4 days ago
AI And The Future Of Work: Andrew Yang's Caution Vs. Labor's Optimism
Andrew Yang, technology policy advocate and former presidential candidate, has been sounding alarms about automation's impact for years. At the Ai4 conference in Las Vegas, he was interviewed by Nancy Scola on his views of AI and universal basic income, while at another session, Taylor Stockton, Chief Innovation Officer at the U.S. Department of Labor shared the administration's plans to deal with AI and workforce disruption.
The two offered sharply different takes on how artificial intelligence is reshaping the workforce, and what should be done about it. While Yang urges caution on AI-accelerated job disruption, Stockton says those predictions are missing the bigger story. Both see AI reshaping the labor market. They just disagree on what's needed to support the changing labor market.
Yang: The Displacement Is Already Happening
Yang doesn't speak in hypotheticals. He says CEOs have told him directly they've frozen hiring and started layoffs because AI tools are now doing work once assigned to humans. That shift isn't theoretical. It's already showing up in revised job numbers. From May to July, the bulk of new jobs came from healthcare, an industry still difficult to automate. Other sectors are seeing a slow drain.
In his words, a 'tidal wave' is rolling through the economy while Washington stands 'inert or unresponsive.' He expects millions in call centers, retail, and food service to be hit, along with white-collar professionals who assumed they were safe.
'Anyone who thinks that the white-collar blood bath is nonsense is going to be wrong,' he said, warning it may only take months for skeptics to see the scale.
The human cost, Yang added, doesn't always make headlines. 'If you're a 50-year-old executive who has lost a job, that's not a really sympathetic narrative to the population at large,' he noted. 'But that's a real impact for the family, and then you multiply that times 100,000 and we have a real problem.'
His solution is to share the gains. If AI drives GDP per capita from $82,000 into six figures, part of that should reach households directly. He points to universal basic income and expanded child tax credits as ways to keep people afloat during upheaval.
For Yang, it's not just about paychecks. Once the link between effort and reward breaks, he says, people stop trying. Younger generations, he warns, are already showing drops in conscientiousness and agreeableness. Some of that, he fears, can't be reversed.
US Department of Labor: AI as an Engine for Opportunity
Stockton's starting point is different. He doesn't buy into visions of empty offices and shuttered plants. 'The fear of mass job displacement is deeply overstated,' he says. History shows that major technology shifts, from mechanized farming to the Internet, ended with more jobs, not fewer. AI, in his telling, is following a similar pattern.
He points to roles emerging right now such as AI prompt engineers and governance analysts, many of which don't require a traditional degree. In healthcare, AI is producing clinical notes so physicians can spend more time with patients. On factory floors and construction sites, sensors catch hazards before they become accidents.
The Department of Labor's plan hinges on agility, tracking AI's impact on jobs in real time, using that data to adjust policy, and running pilot programs for rapid retraining. Stockton wants apprenticeships to become a core path into careers, targeting one million active placements in critical fields such as advanced manufacturing and AI infrastructure. He also wants AI literacy baked into education from K-12 to adult retraining.
Stockton shared an emphasis on apprenticeships and alternatives to the traditional 4-year college education as a path to relevance in the AI-powered economy. A study he cited showed 52 percent of the Class of 2023 unemployed or underemployed a year after graduation.
'The College for All movement has failed,' he told the audience. 'A bachelor's degree no longer guarantees access to professional employment. Apprenticeships offer a faster, debt-free alternative…and combine paid job experience with training that directly maps to employer needs.'
The federal approach isn't just reactive. In July, the White House released the 'America's AI Action Plan,' a 90-point blueprint under three main headings: Accelerating AI Innovation, Building American AI Infrastructure, and Leading in International AI Diplomacy and Security. It calls for streamlining permits for data centers and chip plants, strengthening the electric grid, creating regulatory sandboxes, and exporting a full-stack AI package to allies, while keeping U.S. values embedded in the technology. Stockton sees the plan as a wind at the back of his workforce push.
Common Ground, Clear Differences
Both Yang and Stockton agree AI's advance is fast and the pace will unsettle certain jobs. They see healthcare and other people-focused work as relatively safe for now. Both stress that while AI can handle parts of a process, people must decide what the system should aim for.
Where they diverge is in the first move. Yang wants immediate income support to keep families stable while the market finds its footing. Stockton believes the priority is rapid adaptation including AI literacy, nimble training programs, and routes into new careers. Yang points to struggling college grads and laid-off mid-career workers. Stockton thinks some of those losses are more about post-pandemic corrections or strategic shifts than about AI alone.
Studies fuel both arguments. McKinsey pegs the annual global productivity boost from generative AI at up to $4.4 trillion. PwC reports that jobs exposed to AI have grown 38 percent in the U.S. since the tech's arrival, though roles with less exposure have grown faster. News stories document both companies replacing whole teams with AI systems and companies using AI to amplify human work.
In high-risk industries, AI has improved safety and output, which mirrors Stockton's vision in action. In customer service or routine analysis, AI is consolidating headcount, exactly what Yang warns about.
What's Likely Ahead
Over the next five years, productivity gains are likely to show up before job growth does. Companies that adopt AI early will push output higher without adding staff. Jobs will keep blending human skills with AI tools, making Stockton's AI literacy agenda more pressing. And if wages lag profits for too long, political pressure for income-based solutions could build quickly.
Both men see high stakes. Stockton imagines a workforce ready to keep pace. Yang doubts the system can pivot fast enough. A blended strategy including training and adaptation alongside income support could prove the safest bet. Whether it's adopted may depend on whether policymakers, business leaders, and educators can keep up with the technology's acceleration.
AI isn't waiting. Neither can the people whose jobs it touches.
