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To prepare for potential mass displacement of white-collar jobs by AI, California is experimenting with "employment insurance," a Danish model where the state pays employers to retain workers during transitions. This proactive approach focuses on preventing unemployment rather than just providing benefits after a layoff.

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With over half of new startup pitches focusing on AI automating existing jobs, the primary solution to this massive displacement is not retraining, but fostering an ecosystem that aggressively creates new companies, new industries, and consequently, new roles.

AI will inevitably cause mass, short-term job displacement. To prevent a depression from collapsed consumer spending, Universal Basic Income (UBI) is essential. It acts as a bridge, sustaining demand and allowing society to benefit from AI's productivity gains while new industries emerge.

AI is more than a tool for modernizing government services. It's a disruptive force that changes society's needs, compelling government to ask if its existing programs are even the right ones. For instance, is unemployment insurance the correct response to permanent, AI-driven job displacement?

To manage AI's labor impact, former Commerce Secretary Gina Raimondo proposes a "grand bargain." This includes tax code reforms to reward companies that reinvest AI-driven savings into job creation, worker retention, and entry-level hiring, shifting focus from pure efficiency to opportunity.

The confident belief that AI's impact on jobs will "just work out" is dangerously naive. A more responsible approach, advocated by groups like Windfall Trust, is to use scenario planning. Just as governments plan for pandemics or cyber attacks despite their uncertainty, we must plan for worst-case economic outcomes from AI.

High-paid white-collar workers losing jobs to AI may not file for unemployment insurance (UI). The benefits are often too low to be meaningful for them, and the application process is cumbersome. This could mean that official UI claims data is understating the true extent of labor market softening in professional services industries.

Faced with mass job loss from AI, governments are unlikely to seize assets from the wealthy. The politically easier path is to print massive amounts of money for social support, preserving the existing capital structure while devaluing the currency.

Rather than just destroying jobs, AI could make starting a business dramatically easier, leading to a boom in entrepreneurship. Raimondo proposes policies like allowing laid-off workers to collect unemployment while starting their new venture to facilitate this transition.

The potential rise in unemployment from AI will not happen in a vacuum. Central banks and governments are expected to use tools like interest rate cuts, unemployment benefits, and targeted spending to stimulate the economy, thereby shortening and reducing the severity of any labor disruption.

The consensus in Congress is not to regulate AI to prevent job loss, which is seen as implausible. Instead, the focus is on proactive investments to manage the transition and ensure people have financial stability, with ideas like universal healthcare emerging as alternatives to UBI.