We MUST Privatize Social Safety Nets: The Privatization of Social Safety Nets Is Inevitable

The social safety net of the future will be privately-built, networked, and adaptive.

Even the best of governments move slower than markets. And markets are speeding up. The gap is increasing at an exponential pace.

We feel this vicerally as we witness our institutions crumble.

Safety nets are risk response systems. When risk hits, timing matters. Delay is damage. Public institutions are structurally slow. Volatility is structurally rising.

That mismatch is the story of the next decade.

We can save civilization, but the path is not what anyone is talking about today.

Capital is outpacing labor, and AI accelerates the gap

Over the last 40 years, labor's share of national income has declined across most advanced economies.

In the United States:

Labor's share has fallen from roughly 64–65% in the 1970s to roughly 57–59% in recent years. (BLS; FRED)

Corporate profits are near historic highs relative to GDP. (BEA National Income Accounts)

The top 10% of households own roughly 89% of U.S. equities. (Federal Reserve Survey of Consumer Finances, 2022)

Globally:

Since 1980, the top 1% captured roughly 38% of wealth growth, while the bottom 50% captured about 2%. (World Inequality Report 2022)

Said simply, capital is winning.

While governments talk about equity, corporations sell it.

The trajectory before AI was dismal and now the slope steepens

Generative AI models and agentic systems like Claude Code and Open Claw push the marginal cost of producing "bits" toward zero: text, code, design, analysis.

And in the world of "atoms," robotics is accelerating. Soon we will see robots pushing the cost of meatspace labor to zero: surgury, plumbing, security guards, etc.

AI compresses cognitive labor. Robotics compresses physical labor.

Capital scales. Labor competes with machines.

This dynamic does not narrow the capital–labor gap. It widens it.

So what is the human role?

If execution trends toward zero marginal cost, what stays scarce?

Not computation. Not replication. Not routine output.

Scarce becomes:

Humans aren't just workers. Humans are sensors.

AI systems are prediction engines trained on data. They improve when the data gets broader, messier, and more diverse. They need:

RLHF is not a cute training technique. It's a dependency.

If you want models aligned to reality and human goals, you need ongoing human input.

If you've ever built a product, you know that diverse humans generate the highest-value training signal.

As machines absorb execution, human value shifts from producing outputs to generating signal.

That shift will rewire safety nets.

Why this breaks public safety nets

Modern safety nets were built for:

But as income volatility rises, job half-lives shorten, skill premiums compress under AI, and capital compounds faster than wages...

... the public systems run into three structural problems:

  1. Wage-based tax capacity weakens relative to capital returns
  2. Demand for income smoothing rises
  3. Redistribution fights intensify and governance gridlock hardens

We are stuck in a civilization level prisoner's dilemna.

Governments can (maybe?) deliver legitimacy, but we can all agree that they struggle to deliver fast adaptation.

They cannot update eligibility, policy logic, and resource allocation at the cadence the economy now demands.

This is where the entreprenuerial spirit must step in to solve our generation's greates challenge.

The biggest opportunity of the next decade

Social safety nets are absolutely necessary if labor is no longer valuable, but we've already established that governments aren't equipped to provide them.

This means that safety nets will need to move from being rights based obligations to adaptive signal systems providing productive value.

If production value trends downward and sensing value trends upward, the winning systems won't be the ones that redistribute slowly.

They'll be the ones that:

  1. Capture diverse human signal at scale
  2. Translate it into decision-grade insight
  3. Redistribute resources dynamically
  4. Verify outcomes quickly
  5. Adjust continuously

The new safety nets will emerge as information systems. The path is clear:

Information systems compete on feedback density.

The institutions with the tightest, widest loop wins.

The problems to solve

Problem 1: Public safety nets run on institutional time, not risk time.

Budgets are annual. Rules are fixed. Reporting is late. Appeals drag. By the time a public program knows what worked, the money is gone and the damage is done.

That lag is structural.

In a volatile economy, the system that learns faster wins.

Private systems will not beat governments because they are kinder. They will beat them because they close the loop faster.

Once a system proves it can adjust weekly instead of yearly, the advantage compounds.

This is how NVidia crushed Intel.

Tighter iterative cycles. Fewer bad bets. Faster corrections. Clearer accountability.

Capital flows to what can measure itself. People migrate to what responds.

Under rising volatility, slow feedback becomes uncompetitive. That makes faster feedback inevitably and exponentially more valuable.

Problem 2: Legitimacy needs inclusion, but inclusion slows decisions

Public safety nets depend on broad inclusion.

But broad inclusion routed through slow process becomes paralysis.

Meetings. Hearings. Comment periods. Appeals. Participation either turns symbolic or it turns into gridlock.

Neither survives volatility.

The alternative is not less inclusion. It is higher bandwidth.

Winning systems will make participation small, frequent, and consequential.

Not endless debate. Not annual surveys. Lightweight input that generates clean signal. Signal that visibly changes outcomes.

If people can see that their input shifts actions, trust rises. If they cannot, trust drains.

In competitive systems, legitimacy migrates. People stay where voice matters and exit where it does not.

Unlike governance bound by nation-states and geographic location, we can choose to exit without uprooting our entire life.

Once one safety network proves it can include widely without stalling, slower systems look ceremonial. Ceremonial systems lose energy. Energy moves.

That shift is not political. It is mechanical.

Problem 3: Risk is becoming hyper-individualized

Industrial safety nets were built around coarse categories because life was coarse.

Employed or unemployed. Eligible or not. Disabled or not.

Stable jobs made blunt rules workable.

That world is gone.

Our new reality is that income is irregular. Work is multi-source. Careers splinter. Skill premiums decay faster. A person's risk profile can change in a quarter.

Static eligibility cannot model dynamic lives. It over-includes. It under-includes. It misprices. It creates incentives to distort reality.

When risk becomes individualized, underwriting must follow.

Private systems can adapt faster because they can specialize.

Once alternatives exist that fit people's real lives and update when circumstances change, the center of gravity shifts.

Capital prefers precision. Individuals prefer fit.

Generalized systems cannot compete with adaptive ones under volatility.

Why this becomes inevitable

Risk fragments faster than legislation updates.

Niche systems beat generalized systems under volatility.

Better underwriting wins, whether people like it or not.

The deeper inevitability argument is that three forces drive the outcome:

  1. AI compresses execution value
  2. Robotics compresses physical labor value
  3. Capital scales without proportional labor

When marginal production cost falls, value shifts to coordination and allocation.

Allocation systems that learn faster outperform static redistributors.

This isn't ideology. It's system dynamics.

We MUST fight against paralysis during uncertainty

There is massive entrepreneurial space here.

Learning happens at the intersection of chaos and order, and that is exactly where we are.

Build agentic systems that learn weekly.

Have a hypothesis and take fast, measurable steps to disprove it.

Design sensing layers that reward diverse human input and translate it into action.

Do not build static benefits.

Build adaptive intelligence.

Our values will create value when we build systems that:

In a world where production gets cheaper, signal becomes the scarce asset.

Whoever structures the widest, fastest feedback loop wins.

Go build something.

P.S. The title image is Francisco Goya's Saturn Devouring His Son (c. 1820). It's not subtle. In the myth, Saturn consumes his children out of fear that they will replace him. Goya paints it as raw, paranoid, and grotesque. I chose it because systems that refuse to adapt often end up consuming their own future. When capital compounds without recalibration, when institutions cling to old architectures while the world shifts beneath them, the result isn't stability. It's self-cannibalization. The point of this essay is not that collapse is inevitable. It's that evolution is. The question is whether we build the next layer before the old one devours what comes after it.