Predistribution is an economic strategy focused on how the market distributes income before taxes are collected. Instead of allowing the market to generate extreme inequality and trying to fix it later with taxes and welfare, predistribution changes the rules of the game so wealth is shared more broadly as it is created.

The core argument is timing. Once AI inequality locks in, the political power of winners can become too strong to tax effectively. That means intervention has to happen upstream.

The Core Concept: Fixing the Pipes vs. Fixing the Leak

Redistribution says: let market outcomes happen first, then rebalance through taxation and transfers.

Predistribution says: redesign ownership and participation so market outcomes are less unequal in the first place.

Predistribution vs. Redistribution

FeatureRedistribution (Old Model)Predistribution (New Model)
TimingAfter the money is madeDuring value creation
MechanismTaxes, welfare, UBIOwnership stakes, equity, wage design
Logic“Let winners win big, then tax them”“Ensure more people win as the economy grows”
Power dynamicCitizens as dependents receiving aidCitizens as participants holding assets
AI contextTaxing OpenAI/Google to fund checksGiving citizens a stake in AI infrastructure

How These Mechanisms Could Work

1. AI Sovereign Wealth Funds (The “Alaska Model”)

As Alaska residents receive dividends from oil revenue, an AI sovereign wealth fund would treat data and compute as resources with a public claim.

🏛️ Sovereign Fund Mechanics

How it works: Government taxes the use of public data or holds a public stake in infrastructure such as energy grids and data centers.

The payoff: Returns flow into a national fund and are paid back to citizens as dividends, framed as ROI on collectively owned resources.

Governance risk: Investment control can be captured unless governance is insulated (for example, independent boards).

2. AI Bonds (The “War Bond” Model)

Governments could issue AI infrastructure bonds to finance large-scale energy and compute buildouts.

💰 Bond-Based Participation

How it works: Citizens buy AI infrastructure bonds used to build shared compute and energy assets.

The payoff: AI firms pay to use this infrastructure, and usage revenue repays bondholders with interest.

Requirement: A durable revenue base from infrastructure access fees.

Risk: Platforms may vertically integrate their own infrastructure to avoid paying usage fees.

3. Worker Ownership Models (The “Equity” Model)

If labor value declines while capital value rises, ownership design becomes central.

🏭 Worker Equity Design

How it works: Incentivize or mandate structures like ESOPs so workers accumulate ownership, not only wages.

The payoff: If AI increases margins, workers capture part of that upside through equity.

Fallback protection: If workers are replaced, they exit with capital assets instead of only severance.

Limits: Liquidity and scale constraints remain, especially at mega-platform size.

Why the Window Is Closing

The timing problem follows a feedback loop:

  1. AI adoption accelerates wealth concentration.
  2. Concentrated wealth buys political influence.
  3. Political influence blocks structural reform.

⏰ Lock-In Risk

The risk: Waiting even a few years could let platform and infrastructure winners harden rules in their favor.

The trap: Once wealth concentration is entrenched, structural reform is framed as expropriation and becomes politically fragile.

The threshold: If top 1% US wealth share approaches ~40% (around 37% today in this framing), leverage effects can make major reform far harder.

What Could Extend the Window

  • Slower AI adoption from regulatory friction
  • Stronger democratic institutions
  • Coordinated labor pushback
  • Active antitrust enforcement

What Could Shorten the Window

  • Faster automation deployment
  • Weaker antitrust enforcement
  • Platform consolidation through vertical integration
  • Regulatory capture

Further Reading