The advancements in artificial intelligence of the past few years have been mind-blowing. They have given rise to much research and analysis about the future of work. They have also given rise to a lot of nonsense. The trick is to figure out which is which.
On one side of the argument are respected academics and global consulting organizations. In their tremendous book, Race Against the Machine, Andrew McAfee and Erik Brynjolfsson offered dire predictions of the increasing power of AI and the erosion of jobs it will bring. Their advice? Don’t fight it – instead, figure out how to work with technology change to get the greatest benefit as individuals and as a society. There have been dire predictions about how big job losses will be, but the best-informed numbers come from the McKinsey Global Institute. They predict that automation will eliminate only 5% of today’s jobs. But it will also have an impact on 60% of total jobs. On average, workers in those fields spend one-third of their time doing routine work, and routine labor is the easiest to automate. So, no matter what you do for a living, it would be wise to buckle your seat belt.
But Is It So?
On the other side are some pesky facts. Recessions often lead to bursts of automation, because when revenues fall but wages do not, it makes human labor more costly, and bosses feel more pressure to replace them with machines. Given that logic, the pandemic should have created a major surge in automation.
But it didn’t, according to a survey by The Economist. American imports of industrial robots actually fell by 3% in 2020 and the overall growth in spending on automation slowed. This points to something that will seem truly weird at first glance. Periods when automation has raced forward have not seen big job losses. Believe it or not, they have been periods of job growth.
Weird, right? It’s because automation is one form of innovation. And what people tend to forget is that successful innovation – the kind that produces new products and services – triggers new spending by people who want them. Nobody needed an iPhone, iPod or iPad until Steve Jobs decided they did. But they became three of the most successful consumer electronic products in history. Companies meet the demand for new products and services by – guess what? – hiring more people.
Electric cars were a technology that was always 10 years over the horizon until Tesla put itself through what Elon Musk called “production hell” to work out how to churn them out and sell them by the hundreds of thousands. As of this writing, traditional automakers have announced commitments of more than $140 billion in a massive game of catch-up. Waves of hiring will follow.
That means a foundational technology like AI will power a series of products and services that will generate revenue and employment growth. That’s good news for job creation. But there is a catch. The new employment won’t demand the same skills. People will need to adapt at speed. They will need to gain new and different skills to fill new niches in the economy.
Those Who Adapt Survive
In that kind of economy, your community’s greatest competitive advantage will be the ability to upskill workers – to help young people and adults gain the skills that will soon be in demand.
We know how to do it. As the Work Factor in the ICF Method explains, it takes skillful, collaborative investment by government, business and education that creates a ladder of opportunity for people in the community. It is how to ensure that your people benefit rather than suffer from economic change.
So far, in the US, we haven’t done such a good job. A new study from a nonprofit called Opportunity@Work estimates that, since 2000, this kind of disruption has displaced 7.4 million jobs for people without four-year college degrees. That’s a terrible impact on people who need those jobs to climb into the middle class.
The McKinsey Global Institute predicts that artificial intelligence will add 16 percent or US$13 trillion to global economic output by 2030. It also predicts that up to 375 million workers around the world (14 percent of the total) will have to change job categories to get that result. In the end, there’s no better advice than that offered by Race Against the Machine. Those who adapt survive. AI will eliminate a few categories of employment but dramatically change many more. The success of AI must be measured not just by return on investment but by return on human capital. It is up to government policy and funding, corporate workforce policy and educational innovation to make the growth of AI a benefit to the greatest number possible.
In other words, it is up to us.