the author's own. The frameworks described are applied methodologies of Kiros Intelligence Group, not regulatory standards.