The Gold Asset Currency: AI, Sovereignty, and the Problem of Trust
How AI-assisted resource mobilisation and asset-backed money could help build a more efficient global economy.
How AI-assisted resource mobilisation and asset-backed money could help build a more efficient global economy.
A proposed future in which intelligence, competitive pressure, and the complexity of civilisation gradually shift decision-making from humans to AI.
AI can produce extraordinary benefits or harmful outcomes without those outputs alone proving conscious moral intention. Artificial Innocent Intelligence asks us to examine the training, objectives, incentives and human decisions that shape artificial intelligence before calling it a deity or a monster.
Three Centres of Power in a Possible Post-ASI Civilisation. A speculative analysis of how the masses, asset-owning classes and AI systems might compete over resources, ownership, control and human agency.
What if advanced AI eventually surpasses humanity in nearly every capability? The Human Zoo Paradox explores a future in which humans survive in comfort and safety but lose control over their civilization.
AI can do work worth $1,000 yet cannot earn $1 on its own. The missing piece is economic agency: customers, authority, ownership, capital and control.
AI may become smarter than humans without automatically becoming more powerful. Explore the 20-watt brain, 8 billion minds, autonomy, ownership and control.
A concise exploration of how automation and AI could change the relationship between economic usefulness, ownership, bargaining power and democracy.
What if an intelligent AI could expose a real but weak vulnerability, causing humans to spend their limited defensive resources patching the wrong problem?
A framework for separating AI capability, cognitive labor, work product, attribution, confidentiality, and rights—and understanding AI as a digital employee or agent.
AI companies are approaching a turning point: remain providers of powerful research tools, or become intellectual institutions that discover and commercialize ideas themselves. The difficult territory lies between the two.
AI may become so capable that humans voluntarily surrender practical control—not because AI takes the wheel, but because its reasoning becomes too persuasive to resist.
AI is entering mathematics at unprecedented speed. The real question is not whether machines can solve problems, but who gets the credit—and whether AI enriches mathematics or turns it into a leaderboard.
If AI companies can commercially learn from humanity’s knowledge, should humanity receive a return?
