When people talk about automation, most of us probably imagine a robot arm on a factory assembly line. And, for much of the past few decades, that was a reasonable way to think about automation, because of its focus on replacing human physical labor with machines.
But that image is increasingly obsolete. With the advancement of artificial intelligence technologies, automation is still replacing humans, only that's now happening in the cognitive space as well as the physical one.
Nor is this some remote future vision. When U.S. Treasury Secretary Steven Mnuchin said earlier this year that AI is “not even on our radar screens,” adding that he figured it would be “50 to 100 years” before humans started losing jobs to AI, he couldn’t have been more wrong.
For example, we’re seeing AI technology companies targeting the replacement of what's estimated to be up to 50 percent of current employees in the finance sector over the next 10 years. We would have considered these types of jobs “safe” from automation only a few years ago.
According to University of Oxford researchers, 47 percent of workers may be at risk of losing their jobs to automation, in particular those in mid-skilled retail jobs, and office workers like cashiers and telemarketers. A recent McKinsey report predicted that a smaller percentage of jobs would be at risk of being completely replaced by machines, but pointed out that the majority of jobs would see some of their tasks replaced by automation.
In other words, we’re all going to feel the impact of AI in some way. And our skills aren’t keeping pace.
The sheer number of both soft skills and technical skills already required by most modern companies is exploding. At the same time, the skills people do pick up remain relevant for a shorter and shorter amount of time. AI only accelerates this trend. We’ve crossed a threshold where the timed obsolescence for skills is shorter than for a single career.
The message: People need to adapt faster than ever. And this could have enormous consequences, including widespread unemployment and devastating disruptions for parts of the global economy.
One easily imaginable scenario: In the United States, there are approximately 3.5 million truck drivers. Suppose a truck company could retrofit a truck for $30,000 to make it into a reliable, safe autonomous vehicle. That would be a one-time cost, and the cost would be less than the annual salary of a truck driver. Once that scenario became possible, the industry would likely overhaul its fleet extremely rapidly.
And what would those 3.5 million former truck drivers do then? What about today’s taxi drivers and Uber and Lyft drivers? In fact, it’s entirely possible that we will still have taxi drivers in the streets protesting Uber when Uber drivers take to the streets to start protesting autonomous vehicles.
The good news here, however, is that previous technology revolutions have demonstrated that these changes also create new opportunities and entirely new kinds of jobs. The world will need more people who are able to do jobs that AI cannot. To succeed, then, we need to "robot-proof" our workforce.
Reinventing education and skills development
To do this robot-proofing, we need an approach to education and training that supports ongoing learning and is flexible and engaging -- an approach that suits the needs of all kinds of people.
Unfortunately, our current model of education is aimed primarily at training young people at the beginning of their careers, when learning is their full-time occupation. It’s a model that, by and large, is built around the notion of “seat time”: If you need 40 credits to graduate, you need to spend a certain number of hours in a classroom, listening to a professor. That’s fine if you have lots of time to spend. But, as AI accelerates workers' need to continually update skills, time is quickly becoming a scarce commodity.
So, what might an alternative approach look like?
One direction might be to change what people study. Increasingly, the value humans can add stems from innovation and creativity: seeing connections in seemingly unrelated things. Emphasizing cross-disciplinary knowledge could fuel these creative connections; to support that goal, some universities are already reorienting their departments around real-world careers areas instead of narrow, academic disciplines.
One example: Arizona State University has created a wide range of career-focused departments, such as its “School of Earth and Space Exploration,” which incorporates elements of earth sciences, astrophysics and environmental engineering.
We also need to shift where we place the responsibility for learning. When we are very young, our parents are responsible for our education; later that responsibility shifts to our teachers. Instead, we need a model where individuals are supported in taking responsibility for their own lifelong education, even after graduation. And companies need to take responsibility for continually providing opportunities for their employees to develop.
There needs to be greater connectivity between higher education and the labor market. Colleges can address this need by focusing on skills that are truly in demand. In part this could be accomplished through more partnerships between corporations and institutions of higher learning. It could also be realized by creating more opportunities to integrate work and learning together -- for instance, more and better internship programs.
Getting credit for what you know
Improving higher education is important, but most of us expect that we’ll be continually upgrading our skills after we graduate. In fact, non-traditional students -- adult learners attending post-secondary education part-time -- are already one of the fastest-growing segments within universities and colleges.
To meet the need of these non-traditional students, it’s time that educational organizations fully embrace certifications focused around mastery and demonstrated competency, not seat time. With this approach, students would get credit for what they actually know, not how much time they’ve spent in a classroom.
In sum, learning can’t end with graduation. To be competitive, companies will need to step up and provide education opportunities themselves, while encouraging self-directed learning, so they can ensure that their workers are continually acquiring new skills as the old ones become obsolete.
A modern, competency-based learning approach will not only give employees the skills they need to remain relevant, it will also improve employee satisfaction and help companies with recruitment and retention.