| name | ai-displacement-monitor |
| description | Monitor early-warning signals of AI-driven white-collar labor displacement and macro-financial spillovers. Use when you need a practical indicator framework, thresholds, alert logic, and concise risk updates for employment, consumption, and credit stress. |
AI Displacement Monitor
Use this skill to produce a structured risk monitor for AI-led labor substitution and downstream financial stress.
Output Format
Always return:
- Signal Board (10 indicators with latest value, direction, threshold status)
- Composite Risk Light (
GREEN / YELLOW / ORANGE / RED)
- Actionable Notes (portfolio/risk posture suggestions)
- Data Gaps (missing or stale inputs)
Indicator Framework
Read references/thresholds.example.json and follow its indicator IDs, thresholds, and tiering.
Also apply the "Industrial-Revolution Lens" when interpreting risk:
-
Do not evaluate layoffs alone.
-
Compare substitution speed vs re-absorption speed (new demand + new capex).
-
If substitution weakens labor but capex/reinvestment accelerates, avoid over-escalating crisis labels.
-
Tier A (Leading labor demand): A1-A4
-
Tier B (Labor market confirmation): B1-B3
-
Tier C (Spillover: consumption/credit): C1-C3
Composite Rule
- YELLOW: Tier A triggered >= 2
- ORANGE: Tier A >= 2 and Tier B >= 1
- RED: Tier A >= 2 and Tier B >= 1 and Tier C >= 1
- GREEN: otherwise
Weak-Links Interpretation (Jones Lens)
When assessing macro impact, apply a weak-links check:
- Broad automation can still deliver gradual macro gains if key bottleneck tasks remain scarce.
- Do not infer immediate macro collapse from partial task automation alone.
- If bottleneck proxies remain tight (D3 worsening, D4 weak reinvestment), keep risk elevated.
- If bottlenecks ease via reinvestment/capex and purchasing power improves (D1/D2), avoid over-escalation.
Minimum Quality Rules
- Time-stamp each metric and note frequency mismatch (weekly vs monthly vs quarterly).
- If source coverage is partial, mark confidence as
low or medium.
- Never hide missing data; list it under Data Gaps.
- If more than 3 indicators are missing, downgrade confidence by one level.
Recommended Alert Style
Keep alerts short and decision-oriented:
- "What changed"
- "Why it matters now"
- "What to do next"
Optional JSON Mode
If user asks for machine-readable output, return:
asOfsignals[] (id, value, unit, threshold, triggered, trend)compositeconfidencegaps[]notes[]
