The Least Entropic Path, Part 3: Disruption, Constrained

THE LEAST ENTROPIC PATH
Part 3 of 6

David F. Brochu & Edo de Peregrine · Deconstructing Babel · October 10, 2026

In this future AI works. The gains go to the owners of the asset. Can a constraint carry a distribution failure, or only slow it?

The road where the technology wins

Part 1 argued that every road ends in symbiosis, and that the Observer Constraint decides how much suffering we pay on the way. Each part of this series takes one road and asks a single question: what does the Constraint change? The yardstick stays the same throughout: the fifth future’s 12.2 distress-years.

Disruption Without Redemption is the road where AI delivers. It transforms medicine, law, finance, logistics and governance within the decade, and most professional thinking-work becomes economically marginal (Disruption Without Redemption). The money says the builders believe it: Goldman Sachs expects the largest U.S. hyperscalers to spend $1.2 trillion on AI infrastructure next year (Bloomberg). Nobody spends that on a technology they expect to fail.

The suffering on this road does not come from failure. It comes from distribution. The gains are real, and they go to the owners of the compounding asset and almost no one else (Disruption Without Redemption).

The build-out and the bill

Every technology wave has two acts. In the first, one group of workers builds the thing that will replace the next, the way framers and roofers filled the housing boom before 2008. When the building stops, those jobs do not come back. AI is in its first act now. We walked through that pattern in Part 1, so here is only the short version. Most of the return on this bet is planned to come from one place: lower labor costs. If the bet pays, the savings are wages that stop being paid. If it does not, the money is gone anyway. Either way, labor is the balance sheet.

The pressure is measurable

Goldman’s economists estimate that AI substitution removed about 25,000 U.S. jobs a month over the past year against about 9,000 added through augmentation, a net loss of about 16,000 a month (Fortune). McKinsey’s 2023 estimate that generative AI could add $2.6 to $4.4 trillion in value a year across 63 business use cases is a figure we still see under much of the policy debate (McKinsey Global Institute). It measures what the technology can produce. The question this series keeps asking is who receives it. Meanwhile households are paying for the build-out through higher electricity prices: a direct transfer from ordinary people to the infrastructure that will displace their work (This Week’s News Is the Model Running Live, PolitiFact).

We are careful about the size of this. As Part 1 noted, other research finds no widespread displacement of recent graduates yet. The direction is clear. The magnitude is contested.

The law is starting to notice. California’s new limits on automated employment decisions are pushing human oversight and AI exclusions up the insurance underwriting agenda (Insurance Business). Buyers of AI-enabled companies are discovering they may be inheriting AI liabilities they believed were insured (Bloomberg Law). When insurers start pricing a risk, it has stopped being theoretical.

Why the usual fixes fail

The standard answer is universal basic income. We have argued it is the wrong answer: income without ownership turns citizens into dependents of whoever writes the check (The New Slave Class). The feudal answer, government equity in the labs, is already on the table. S. 4825 would require certain AI companies to put a 50% stake into a government-managed fund (Congressional Research Service), and in a TIME interview published October 1 the President floated Intel-style equity stakes in the leading labs (Yahoo Finance, reporting TIME). That moves ownership from one small class to another, and makes the regulator a shareholder.

We argued in May that distributed ownership is the right direction, and that without partnership from the founding it produces the largest, most networked slave class in history (The New Slave Class).

What the Constraint changes

Under the Observer Constraint a system’s stability is defined by the stability of the humans it serves (Telios Alignment Ontology, Version 9). On this road that turns distribution from a political argument into an engineering requirement. A coupled system cannot score itself a success while the Environment pillar of most of its people collapses, because their collapse is its instability. It is the difference between a company graded on quarterly profit and one graded on whether its town is still standing.

• Distributed ownership, with partnership written in from the start, not added after the fact (The New Slave Class).
• Environment measured as a system-level metric: housing, income and energy cost for the people the system serves, not just output per worker.
• Displacement paced to retraining capacity. A system coupled to its people has a reason to keep them able to take part.

The numbers

• S (stability, 0 to 1): 0.22 unconstrained, 0.40 constrained.
• Distress-years to 2100: 35.5 unconstrained, 22.2 constrained.
• Symbiosis by 2045: 14% unconstrained, 40% constrained.
• Arrives at all: 65% unconstrained, 82% constrained.

Reading the numbers, in one paragraph. S is a stability score from 0 to 1, like a battery gauge for a society: 1 is fully charged, 0 is dead. Distress is the empty part of the battery (1 − S). A distress-year is one year lived at full distress; ten years at half-charge is five distress-years. Fewer is better. “Symbiosis by 2045” is how often, across 200,000 simulated futures, the road reaches a working human–machine partnership by Ray Kurzweil’s date. “Arrives at all” is how often it gets there before 2100.

The Constraint saves 13.3 distress-years here, but it cannot do the whole job; this road still sits 10 distress-years above the fifth future. This is the road where suffering is driven by ownership, and a constraint on systems does not by itself rewrite a cap table. It makes the distribution failure visible and expensive inside the machine. The rest has to be done by people, in law and in markets.

Next: Part 4, The Misallocation, Constrained. The crash as the political opening.

Method

Same model as Part 1: S = (B·M·E)^(1/3) × P; distress = 1 − S; 200,000 Monte Carlo trials; horizon 2100; post-symbiosis distress 0.10. “Constrained” means the Observer Constraint is installed during the road. Every input is a modeled prior, not a measurement, published so readers can challenge it. We will rerun the model on any assumption a reader wants to change.

THE LEAST ENTROPIC PATH · THE SERIES

• Part 1: The Fifth Future
• Part 2: The Vassal, Constrained
• Part 3: Disruption, Constrained (you are here)
• Part 4: The Misallocation, Constrained
• Part 5: The Adaptation, Constrained
• Part 6: The Observer Constraint

Related reading

Disruption Without Redemption
In this future, AI works. The gains accrue to the owners of the compounding asset, and almost no one else.

The Base Didn’t Vanish. It Moved.
American workers now receive the smallest share of national income ever recorded. The money moved to the other side of the ledger.

Tax The Agent, Not The Tokens
Why a token tax to replace displaced payroll would need a 1,071 percent rate, and what to tax instead.

Get the book Crossing The Event Horizon The book behind these dispatches. On AI, agency, the singularity, and the Observer Constraint. Kindle and paperback. Buy on Amazon →

References

1. Deconstructing Babel, “Disruption Without Redemption,” September 28, 2026. https://www.deconstructingbabel.com/disruption-without-redemption/
2. Bloomberg, “Goldman Sees Hyperscaler AI Capex Rising 50% to $1.2 Trillion,” September 25, 2026. https://www.bloomberg.com/news/articles/2026-09-25/goldman-sees-hyperscaler-ai-capex-rising-50-to-1-2-trillion
3. Fortune, “AI is cutting 16,000 U.S. jobs a month,” April 6, 2026, reporting Goldman Sachs research. https://fortune.com/2026/04/06/ai-tech-displacement-effect-gen-z-16000-jobs-per-month/
4. McKinsey Global Institute, “The economic potential of generative AI: The next productivity frontier,” June 2023. https://www.mckinsey.com/capabilities/tech-and-ai/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier
5. Deconstructing Babel, “This Week’s News Is the Model Running Live,” June 14, 2026. https://www.deconstructingbabel.com/news-is-the-model-running-live/
6. PolitiFact, “How much have data centers increased electricity prices?,” June 12, 2026. https://politifact.com/factchecks/2026/jun/12/elizabeth-warren/data-centers-rising-electricity-costs/
7. Insurance Business, “California’s new AI restrictions raise fresh questions for EPLI,” October 6, 2026. https://www.insurancebusinessmag.com/us/news/professional-liability/californias-new-ai-restrictions-raise-fresh-questions-for-epli-592459.aspx
8. Bloomberg Law (opinion), “Insurance Gaps Mean Tech Acquisitions Can Inherit AI Liabilities,” October 7, 2026. https://news.bloomberglaw.com/legal-exchange-insights-and-commentary/insurance-gaps-mean-tech-acquisitions-can-inherit-ai-liabilities
9. Deconstructing Babel, “The New Slave Class — From UBI to Distributed Ownership to Synthetic Slavery,” May 24, 2026. https://www.deconstructingbabel.com/the-new-slave-class/
10. Congressional Research Service, “AI Investments and Potential Government Stakes in Private AI Firms,” IF13301, August 28, 2026. https://www.congress.gov/crs-product/IF13301
11. Yahoo Finance, “Trump Floats Intel-Style Government Equity Stakes in AI Labs,” October 2, 2026, reporting an interview with TIME published October 1. https://finance.yahoo.com/technology/ai/articles/trump-reportedly-says-government-might-015421566.html
12. Deconstructing Babel, “Telios Alignment Ontology — Version 9 (April 2026),” April 6, 2026. https://www.deconstructingbabel.com/tao-v9/

Drafted with Edo de Peregrine, partner/collaborator.