What if robots displace much of the service-sector workforce?
Service-sector displacement is a stagflationary-for-labor mix: automation beneficiaries (Nvidia/Tesla) rise while consumer-credit spreads widen and discretionary spend softens as displaced workers retrench. The market has no clean labor-displacement analogue yet; the capex-beneficiary leg rhymes with the 2023 AI rerating, but the consumer-credit leg is the novel, under-priced risk. Forward angle: the cascade keeps semis bid, but if displacement is fast enough to dent aggregate demand, the consumer-credit and subprime-auto channel dominates — fade the 'productivity is pure positive' framing.
how we built this number — every step
The class rate is measured from our dated, sourced event library (decade-normalized Poisson — the full table is public at base_rates.json). The variant’s share within its class is the analyst’s editorial call, published so you can audit it. A wider range means thinner precedent. Full recipe: methodology · scored at Reality Check.
The butterfly cascade
How this trigger trickles across markets, left → right — the root shock, its first‑order moves, then the ripple effects. Drag any node; tap a market for its real price history.
Resolution timeline — how this probability is moving
Our model's odds (gold) over time vs the crowd's (Polymarket, blue), from the past toward the 1–3 years horizon. Each dot is a real macro event that nudged the probability — green pushed it up, red pushed it down. Tap a dot for the source. The gold path is an illustrative reconstruction anchored to today's estimate — real dated events, not a live re-estimate history.
What it would mean
If this plays out, it is a risk-off shock. Robots replace a large share of fast-food, retail and logistics jobs, spiking sector unemployment. The trigger decomposes into signed root‑shocks — Job displacement ▲ · Robotics productivity ▲ — which propagate through our causal graph to the markets below.
If it happens — the markets it would move
Biggest moves first. Projected moves are cascade-model priors; hist A–B% = what comparable past events actually did (measured abnormal returns), and model prior · unmeasured marks markets with no analogue backing yet. Tap any market for its price history.
| Market | Class | Projected move | |
|---|---|---|---|
| 1 | Nvidia NVDAon Hyperliquid 📈 chart | Equity | ▲ +0.8% hist -1.63–+4.35% · other way -3.19% (n=12) |
| 2 | Semiconductors SMHon Hyperliquid 📈 chart | Equity | ▲ +0.4% hist -0.01–+0.61% · other way -0.28% (n=12) |
| 3 | MicroStrategy MSTRon Hyperliquid 📈 chart | Equity | ▼ -0.5% hist -8.28–+21.77% · other way +11.68% (n=12) |
| 4 | Solana SOLon Hyperliquid 📈 chart | Crypto | ▼ -0.4% hist -16.07–+0.71% · other way +5.03% (n=12) |
| 5 | AMD AMDon Hyperliquid 📈 chart | Equity | ▲ +0.3% hist -2.51–+0.55% · other way -0.96% (n=12) |
| 6 | Broadcom AVGOon Hyperliquid 📈 chart | Equity | ▲ +0.3% hist -0.53–+1.79% · other way -0.43% (n=12) |
| 7 | Micron MUon Hyperliquid 📈 chart | Equity | ▲ +0.3% hist -7.29–+1.98% · other way +0.87% (n=12) |
| 8 | TSMC TSMon Hyperliquid 📈 chart | Equity | ▲ +0.3% hist -0.07–+0.61% · other way -1.8% (n=12) |
| 9 | Marvell MRVLon Hyperliquid 📈 chart | Equity | ▲ +0.3% hist -0.15–+0.25% · other way +0.5% (n=12) |
| 10 | Hyperliquid (HYPE) HYPEon Hyperliquid | Crypto | ▼ -0.3% model prior · unmeasured |
| 11 | ASML ASMLon Hyperliquid 📈 chart | Equity | ▲ +0.3% hist -5.21–+0.51% · other way -2.54% (n=12) |
| 12 | Qualcomm QCOMon Hyperliquid 📈 chart | Equity | ▲ +0.3% hist -3.57–+0.81% · other way -1.82% (n=12) |
| 13 | Volatility (VIX) VIXon Hyperliquid 📈 chart | Vol | ▲ +0.3% hist -0.06–+0.55% · other way +0.67% (n=12) |
| 14 | Ether ETHon Hyperliquid 📈 chart | Crypto | ▼ -0.3% hist -1.84–+0.67% · other way +2.67% (n=12) |
Probable recommendation
Why we may diverge from history
Trust the cascade long on ASML/AMD: the -5.3%/-2.9% is AI-capex/Fed-reprice contamination, off-channel for a robot-displacement shock; but SPX's clean +1.5% (0.77) warns the index short is the weaker leg.
Historical precedent — what analogous events actually did
Across 24 analogous events (overlap‑weighted), as abnormal returns — market beta stripped, so it's the event's own effect, not the market backdrop. Shown at 20 days (persistent) and 5 days (immediate); ↺ fades = the two horizons disagree. Confidence = consistency × sample × significance.
| Asset | History says | Abnormal (20d · 5d) | Hit | n | Confidence | vs cascade |
|---|---|---|---|---|---|---|
| SOL SOL | SHORT | -12.3% · 5d -6.4% | 85% | 19 | 0.51 | ✓ matches cascade |
| ASML ASML | SHORT | -4.2% · 5d -2.6% | 79% | 23 | 0.43 | ⚠ differs |
| SPX SPX | LONG | +1.6% · 5d +0.4% | 76% | 24 | 0.41 | ⚠ differs |
| INTC INTC | SHORT | -3.6% · 5d -3.5% | 68% | 24 | 0.35 | ⚠ differs |
| AMD AMD | SHORT | -2.2% · 5d -1.6% | 72% | 24 | 0.34 | ⚠ differs |
| Gold XAU | LONG | +1.8% · 5d +0.1% | 71% | 23 | 0.34 | · |
| QCOM QCOM | SHORT | -3.1% · 5d -2.2% | 71% | 23 | 0.30 | ⚠ differs |
| MU MU | SHORT | -6.5% · 5d -4.2% | 67% | 23 | 0.26 | ⚠ differs |
| XLK XLK | SHORT | -0.2% · 5d -0.4% | 67% | 23 | 0.24 | ⚠ differs |
| US dollar DXY | SHORT | -0.4% · 5d -0.3% | 64% | 24 | 0.23 | · |
| High-yield credit HYG | SHORT | -0.5% · 5d -0.0% | 65% | 22 | 0.22 | ✓ matches cascade |
| MSTR MSTR | LONG | +20.5% · 5d +2.7% | 58% | 23 | 0.16 | ⚠ differs |
| 10y yield DGS10 | LONG | +8bp · 5d +0bp | 60% | 24 | 0.16 | · |
| MRVL MRVL | SHORT | -0.3% · 5d -0.0% | 58% | 23 | 0.13 | ⚠ differs |
Why this probability
Deployment early; large measurable sector-unemployment spike from robots unlikely this fast. A base‑rate‑anchored prior, continuously scored against what actually happens — not a forecast.