Do Not Be Afraid: Machine Learning and the Future of Employment
Even a cursory glance at your daily newsfeed is certain to yield at least one doomsday article predicting the certain demise of our employment futures as a result of introducing highly intelligent, and sometimes self-reliant, technologies into the workplace. That’s right, I’m talking about Artificial Intelligence, or more specifically, Artificial Neural Networks taking our jobs.
Experts insist that Machine Learning technologies will result in human erasure — that highly intelligent “robots” will negatively disrupt our industries, driving job losses and mass unemployment. At the base of these predictions lies a central fear, one that’s been fed to us via science fiction for years: that our creations will soon outstrip us of any usefulness.
They’re right, right?
That is not to say that nothing will change. As many economists will report, this shift toward using technologies that do the work for us, and that can work 24/7, is going to result in job losses in many sectors as early as 2030. What many of these studies downplay, however, is the impossibility of forecasting how many jobs will be created because of these advancements.
Even fifteen years ago, position titles like Climate Change Adaptation Specialist, E-Commerce Analyst, and Social Media Manager simply did not exist. Nor could anyone predict how impactful technologies and trends like cloud-sharing and crowd-sourcing would be on job production. Recent trends in employment–aided by our aging population–predict higher spending, and therefore employment, in the health, education, sustainability, and renewable energy sectors. What’s more, employers are focusing less on hiring skilled workers, a concept referred to as “deskilling”, and more on investing in proper on-the-job training. This can only mean good things for those who commit to keeping an open mind about their future.
We can evolve, too.
What is simmering behind all the gloom, then, is the historical certainty that humans adapt quickly to new technologies, and train to remain useful as these technologies advance. I am reminded of the great lengths NASA’s Katherine Johnson, Dorothy Vaughan, and Mary Jackson went to ensure that they and their peers evolved their skills alongside the machines that threatened to replace them. Machine Learning technologies ultimately aid humans in creating connections, bettering our solutions, and helping us reorient ourselves to begin tackling bigger, more creative problems while allowing our friendly AI technologies to take on the more time-consuming tasks.
In freeing up more “labour-space”, or by allowing these technologies to work with us, employees will begin seeing themselves in more supervisory and training roles. This could mean higher wages (due to machine-learning efficiencies), and improved work atmospheres. In short, providers will be able to shift their existing workforce into roles that require new and exciting skill sets, helping alleviate the predicted losses that will come by adopting AI technologies.
So rejoice, and keep your mind open. At the very least, you’ll never have to come into work to find that a machine has stolen your vanilla creamer.