Robots, Automation & Jobs
Machines have been taking our jobs forever. But Economists, as practitioners of the " dismal science", have always been upbeat about that. Sure, machines destroy jobs. But, for new industries that new technology enables create even more new jobs. There may be a bit of disruption between destruction and creation, but that's Capitalist's business as usual.
We have lived through the stage, call as Automation 1.0. A typical example - car manufacturing. Henry Ford's production line to change into Toyota's machine and as a consequence where few humans are visible on an assembly line. Once upon a time, car industry employed thousands of people called as Blue collar workers. Now, it employs far fewer. The Robots did take their jobs.
In some cases, those made redundant found other jobs but many didn't. Some times, communities were devastated as a result. But, GDP went up, so Economists were happy.
Now, we are beginning on automation 2.0. This is largely driven by technologies employing machine learning (ML) and big Data, what we misleadingly call "Artificial Intelligence". The types of job it targets are different from those addressed by Automation 1.0. They have some cognitive content but also a lot of routine. We call them as White collar jobs, and new machines often do them well, which may explain why people are beginning to be more agitated about the widespread deployment of technology than they were about Automation 1.0. This displacement will not be evenly distributed
around the world or within the countries. We are learning about digital technology is that in almost
every area of its deployment it has become an amplifier of inequality. The tech companies that control it employ almost no one in comparison either to their profits or to non-tech companies of comparable size and scale.
The negative effect of robotization are disproportionately felt in the lower-income regions of the globe's major economies - on average, a new robot displaces nearly twice as many jobs in lower- income regions compared with higher-income regions of the same country.
At a time of worldwide concern about growing levels of economic inequality and political polarization, this finding has important social and political implications. Automation 2.0 is likely to be very profitable for the companies that deploy it, but it will be Governments that will be left to pick up the pieces. Some progress.
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We have lived through the stage, call as Automation 1.0. A typical example - car manufacturing. Henry Ford's production line to change into Toyota's machine and as a consequence where few humans are visible on an assembly line. Once upon a time, car industry employed thousands of people called as Blue collar workers. Now, it employs far fewer. The Robots did take their jobs.
In some cases, those made redundant found other jobs but many didn't. Some times, communities were devastated as a result. But, GDP went up, so Economists were happy.
Now, we are beginning on automation 2.0. This is largely driven by technologies employing machine learning (ML) and big Data, what we misleadingly call "Artificial Intelligence". The types of job it targets are different from those addressed by Automation 1.0. They have some cognitive content but also a lot of routine. We call them as White collar jobs, and new machines often do them well, which may explain why people are beginning to be more agitated about the widespread deployment of technology than they were about Automation 1.0. This displacement will not be evenly distributed
around the world or within the countries. We are learning about digital technology is that in almost
every area of its deployment it has become an amplifier of inequality. The tech companies that control it employ almost no one in comparison either to their profits or to non-tech companies of comparable size and scale.
The negative effect of robotization are disproportionately felt in the lower-income regions of the globe's major economies - on average, a new robot displaces nearly twice as many jobs in lower- income regions compared with higher-income regions of the same country.
At a time of worldwide concern about growing levels of economic inequality and political polarization, this finding has important social and political implications. Automation 2.0 is likely to be very profitable for the companies that deploy it, but it will be Governments that will be left to pick up the pieces. Some progress.
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