Domain II — Artificial intelligence

Intelligence in service of human agency, not in place of it.

AI is reshaping work, knowledge, and power at unprecedented speed. Whether it concentrates that power or broadens human capability is a question of ownership, design, and intention — not a technical inevitability.

Why now

The most consequential technology of our lifetimes deserves considered stewardship.

AI systems are being deployed at civilisational scale before their implications are widely understood. The decisions being made now — about who builds these systems, who benefits, and who is accountable — will shape decades to come.

CAISCEN does not treat AI as either salvation or threat. We treat it as a domain that requires patience, cross-disciplinary judgement, and the courage to ask uncomfortable questions early.

Concerns we take seriously

Risk, incentive, and concentration.

Concentration of power

A small number of firms are shaping the infrastructure of intelligence. This is a governance question, not merely a competitive one.

Erosion of judgement

Convenience can hollow out the very capabilities — attention, judgement, craft — that make human agency meaningful.

Extractive deployment

AI can accelerate extraction — of data, of labour, of ecological resources — unless deliberately shaped otherwise.

Public interest gap

Most alignment work happens inside the firms building the systems. Independent, publicly accountable capacity is thin.

What AI could serve

Human capability, co-operative infrastructure, and regenerative futures.

The same technologies that risk concentrating power could — under different ownership, different incentives, and different design — broaden access to expertise, support co-operative coordination, model ecological systems, and free human attention for the work only humans can do.

That trajectory is not automatic. It has to be chosen, built, and defended.

Questions we are exploring

What does AI in the public interest actually look like?

  1. 01

    What forms of ownership and governance would keep AI accountable to the public?

  2. 02

    How can AI strengthen — rather than erode — the judgement of practitioners who use it?

  3. 03

    What safety practices belong outside the firms building frontier models?

  4. 04

    How do we prevent the gains of AI from being privately captured?

  5. 05

    What role can co-operatives play in shaping open, shared AI infrastructure?

  6. 06

    How do we hold both the risks and the possibilities without collapsing into hype or fear?

Related resources

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