The concept of work is getting re-worked. As automated technology continues to replace human labor, the traditional definition of "average" work is becoming outdated. The skills required to get and keep a job are changing dynamically and continuously. With technological progress occurring at record rates, success at any level of work is increasingly defined by how well you work with machines.
Marc Pensky, who coined the term "digital immigrant" in 2006, described our current work environment quite eloquently when he told CNN, "People will always be behind now, and that will be a stress they have to cope with." That stress is prominent for Baby Boomers and Generation X who experienced changing technology only as professional adults. For at least the last decade, their perception has been that the pace of technology was too fast.
But here's the thing. While Millennials and Gen Z may be more comfortable with technology, the pace of change is disrupting everyone's world. Exponential change doesn't play favorites. It's blind to age, gender, and the color of your skin. Consequently, the bar for even low jobs is being raised and "average" skills qualify workers for a small and shrinking subset of jobs, along with smaller paychecks. Compounded by the slowing growth of semi-skilled work, the once average worker is quickly facing the dubious options of becoming a low-skill, low-pay worker or unemployed.
Keeping Up with the Rate of Change
Many workers not only lack the right set of skills, but the ones they currently have are becoming less relevant over time. Almost half of all tasks people are paid to do every day are at risk of being automated. In our current economy, change is happening so fast that the half-life of a learned skill is a mere five years, compared to a worker's lifetime just a few decades ago. While estimates about how many jobs will be replaced by robots range from 5 percent to 50 percent, there is near unanimous agreement that more than 60 percentof all jobs will be at least one-third automated. That's good news for those that can hold onto their jobs for now. The bad news is that the skills required to do those jobs will be more advanced and forever evolving.
The pathway to a good paying, skilled job is also up for grabs. A college education is no longer the gateway to a good-paying career. Individuals need to develop and maintain transferrable skill sets throughout their lives for multiple and possibly simultaneous careers, even if the job titles don't change.
Collaborating Between Man and Machine
The Institute for the Future (IFTF) released research that suggests that a qualitative shift, perhaps an order of magnitude greater than the outsourcing revolution, could now be taking shape in the workforce. The IFTF's project describes some of the new work skills required to leverage emerging automation technologies—AI IQ, futures thinking, digital fluency, pop-up communities and multi-cultural smarts to name a few.
Collaboration will also be a must-have skill going forward. But the scope of collaboration is something that most people don't yet grasp.
Today, collaboration not only concerns relationships between humans, but between humans and machines. Unlike the John Henry legend in which man's skills challenge the productivity of a steam-hammer or the time that chess champion Garry Kasparov triumphed against Big Blue, future innovation will depend upon people racing with machines, not against them.
Automation Is Real, Folks
Much of the rhetoric on the 2016 Presidential campaign promised to "bring jobs back." Here's a real-life example why labor-intensive, task-heavy jobs are going, going, almost-gone.
When the price of oil fell in 2014, so did the number of oil industry workers. But when the oil rigs started up again, a lot of workers didn't. Thanks to automated drilling, a dangerous, laborious task now required fewer people to accomplish. In fact, it's expected that what once took a crew of 20 will soon take a crew of 5. The application of new technologies to oil drilling means that of the 440,000 jobs lost in the global downturn, as many as 220,000 of those jobs may never come back.
This scenario is taking place in nearly every industry–from robots on the manufacturing floor and in the surgical suite to autonomous vehicles driving down the interstates.
I repeat—exponential change does not play favorites.
Crossing the Data Divide
Data mining is another example of how work is changing. In the past, millions of jobs were created for people to input data. Today, computers input much of that basic data themselves and software creates more of it. Data jobs now require workers to have the ability to analyze and use the data—skill sets that few people have. Finding a solution requires not only exceptional "sense-making" skills, but the ability to collaborate with machines.
By 2018, the United States alone is predicted to face a skills gap of up to190,000 people with analytical skills needed to use big data to make effective decisions. But predictions like this about employment and unemployment are nearly meaningless without management and government alike focusing on the fundamentally changing nature of work.
Exponential change that disrupts work is not a passing fad. As the concept of work and the skills required to perform it get re-worked, jobs are being transformed. It goes without saying that an epic shift is underway.
Maybe Issac Asimov had it right when he said, "It is change, continuing change, inevitable change that is the dominant factor in society today." From the way we educate our youth to a transformative shift in mindset about careers and jobs, we all need to re-imagine the average worker alongside the evolution of average work.
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