For humanity, major socio-economic transformation is nothing new, but the rise of artificial intelligence (AI) requires the world to adapt and realign to a new reality more rapidly than ever before. How will we cope?
It took 150,000 years to become an agrarian society and complete the transition from hunting and gathering. Over the next 10,000 years, the economy slowly evolved as populations grew. The real change came with the advent of the industrial revolution. 200 years ago, we began to move from farms to factories. Enabled by fast transportation, open foreign currency exchange, trade policies and communications, the economies quickly became global. We are still completing our most recent, 50-year shift to a services-based economy. Relatively speaking, these were all gradual shifts—and yet, they disrupted lives and dramatically transformed whole societies.
Now, we stand on the brink of a fourth economic revolution, one that will reshape society with rapid advances in robotics automation and AI. Expected to generate dramatic returns for society, the AI revolution is predicted to make a massive impact in 20 to 25 years, about half of a single work career.
It’s easy to envision a doomsday scenario about the displacement of workers in the face of this rapid advance. Will the coming AI disruptions leave millions unemployable?
I believe it will not — not if we plan ahead.
Doomsday Or Development?
Past innovations automated routine, menial work. Displaced workers could (and typically did) simply educate and re-skill themselves back into employability. In the past, they had the time to do it.
In contrast, AI’s looming threat is to replace high-level, judgment-based skill-sets, such as complex analysis, discretionary decision-making and even creative ideation. Robotics will replace many of the services and manufacturing positions. What kind of jobs will be left for people to do?
This is a pressing concern without clear answers, but doomsdayers neglect a crucial fact: Investments cannot capitalize on AI’s gains in the absence of human consumption. I believe AI will only be meaningful if humans are able to capture the benefits of AI technology.
The McKinsey Global Institute recently observed that the only way to realize the productivity dividends of AI will be to have people in place to capture them. Managing this transition will be a competitive imperative.
In other words, all jobs will not disappear — they will undergo a significant metamorphosis.
Past Economic Shifts Offer Hope
However unprecedented the pending revolution may be, studying the past is still reassuring and helpful. If we take the whole of human history as our dataset, it is apparent that, ignoring local dislocations and the resulting need to migrate, humanity has typically landed on its feet and moved forward.
That’s how large-scale transformation works. As past advances displaced workers, so too have they given rise to a new, previously unimagined class of employment. Hunter-gatherers became farmers. Farmers morphed into factory workers. As we peer into the future, it’s difficult to predict exactly who society’s workers will be, but the past forecasts that human employment will be alive and well.
Of course, one key challenge of the AI revolution is that workers will have far less time to retrain themselves. Previous economic shifts occurred slowly, over many generations; this one is likely to happen well before many of today’s workers retire. It will take deliberate forethought, planning and action to avoid a disastrous disruption.
I suggest a four-pronged strategy.
1. Identify Skills
To start training and upskilling the workforce, the first task will be to forecast the new wave of jobs and identify their corresponding skills. Once we do so, we can develop specific training curricula and socialize it. This process will have to be constant and flexible, as the skills needs will likely change every five to 10 years.
2. Retain Your Current Employees
As a workforce strategy, it’s clearly more efficient and fiscally responsible to retain and retrain your employees, rather than engage in large-scale layoffs and rehiring. Existing employees are already familiar with your company culture. They know your customers and have working dynamics that may have taken years to optimize. Except for dealing with poor performers, in my view, there’s no need to replace when retraining is a cheaper option.
3. Develop And Deploy Training
In the past, most workers had a single career in their lifetime. As automation accelerates, workers will require a new skills portfolio about once a decade. Predictive analytics technology can help pinpoint three things: employees in your business that are most likely to leave, those who can benefit most from being re-skilled and the likely impact that re-skilling programs will bring to your workforce overall.
Developing and deploying useful training takes years. Rather than simply throwing money at it, one should investigate the cause of every notable success and failure. I recommend measuring inputs, tracking outcomes, modeling different policies and closely following early adopters to learn and emulate best practices.
4. Reimagine Education
The children of tomorrow need to know how to both manage the advanced machines and systems that will surround them from childhood and how to harness the resulting insights. The current education curricula are not designed to deal with these needs, and time is running short.
I recommend that businesses involve themselves in assisting their source schools in shaping the curriculum, providing teaching assistance, funding teacher development programs, sending their key innovators into the classrooms and developing teacher sabbatical exchange programs. Technology firms should provide assistance in terms of free access to products and co-op programs in collaboration with their local colleges.
The challenge we face is dramatic, and it will require unconventional thinking and experimentation. The earlier and more aggressively we engage in a global discourse on this issue, the more likely we will develop coping mechanisms and avoid another rust-belt calamity.
This article first appeared in Forbes.