A Plan to Stop AI from Automating Our Decline | Gina Raimondo | TED

To lead the global AI competition, America needs more than just plentiful energy, superior chips, innovative AI companies, and advanced models. A crucial, often overlooked, element is a comprehensive plan to prevent the displacement of millions of American workers. Failure to address this could lead to national decline through recession, social unrest, and political upheaval, ultimately resulting in excessive regulation that stifles AI innovation. The United States cannot genuinely lead in technological innovation if its people at home are struggling. A successful strategy requires both technological leadership and a human capital strategy that ensures everyone benefits from the AI economy. While the long-term potential of AI to create new jobs, industries, products, and services is optimistic, the immediate concern is the near-term disruption to workers. America's existing workforce and career transition systems are ill-equipped for this shift, with tens of millions of jobs potentially vulnerable across all demographics. This lack of preparedness is causing widespread anxiety among Americans, who deserve a concrete plan and action, not just empathy. Current proposed solutions, such as slowing or over-regulating AI, are detrimental as they deny Americans the benefits of AI and risk falling behind competitors like China. Similarly, universal basic income is not a viable solution because a job provides more than just a paycheck; it offers dignity, purpose, and pride, which are essential for a stable society. An effective transition plan, though not yet fully detailed, must be rooted in a new grand bargain between government and business. It requires dismantling the long-standing divide between education and employment, with industry playing a leading role in guiding the transition. The speaker emphasizes that with determination, this can be achieved. Massive changes are needed in both workforce training and career transition support systems. An effective workforce training system should be employer-led, with businesses defining current and future skill requirements. Schools and government training programs would then prepare individuals accordingly. The current system, which spends billions incentivizing college enrollment without regard for job outcomes or necessary skills, is inefficient. Government and schools often lack the up-to-date knowledge of employer needs that industry possesses. An example of successful collaboration is TSMC's expansion in Arizona, where tailored accelerated certificate programs and apprenticeships were developed with community colleges to meet the company's specific needs for skilled electrical engineers and equipment operators, leading to the large-scale production of AI chips. The "one-and-done" approach to education, where learning ends after high school or college, is unsustainable in an AI economy. Continuous learning and upskilling will be necessary throughout one's career as jobs constantly evolve. There is a need for more effective, affordable, and flexible options for continuous learning that allow individuals to earn while they learn. While excellent employer-led training, apprenticeships, and co-ops exist, they are currently a small fraction of the post-high school system and should become the norm, without any associated stigma. Beyond training, robust support for individuals during job transitions is essential. The current primary system, unemployment insurance, is outdated, designed for a different era of stable, long-term employment. It fails to support new training, business creation, or entry into new fields, and does not provide adequate income support for middle- and high-income earners. Instead, temporary wage support could be offered to help workers re-enter the workforce quickly by topping up salaries if they take a pay cut in a new field. Additionally, self-employment assistance programs could support workers in starting new businesses, leveraging AI's potential to simplify entrepreneurship. Imagine a 45-year-old accountant, typical of many Americans, who loses her job to automation. In a better system, her company would offer retraining months before layoff, potentially leading to a short-term credential for a higher-value skill and redeployment within the company. If needed, temporary wage insurance could bridge the income gap between her old and new salaries. Achieving this requires incentives, innovation, and urgency. Government funding for schools and training programs should be based on outcomes—whether people acquire valuable skills and secure jobs—rather than just enrollment numbers. Business incentives also need to change. The current system often rewards layoffs, making it too easy for companies to shed workers. A new system should make it more costly to abandon workers than to retrain them. Piloting tax credits or other economic incentives that reward companies for worker redeployment, entry-level hiring, and reinvesting AI productivity gains into new jobs is crucial. For decades, incentives have focused on investing in machines; now, they must equally encourage investment in people. A smooth transition to an AI economy benefits everyone. It is not a zero-sum game between business and workers, as recessions, excessive AI regulation, social unrest, and political divisiveness harm all. Realizing AI's potential is in everyone's interest; it's not corporate charity, as human consumers with money are essential for economic activity. America has faced similar economic transitions before, notably when manufacturing moved overseas, leading to millions of job losses and devastating communities. The speaker recounts his father losing his job at 56 after nearly 30 years, highlighting the pain and bitterness caused by a poorly planned transition. This past failure, which still impacts the country's divisive politics, involved a few million job losses. The current AI transition could affect tens of millions, necessitating a different approach. Despite these challenges, there is reason for optimism. History shows that when stakes are high, America reinvents itself. Post-World War II public investment spurred new industries, and recent crises like COVID accelerated growth in clean energy and healthcare. AI is a century-long technology demanding a century-long response to ensure all Americans benefit. If the country can design the best chips, create the best models, and invest trillions in AI infrastructure, it can meet this challenge. The future is not predetermined; it is ours to create.