How likely is an AI bust, and how bad would it be?
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The odds
Cumulative probability, median of the pooled estimate. The bar shows the 10th to 90th percentile range.
How the headline odds have moved
Economic bust by end-2028Market crash by end-2028
View as table
Why four methods, and why they disagree
By end-2028. Each method is an independent estimate and the headline pools them. Credit markets are usually the outlier on the bust.
Economic bust
Market crash
If a bust happens
Two damage models, weighted by the odds above. Figures are averages over all shock draws, not conditional on a bust, so they understate losses in a deep one.
Neocloud debt maturity wall ($B)
Model D and Model F in short
- Model D: 12-sector contagion network with legal friction. Fat tail, with a cliff above a shortfall of roughly 22 to 25%.
- Model F: weekly agent-based model of firms with nine switchable mechanisms. Contracts and rescues cap the tail.
- “S&P 500 down 30%” in Model F is a synthetic index, not the real one.
Inputs and data sources
Inputs fed to the models
Data sources
Credit spreads, option-implied volatility, lab revenue and neocloud backlog have no free feed. They come from manual_inputs.json and are marked manual. Model G stays at its paper calibration.
What to keep in mind
- The odds rest on stated judgment calls: when the boom started, how a shortfall maps to Model F, how strongly the Fed and sovereign buyers respond.
- Model F ablations are noisy and only loosely paired across seeds, so small differences mean nothing.
- Model F’s no-shock baseline is not quiet: some seeds lose money even at zero shock.
- The live fetchers have had limited real-server history. Check the source table for stale or failed feeds.
- Credit spreads, implied volatility, lab revenue and backlog are manual inputs.