Source library

Sources on AI job displacement and workforce transition

displacement.ai should earn trust by separating cited evidence from modeled assumptions. This source library is the public trail for research, official statistics, and labor-market signals behind the platform.

Source policy

Every public claim should name the source, geography, publication date, data vintage, and limitation. Model scores should carry a version and confidence label so readers can distinguish observation from inference.

  • World Economic Forum: Survey-based projections reflect employer expectations, not realized displacement.
  • International Labour Organization: Exposure estimates do not directly predict layoffs or wage outcomes.
  • McKinsey Global Institute: Scenario analysis depends on adoption timing, demand growth, and occupational transition assumptions.
  • OECD: Automation-risk framing varies by country, institution, and workplace implementation.
  • US Bureau of Labor Statistics: Wage and employment figures are historical labor-market measures, not AI-specific forecasts.
  • O*NET: Task descriptions require modeling to translate into AI exposure and displacement pressure.