Vol. I · A Publication on the Long Future
Understanding not only how artificial intelligence evolves — but how civilization must evolve alongside it.
§ I
Technology does not change civilization. People do.
Artificial intelligence is not the story. Human adaptation is.
The Next Civilization exists because the conversation around artificial intelligence has become loud, fast and shallow — and the questions that will actually matter in twenty years are quiet, slow and deep.
Following the news of technology tells you what changed this week. Understanding civilization tells you what is likely to remain true for the rest of your life. This publication is written for readers who prefer the second.
§ II
Three essays open the first volume. Each begins a series the publication will return to over the coming years.
On Labor & Judgment
When intelligence becomes abundant, the value of judgment, taste and trust does not vanish. It concentrates — in fewer hands, and in stranger places than economists expected.
On Institutions
Our laws, schools and corporations were designed for a century of incremental change. The next decade will not be incremental — and the friction will be felt long before the policy catches up.
On Capital
What happens when the means of producing intelligence are no longer scarce, no longer centralized, and the returns no longer geographically bound to a handful of cities.
§ III
Six long arcs we follow. Each will become a dedicated section of the publication as the work matures.
Markets, productivity and the shifting price of cognition.
How people, families and communities absorb accelerating change.
Ownership, access and the geography of intelligence.
Learning systems for a world where knowledge is cheap.
Embodied intelligence in physical economies.
Governance, law and the slow machinery of trust.
§ IV
A working bibliography for the next civilization — the books, papers and institutions that inform our thinking.
A foundational map of the trajectory from general to superhuman systems, and the open problems that separate them.
The canonical theory of how new ideas and technologies move through societies — still the clearest lens for understanding AI adoption.
Why most transformative technologies stall between early enthusiasts and the mainstream, and what determines whether they cross.
Decades of longitudinal evidence on how human beings actually experience work, change and institutions.
A sober macroeconomic baseline for thinking about productivity shocks in a world of cheap intelligence.
An early reference architecture for compute as a distributed, sovereign and economically owned resource.