Increased income disparity
While AI is predicted to bring increased GDP per capita by performing existing jobs more efficiently and compensating for a decline in the workforce, especially due to population aging, the potential substitution of many low- and middle-income jobs could bring extensive unemployment.
ENTITY
2 - AI
INTENT
3 - Other
TIMING
2 - Post-deployment
Risk ID
mit617
Domain lineage
6. Socioeconomic and Environmental
6.2 > Increased inequality and decline in employment quality
Mitigation strategy
1. Investment in Human-AI Complementary Skills and Retraining Establish a robust, publicly funded AI Worker Training Fund (e.g., utilizing WIOA mechanisms) to support the development and delivery of subsidized, accessible retraining programs. These programs must focus on cultivating skills that complement AI—such as critical thinking, ethical reasoning, and complex problem-solving—and should offer financial stipends or integrate with unemployment insurance to ensure participation is feasible for displaced or at-risk low- and middle-income workers. 2. Progressive Fiscal Policy and Targeted Social Transfers Implement significant reforms to the national fiscal structure by expanding progressive taxation, particularly targeting wealth, property, and capital gains, to generate requisite public revenue. This funding must be strategically channeled to strengthen and broaden targeted social protection systems, including fully refundable tax credits (e.g., CTC, EITC) and cash transfer programs, thereby directly mitigating the income loss and poverty resulting from AI-driven job substitution. 3. Strengthened Labor Governance and Transparency for AI Systems Enact comprehensive regulatory frameworks that mandate high-risk AI systems used in employment decisions (hiring, performance, and termination) undergo recurring bias and societal impact assessments. Furthermore, strengthen existing labor laws to require employer transparency regarding the deployment of AI in the workplace and enhance workers' collective bargaining rights concerning the adoption and impact of automated decision-making systems to ensure equitable distribution of productivity gains.