One of the ways presidential candidate Donald Trump appealed to workers across America in 2016 was by promising them that he’d bring back jobs. The promise was appealing. Over the last few decades, automation has swept through industrialized areas and displaced thousands of blue collar workers.
While many technologists believe that automation is a solution for the country's economic problems, one that actually creates new jobs and pushes the economy forward, there are two sides to every story. Brian Alexander, author of "Glass House: The 1% Economy and the Shattering of the All-American Town," says that he’s seen factory workers in his home state of Ohio struggle to adapt to new technologies. And as robots took on more factory jobs, they were left feeling “increasingly disposable.”
Indeed, automation’s ripple effects have transformed small towns economically, socially, and politically.
Alexander had written about American culture for decades, and when he went back to visit his hometown in Lancaster, Ohio, it didn’t take him long to discover that the Ohio of his childhood had changed. The social cohesiveness of small towns, like Lancaster, had eroded. And it wasn’t the first time he’d seen this happen — he says that it’s a trend that’s been spreading across the country since moves towards automation accelerated in the 1970s and ‘80s.
Although it’s been 10 years since the last recession, Alexander argues that many folks in Ohio have just started to recover. Training initiatives have helped workers learn new skills that are allowing them to adapt to the market’s needs, and work with (and manage) robots. People with such skills are in high demand. But Alexander says that people are still fearful of losing their jobs, as technology continues to change.
“The ground has shifted under their feet,” Alexander says, which may help explain why the state voted for Trump, who promised to bring jobs, economic stability, and a shake-up in trade.
Aceel Kibbi is an intern at Innovation hub. You can follow her on Twitter: @aceelkibbi