Resources for policymakers, advocates, and community organizers responding to AI-driven labor displacement.
This section presents evidence about policy responses to AI-driven labor displacement. It does not advocate for specific legislation or endorse particular policy positions. Evidence strength ratings reflect the quality and quantity of supporting research, not political feasibility.
Quick Report (single ZIP)
Create a one-page report on AI labor displacement risk for your area — the fast path for a one-page report on one metro. Useful for briefings and advocacy.
Custom Report Builder
Build a multi-metro, multi-indicator PDF + CSV report. Select up to 12 metros and any combination of indicators. Inspired by KFF State Health Facts' Custom State Reports.
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Policy Interventions
Evidence-based policy responses to AI-driven labor displacement, organized by type.
Grade
Study count
Design
Replication
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Workforce Reskilling Programs
Evidence: Strong ⓘ
Government-funded retraining programs for workers displaced by automation. Examples: Singapore's SkillsFuture, Germany's Kurzarbeit, US WIOA programs.
Income supports during retraining: Stipends or UI extensions for workers in training programs
Industry-recognized credentials: Stackable certifications aligned with AI-resistant occupations
Employer tax credits: Incentives for companies that invest in reskilling rather than replacing
AI workforce legislation from state legislatures, manually curated with last-verified dates.
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How this data is collected
Data is manually curated from state legislature websites and Congress.gov. Last verified dates indicate when we confirmed the bill status. Legislative status changes frequently — verify with the source before citing.
Federal Workforce Programs
Federal programs relevant to AI-driven labor displacement and workforce transition.
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How this data is sourced
Program data is sourced from official government websites. Funding levels are approximate annual figures.
Framing the evidence
Talking Points
Key messages for engaging with policymakers, employers, and the public on AI labor displacement.
Labour-market stress in AI-exposed occupations is measurable today; this dashboard tracks it. Attribution to AI specifically is not established.
Early warning indicators give us time to prepare, but only if we act on them.
Reskilling works — but it requires sustained investment and income support during transition.
Augmentation-focused AI adoption (AI as tool) outperforms replacement-focused strategies for both workers and employers.
Data for Advocacy
Use our data to support your advocacy work. All data is public and downloadable.