In the early 1960s, just as the information technology revolution was taking its first baby steps, a committee of scientists and social activists sent an open letter to the US President, Lyndon B. Johnson: “The cybernation revolution” will create “a separate nation of the poor, the unskilled, the jobless” who will be unable to find work and to afford life’s necessities, they argued.
Three decades earlier, in the 1930s, according to The Atlantic, a California mayor wrote to the US President that industrial technology was a “Frankenstein monster” that threatened to upend manufacturing, “devouring our civilization”.
These doom and gloom predictions of how new technology would lead to a worse world proved to be utterly wrong, of course – just as many similar, earlier predictions about the effects of new technology had been. But the most recent World Economic Forum meeting in Davos, presented a déjà vu moment: An IMF report concluded that 40% of jobs around the world will be affected by AI. In advanced economies, that rises to 60% of jobs set to be affected by machine learning, with about half being negatively impacted. The losers will face lower salaries and reduced hiring, and some jobs will disappear altogether.
Over the last 200 years, predictions of fewer jobs in the future have generally proven to be false. The pessimists have been wrong repeatedly. But make no mistake – hundreds of millions of jobs have been destroyed. First, agricultural technology replaced millions of farming jobs, while the industrial revolution moved people into factories. Then automation moved them back out of the factories, giving rise to an economy of services.
Throughout these waves of creative destruction, however, the total number of people employed has risen. Today there are a record number in employment across the globe and in almost every country.
Number of people employed worldwide (billions), 1991-2023 Image: International Labour Organization
But it will be different this time because AI is different. Technology will not always support people in doing their jobs, it will primarily replace jobs. New types of jobs will emerge, however.
Trying to imagine the new world of work
If you were a farm worker 120 years ago – like roughly three quarters of all people at the time – would it have been possible for you to imagine a world where only one in 20 people worked on farms? Could you have anticipated the range of new jobs available to workers today? Even 20 years ago, economists probably wouldn’t have predicted that there would be 800,000 personal trainers employed in the US today and 2.5 million jobs in the app development industry.
It’s possible that we are experiencing the same difficulty today in trying to imagine the new, unknown jobs of the future. We can’t see into the future, but we can shift our perspective on the possible creation of new jobs by asking broader questions.
First, are all of our needs satisfied today? For instance, would we like higher quality food? Would we like better services from businesses or government agencies? Would we like more efficiently or more beautifully designed products? Do we want better health – physical and mental? New roles could be created to address these needs and wants.
Second, will new needs arrive as our society evolves – as we work through solutions to our current global challenges and as new innovations arrive? A future equivalent to today’s smartphone could create entirely new sectors of employment. It’s possible that we are not able to imagine this today, but if the patterns of the last 200 years continue, these jobs will arrive.
Third, will an increase in demand for products and services lead to new jobs? New technology will eliminate some jobs, yes. But in many cases, it will support a worker in doing a better, more efficient job, lowering the cost of production. When products and services become more affordable, demand generally increases.
Last, and perhaps most relevant: How can policy makers and government agencies best facilitate the dynamic creation and rotation of the labour market towards new jobs? This will be particularly important if, as is likely, creative destruction and job changes continue, possibly at a higher rate than ever.
Investing in new technology and jobs
Small and mid-sized businesses create a disproportionate amount of new jobs around the world. So, freedom for entrepreneurs and investors to create and grow businesses will be more critical than ever as new technology becomes more available.
A more flexible and free labour market should allow more rapid moves between sectors and businesses as the nature of jobs change. This means that nations that are less attractive to entrepreneurs and investors because of lower economic freedom and heavily regulated labour markets may suffer from more unemployment. Alternatively, nations with open and free markets will keep creating new jobs to replace the lost ones.
Creative destruction stemming from tech development may lead to hard times and new challenges for many people, as well as for whole cities and regions. Governments can play an important role in alleviating this by providing opportunities or support programmes for reskilling, as well as unemployment benefits and other forms of transitional safety nets.
During the industrial revolution, local and national governments made major public investments to teach the skills of reading, writing and math that were necessary for the new jobs at that time. There was also investment in new roads, ports and other infrastructure. In this new era, we need public investment in digital skills for everyone, as well as digital highways that allow regions to participate in new economic opportunities.
As we all try to imagine the new, unknown jobs of the future, we must ask the right questions about new technology and how it will affect our work and our industries. By shifting our perspective on how new jobs can arise from new technology, we can ensure AI brings about change that works for everyone.
This article previously appeared in the World Economic Forum.
Also read: Mapping deforestation to recycling more waste—9 ways AI is helping fight climate change