ClawHub

AI Displacement Monitor

Other

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.

Install

openclaw skills install ai-displacement-monitor

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:

  1. Signal Board (10 indicators with latest value, direction, threshold status)
  2. Composite Risk Light (GREEN / YELLOW / ORANGE / RED)
  3. Actionable Notes (portfolio/risk posture suggestions)
  4. 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:

  • asOf
  • signals[] (id, value, unit, threshold, triggered, trend)
  • composite
  • confidence
  • gaps[]
  • notes[]