It remains difficult to predict just how much artificial intelligence will affect a growing range of jobs. In what might prove to be an optimistic outcome, machine learning, artificial intelligence, and robotic automation will likely mean 16 percent of U.S. jobs will disappear by 2025, some estimate.
However, such technologies will also create new jobs, such as robotic engineers and technicians, data scientists, and content curators, amounting to a nine percent job increase to 2025, Forrester Research now estimates.
Optimistically, humans will be left with more “person to person” jobs and “higher value” work.
On the other hand, such forecasts might prove, at least in some cases, to be too pessimistic. Many made the same predictions when automated teller machines were widely adopted in the 1990s.
But banks also shed about 25 percent of people in the back office staff.
Forrester Research forecasts a net job loss of seven percent. Office, sales, and administrative support jobs will be "the most rapidly disrupted", says Forrester.
The number of white collar office workers, of which there are 89 million in the U.S., is forecast to decline by 12 percent between now and 2025.
Nor are gains and losses equally distributed. When economies evolve, it very often happens that gains are reaped by one segment of citizens or workers, while others are harmed.
Few likely really believe that when steel mills and auto plants are shut down that workers actually wind up in new high-paying jobs in growing industries. There might be winners, but there surely are losers.
Eventually, one has to wonder how machine learning and artificial intelligence will affect many jobs in the communications business, beyond the simple matter of firms needing to reduce operating and capital costs that almost necessarily require job cuts.
How much of the complexity and difficulty of buying and using communication-related services will be made much easier as we apply AI to the process of creating, delivering and selling services?
Nor are gains and losses equally distributed. When economies evolve, it very often happens that gains are reaped by one segment of citizens or workers, while others are harmed.
Few likely really believe that when steel mills and auto plants are shut down that workers actually wind up in new high-paying jobs in growing industries. There might be winners, but there surely are losers.
Eventually, one has to wonder how machine learning and artificial intelligence will affect many jobs in the communications business, beyond the simple matter of firms needing to reduce operating and capital costs that almost necessarily require job cuts.
How much of the complexity and difficulty of buying and using communication-related services will be made much easier as we apply AI to the process of creating, delivering and selling services?
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