Navigating AI's Impact on Employment and Inequality: A Call for Pro-Worker Policies
AI development is increasingly viewed as a crossroads between two potential futures: one that prioritizes automation and mass layoffs, negatively impacting workers, and another that upskills employees and preserves jobs, according to MIT economist Daron Acemoglu.
Forecasts paint a concerning picture: AI could eliminate approximately 50% of entry-level white-collar jobs within 1 to 5 years, as per Dario Amodei, and Bernie Sanders warns that up to 97 million U.S. jobs may be replaced over the next decade.
To address these challenges, proposed policy responses include expanded retraining programs, free community college, universal health coverage, a four-day workweek with the same pay, and stronger unemployment insurance. Universal basic income is considered insufficient on its own to meet most workers' needs.
Funding these safety net enhancements would require higher taxes on the ultra-rich, aiming to support health coverage and retraining initiatives.
The article stresses the importance of giving workers a voice in AI development. Although Biden-era policies involved labor discussions, they did not result in regulatory measures to minimize layoffs. These efforts were later undone by a Trump administration executive order that blocked state AI restrictions.
A model inspired by Germany and Scandinavia's cooperative industry-labor-government approach is highlighted as a guiding blueprint for pro-worker AI policy. The historical example of Roosevelt-era government intervention during electrification underscores the potential for successful public-sector leadership.
The piece warns that without protective measures, AI could exacerbate income inequality by concentrating wealth among investors and tech executives, potentially creating a new underclass.
Ultimately, the author calls for a grassroots movement to pressure lawmakers and tech companies to ensure workers have a say in AI's future and to strengthen the social safety net for those displaced or affected.
