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6. Socioeconomic and Environmental2 - Post-deployment

Economic

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

Source: MIT AI Risk Repositorymit616

ENTITY

2 - AI

INTENT

1 - Intentional

TIMING

2 - Post-deployment

Risk ID

mit616

Domain lineage

6. Socioeconomic and Environmental

262 mapped risks

6.2 > Increased inequality and decline in employment quality

Mitigation strategy

1. Establish comprehensive, publicly and privately supported, lifelong learning and reskilling programs. These initiatives must be financially accessible and focused on cultivating human-AI complementarity skills (e.g., critical thinking, ethical reasoning, and domain expertise) to facilitate worker transition into new, high-value roles and to ensure workforce adaptability to technological change. 2. Modernize and strengthen the social safety net architecture to withstand AI-driven labor market volatility. This necessitates enhancing the portability of benefits (e.g., healthcare and retirement vesting), expanding flexible income support mechanisms such as monthly Earned Income Tax Credits, and exploring adaptive measures like Universal Basic Income pilots to provide economic stability for displaced workers. 3. Implement progressive fiscal policies and regulatory frameworks to ensure an equitable distribution of AI productivity gains. Key actions include utilizing progressive taxation models (e.g., on wealth or high incomes), reforming business tax codes to incentivize human capital investment over physical capital, and instituting labor reforms such as clarifying independent contractor status and promoting profit-sharing or displacement taxes.