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To manage the societal impact of automation, governments might require licenses for autonomous systems like self-driving delivery vehicles. These licenses could be capped and auctioned, providing a way to control the pace of job loss and generate public revenue.

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Fiscal incentives and monetary policy, such as suppressing long-term rates, have made it cheaper for AI companies to fund massive build-outs. This government-enabled environment accelerates the AI arms race, potentially exacerbating job displacement faster than natural market forces would allow.

China is halting the expansion of autonomous vehicle fleets. This move is viewed not as a reaction to technical failures but as a preemptive measure to prevent mass unemployment and social unrest among drivers. It foreshadows the political and labor-related battles that will likely emerge in the West over automation.

While the U.S. explores wealth redistribution schemes like UBI, China's initial approach makes it illegal for companies to fire employees whose roles are automated by AI. This forces firms to retain and find new tasks for workers, rather than shifting the burden to the state.

When confronting AI-driven job loss from technologies like Waymo's driverless cars, the policy framework is not to block innovation. Instead, it prioritizes managing the "collateral damage" by proactively developing retraining and alternative career paths before workers are fully displaced.

Governments will aggressively protect jobs from automation through policy, creating a significant but often overlooked barrier to AI's real-world deployment. This societal threshold for what we allow AI to do will be a more potent brake on progress than technological limitations, as seen with unions protecting dockworker jobs.

AR Rahman believes AI tools that can replace human jobs are a destructive force that must be regulated. He compares it to firearms, arguing that just as there are rules for ownership, there should be rules preventing the deployment of AI that makes entire skill sets worthless.

To handle the social unrest from AI-driven job displacement, governments are predicted to turn to a two-pronged approach. First, they will issue UBI-like payments to quell economic anxiety. Second, they will increase policing to control the inevitable fear and anger.

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.

Sam Altman outlined a new social contract for the AI age, suggesting a tax on automated labor (robots and AI) instead of human income. This revenue would fund a public wealth fund, providing citizens with an 'AI dividend.' This proactive policy aims to ensure the public broadly benefits from AI-driven productivity gains, not just company owners.

The massive valuations of AI companies aren't just based on technological potential; they are fundamentally tied to the economic value unlocked by displacing millions of jobs. This direct link between AI's value and its societal disruption justifies policies that capture and redistribute some of that value to cushion the blow for displaced workers.