Technology has been transforming the working environment throughout history. John Maynard Keynes in 1930 predicted “technological unemployment” in Economic Possibilities for our Grandchildren in 1930. And in 1961, as Henry Ford’s production lines transformed industry, U.S. President Kennedy said: “The major challenge of the sixties is to maintain full employment at a time when automation is replacing men.”
Today, Carl Frey and Michael Osborne at Oxford University predict up to 47 percent of U.S. jobs are at risk of being automated. In 2016, Forrester predicted automation would eliminate 6 percent of U.S. jobs by 2021.
“Every time humanity goes through a new wave of innovation and technological transformation, there are people who are hurt, and there are issues as large as geopolitical conflict. AI is no exception,” Fei-Fei Li, Director of the Stanford Artificial Intelligence Lab told CNN.
The UK Industrial Revolution caused wages to stagnate for decades and required substantial policy reforms to improve. McKinsey notes similar consequences, warning these could be enhanced if AI is adopted rapidly across multiple sectors at once, which may “accelerate both the rate and the extent of worker displacement.”
The pace of change
The Organisation for Economic Co-operation and Development (OECD) says: “As job losses are unlikely to be distributed equally across the country, this [AI] would amount to several times the disruption in local economies caused by the 1950s decline of the car industry in Detroit where changes in technology and increased automation, among other factors, caused massive job losses.”
Pew Research predicts, “Robots and digital agents [will] have displaced significant numbers of both blue- and white-collar workers.”
MIT economist Erik Brynjolfsson points out that while steam engines doubled in power and efficiency over 70 years, Moore’s Law tells us processors double in power every 18 months. Mobile robots like Rethink Robotics’ Baxter show that future systems will be capable of replacing even more human roles.
Those most at risk initially include low-skilled workers and the young, the OECD said. Moving forward, other industries, including retail, telemarketing, customer support, and more will also change.
Winners and losers
History shows that while technology often imposes initial painful impacts on employment, it eventually creates new employment. In part this is because technology fosters productivity, which helps stimulate demand.
Take agriculture. The sector accounted for 60 percent of jobs in 1850 but just five percent by 1970. The enhanced productivity enabled employment to shift, and new industries and occupations emerged – retail, healthcare and wholesale, for example. Demand for retail workers climbed 12.8 percent while healthcare employments rose 9.3 percent, claims McKinsey.
While millions of jobs were eliminated as PCs hit daily working life in the 1990s, an overall 15.8 million new U.S. jobs were created overall, they say.
The human touch
But robots can’t do everything. AI and robotics research Hans Moravec came up with a paradox in the 1980s, which can be summarized as "robots find the difficult things easy and the easy things difficult." Machines lack physical and mental agility, which makes them less capable for tasks that require ideation, complex communication or even situational understanding. AI is less creative and lacks the interpersonal skills for tasks like teaching or nursing.
McKinsey predicts post-AI demand for such soft skills will grow across all industries by 26 percent in the U.S., and by 22 percent in Europe. Skilled entrepreneurs, managers and other forms of leadership will be in demand. Creativity, critical thinking and decision-making skills will be prized, while tasks that require basic data input and processing will decline. Demand for physical and manual skills will shrink by 20 percent.
Intelligent machines may help augment human achievement, enabling us to achieve impossible results and fresh opportunities, from remote space exploration to medical analysis.
We must adapt
In an era of wealth inequality, education systems may need to be overhauled, enabling life-long learning to empower people to keep pace with technological change and shifting skills requirements, particularly among those groups of workers most impacted by AI.
Workforces must learn new skills. “Re-qualification is an important mechanism to aid the transition from more to less automatable jobs,” says the OECD.
Enterprises must also adapt. John Van Reenen, a British economist at Sloan, warns that while most European firms were too inflexible to benefit from the 1990s impact of IT, they must now prepare for AI to impact their business. For example, recent advances in natural language processing mean machine intelligence can now translate conversations in near real time – how does this impact international collaboration?
Despite the promise of AI, uncertainty remains. “There’s no economic law that says: ‘You will always create enough jobs or the balance will always be even,’ it’s possible for a technology to dramatically favor one group and to hurt another, and the net of that might be that you have fewer jobs,” MIT’s Brynjolfsson warns.
While the consequences of AI are now being felt, the future remains opaque. However, a focus on learning and making learning opportunities available to displaced workers seems important to unlocking the potential productivity benefits that these technologies bring.
Discover what's next with AI in this blogbook and a report from our labs in Silicon Valley.
Jon Evans is a highly experienced technology journalist and editor. He has been writing for a living since 1994. These days you might read his daily regular Computerworld AppleHolic and opinion columns. Jon is also technology editor for men's interest magazine, Calibre Quarterly, and news editor for MacFormat magazine, which is the biggest UK Mac title. He's really interested in the impact of technology on the creative spark at the heart of the human experience. In 2010 he won an American Society of Business Publication Editors (Azbee) Award for his work at Computerworld.