Status: Development On Hiatus - Resuming May 8.
Version: 0.4.3
The Automated Economy Initiative is founding a new field - one that existing economics, governance theory, and social science are not equipped to handle. This is not commentary on AI. It is the construction of a rigorous intellectual framework for civilization after the assumptions of scarcity, human labor, and institutional continuity no longer hold.
Modern economics explains how humans allocate scarce resources. Modern governance assumes human agents making decisions within institutional structures. Modern social norms are built around work as the organizing principle of identity, status, and participation. AI breaks all three simultaneously.
Labor is no longer the primary input to value. Capital that can replicate itself, learn, and improve without human input does not fit into any existing production function cleanly. Governance has no framework for non-human agents. When an AI system makes a consequential decision - economic, legal, social - existing institutions have no coherent answer for accountability, representation, or rights. Scarcity assumptions collapse under AI-driven abundance. The core mechanism of price theory - scarcity signals driving allocation - degrades when marginal cost approaches zero across entire industries simultaneously.
These are not edge cases or long-run concerns. They are structural failures in the current framework, already in motion. Patching existing theory is insufficient. The field this initiative is building starts from different axioms.
The Automated Economy Initiative would re-evaluate each domain of society & provide an answer for each core question:
| Domain | Core Question | |———————–|————————————————————————————| | Labor & Value Theory | How would value be created and distributed when machines outcompete human labor? | | Capital & Ownership | Who owns the means of ownership & what does it imply about capital allocation? | | Governance & Policy | What role would governance play in a world of agentic intelligence? | | Economic Modeling |How does value get modeled and allocated when the primary inputs are no longer human?| | Ethics | What responsibility are we endowed upon with AI technology for societal cohesion? | | Geopolitics & Power | How would the race for AI define the next century of power dynamics? | | Culture & Meaning | What can societies do once AI detaches meaning from value creation? |
The Automated Economy Initiative has identified these key axioms past frameworks don’t address. Any work that wishes to be contributed into the Initiative MUST build themselves on top of them, not without them.
Labor is a diminishing input: Human labor is being marginalized in value as scarcity-shifts reduce its necessity. Frameworks of old would be obsolete lest they depend on human-centric aggregates.
Abundance does not solve distribution: A post-scarcity economy does not automatically produce equity. The political economy of plenty is as contested as the political economy of scarcity, and less studied.
The shift of power from decentralized intelligence will end existing power structures. How societies respond to such will define the coming century of societal dynamics, and it won’t be easy to undo.
The exponential nature of AI contradicts pre-existing patterns of scarcity-shifts. The idea that scarity-shifts would remain linear in knowledge/intelligent bottlenecks will end, completely removing humans from value-creation.
The Automated Economy Initiative’s aim is to become an open reference for every class of people, a reference where everyday civilians, researchers, tech enthusiasts and statisticians can extract value from the repository. Below are the kinds of extractions one can hope to receive:
Researchers - Foundational literature, novel frameworks, and empirical datasets to anchor new work in a field that has no established canon yet.
Policymakers - Actionable models and transition analyses to inform legislation before institutional lag makes the decisions for them.
Builders & Founders - A theoretical grounding for the economy they are actively constructing, whether they realize it or not.
Statisticians & Modelers - Raw data, displacement curves, and simulation scaffolding for quantitative work on labor, capital, and distribution dynamics.
Educators - Curriculum material for teaching economics, governance, and social theory in a context where the standard textbooks are already obsolete.
Journalists & Analysts - A rigorous reference point for covering AI’s structural economic impact beyond the usual hype and panic cycles.
Everyday civilians - Plain-language documentation of what is actually happening to work, wages, ownership, and society, written for people who need to understand.