How efficient your workforce is and how quick they learn and adapt, makes them resilient to face the impact of change
By Kiran N. Kumar
In a peer-reviewed publication, a team from the University of Pittsburgh found that the German workers were not taking to substance abuse as their American counterparts after robots replaced them in the work environment.
While automation truly enhances productivity and reduces accidents, it was found more harmful to the mental health of human co-workers, suggests the study published last week in Labor Economics from Pitt economist Osea Giuntella.
Rania Giuntella, co-author of the study from Kenneth P. Dietrich School of Arts and Sciences says, “On one hand, robots could take some of the most strenuous, physically intensive, and risky tasks.”
“On the other hand, the competition with robots may increase the pressure on workers who may lose their jobs or be forced to retrain. Of course, labor market institutions may play an important role, particularly in a transition phase.”
Crucial transition phase
These findings reiterate the need for a transition process before robots or Artificial Intelligence (AI) take over most of the jobs, making humans redundant and resilient in work places.
In the US, more people working alongside robots had resulted in a significant increase of 37.8 cases per 100,000 people in drug or alcohol related deaths, besides a slight increase in suicide rate and mental health issues.
When researchers investigated the effects of robotics on workers in Germany, they did not find significant mental-health change due to robotics.
So, the imminent question follows: Why does American automation at work seem to result in much more negative outcomes than in Germany?
“Robot exposure did not cause disruptive job losses as Germany has a much higher employment protection legislation,” Giuntella explains.
Read: Good bots vs bad bots: In elections, who decides what? (June 22, 2022)
“Our evidence finds that, in both contexts, robots have a positive impact on the physical health of workers by reducing injuries and work-related disabilities.”
“However, our findings suggest that, in contexts where workers were less protected, competition with robots was associated with a rise in mental health problems.”
Giuntella, who has studied the effects of robotics on economic stature and marital lifestyle, however, offers no quick-fix solution.
“There has been an intense debate on the effects of robotics and automation on labor market outcomes, but we still know little about how these structural economic changes are reshaping key life-course choices,” he said.
Choice after job loss
Last year, McKinsey Global Institute predicted that 45 million Americans or one-quarter of the workforce would lose their jobs to automation by 2030, accentuated by Covid-19 pandemic and the possibility of recession.
But optimists argue that automation being constant, loss of jobs remain a temporary phase since new inventions create new markets and new jobs. The opponents point out that the robot job apocalypse scenario due to AI is advancing so quickly that replacement jobs won’t keep pace.
Another McKinsey report estimates that the loss of jobs could be 27%, but after diversifying the workforce into new roles, the effective job losses could only be 9%. Still it is high enough not to be discarded easily.
Here, the solution shown should not be isolated to mental impact on the labor force but in German resilience that could be gleaned from the study.
The German worker could adapt to change quickly, but his American counterpart did not. Efficiency of Germans being what it is, American workers are seeking a protective shield instead, in the form of a government bailout or income protection.
No wonder, a solution offered by Andrew Yang, who was a candidate in the 2020 Democratic Party presidential primaries and the 2021 New York City Democratic mayoral primary, becomes contextual here. He proposed that lack of jobs should entail all Americans to a $1,000 monthly government income.
Is it a solution? In a scenario of 100-meter race, an Olympic runner takes 6 to 7 seconds but an ordinary runner takes more than 20 seconds.
Efficiency matters! How efficient your workforce is and how quick they learn and adapt, makes them resilient to face the impact of change, whether from robots or AI. Unless this is addressed, a holistic solution remains far-fetched.