"President Donald Trump broke through the "blue wall" of Pennsylvania, Wisconsin and Michigan as rust-belt voters agreed with his campaign messaging that they'd been "ripped off" and "taken advantage of" and the system had been rigged against them. Decades of promises from politicians in both parties who negotiated free-trade deals hadn't panned out, and groundbreaking work from economists David Autor, David Dorn, and Gordon Hanson gave the era a name: "the China shock.""
"Even JPMorgan CEO Jamie Dimon recently admitted, in an onstage appearance with Anthropic CEO Dario Amodei, that the government's post-NAFTA promise to reskill manufacturing workers "didn't work," saying "it wasn't set up right." But Dimon expressed optimism that government and business can work together better this time, somehow."
"Count Bhaskar Chakravorti, dean of global business at Tufts University, as a skeptic. He just mapped out the American AI Jobs Risk Index, a model tracking the geography of jobs most vulnerable to AI automation across 784 occupations and he's certain that the "Rust Belt" of the China shock era is getting a "wired belt" in the AI era. According to Chakravorti's index, 9.3 million American jobs are vulnerable to AI automation, amounting to a projected $200 billion in lost income."
"But in an extreme scenario where AI is able to replace a larger share of labor, that figure rises to $1.5 trillion. Most of those are concentrated in just a handful of metros, according to Chakravorti. "There are 14 knowledge-driven metros that range from the whole San Jose area to the Raleigh-Durham area to big cities like New York or Seattle or Boston," he told Fortune. "They face 3.6 times the job loss and over five times the income loss of the traditional sort of manufacturing and tasks.""
In 2016, voters in Pennsylvania, Wisconsin, and Michigan shifted away from the prior political alignment, influenced by messaging that they had been exploited and that the system was rigged. Free-trade promises and the “China shock” framing connected economic disruption to manufacturing job losses. Acknowledgment from JPMorgan’s CEO indicated that post-NAFTA reskilling efforts for manufacturing workers did not work as intended. Bhaskar Chakravorti developed an American AI Jobs Risk Index covering 784 occupations to map jobs vulnerable to AI automation. The model estimates 9.3 million jobs at risk, with projected lost income of about $200 billion, rising to $1.5 trillion under an extreme replacement scenario. Risk is concentrated in a limited set of knowledge-driven metros, which face substantially higher job and income losses than traditional manufacturing areas.
Read at Fortune
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