Automation Will Lead To Collaboration Between Man And Machine
Political promises to ‘bring back’ well paid jobs in the manufacturing and others sectors are a cruel deception that ignore the realities of a global inter-connected economy. Instead, we should focus on the challenges and opportunities presented by new technology trends including artificial intelligence, machine learning and big data analytics.
The concerns of some employees and young people about the impact of next generation automation on jobs and pay are understandable. As James Manyika, director of the McKinsey Global Institute, wrote an Institute paper published in May: “There is growing polarization of labor-market opportunities between high- and low-skill jobs, unemployment and underemployment especially among young people, and stagnating incomes for a large proportion of households and income inequality.”
He added: “The development of automation enabled by technologies including robotics and artificial intelligence brings the promise of higher productivity (and with productivity, economic growth), increased efficiencies, safety, and convenience, but these technologies also raise difficult questions about the broader impact of automation on jobs, skills, wages, and the nature of work itself.”
Mark Muro, a senior fellow and the director of policy at the Metropolitan Policy Program at the Brookings Institution, agrees. In an article published in the MIT Technology Review shortly after the U.S. Presidential elections, he said: “The collapse of labor-intensive commodity manufacturing in recent decades and the expansion in this decade of super-productive advanced manufacturing have left millions of working-class white people feeling abandoned, irrelevant, and angry.”
Brookings calculated that since 1980, globalization, offshoring, and automation eliminated nearly 7 million manufacturing jobs in the U.S. – more than one-third of U.S. manufacturing positions – as manufacturing employment plunged from 18.9 million jobs to 12.2 million.
What is more, while the trend is longstanding, it accelerated in the 2000s as millions of workers lost manufacturing jobs paying $25 per hour plus health and retirement benefits. Often the only alternatives have been service-sector jobs paying $12 an hour without benefits.
US Manufacturing Sector on the rise and the myth of reshoring jobs
Significantly, despite the decline in manufacturing jobs, the total inflation-adjusted output of the U.S. manufacturing sector is now higher than it has ever been. Quite simply, this reflects the higher productivity of factories employing robots rather than people – Boston Consulting Group reports that it costs $8 an hour to use a robot for spot welding in the auto industry, compared to $25 for a worker.
More generally, the “job intensity” of America’s traditional manufacturing industries is in decline. In 1980 it took 25 jobs to generate $1 million in manufacturing output in the U.S. Today it takes just five. The advent of advanced manufacturing techniques and ‘smart factories’ suggest these trends – including the substitution of capital investment for human capital – will continue.
Impact of technology adoption, the long view
But there is no consensus about the scale or timing of worker displacement, or the net impact on jobs of automation and digitization in the longer term. McKinsey itself argues that while 49% of jobs will be subject to some degree of automation, just 5% will be fully replaced anytime soon. In most cases, automation will take over specific (often dull and repetitive) tasks, rather than entire jobs.
As machine-learning–based skills approach those of human beings, it’s tempting to view their evolution as a slam dunk for the robots. But it is more likely that automation will lead to collaboration between man and machine rather than outright job replacement. And over time machine learning and other advanced technologies will create new growth opportunities and jobs for workers with updated skills.
“Even while technologies replace some jobs, they are creating new work in industries that most of us can’t even imagine, and new ways to generate income,” wrote James Manyika. SAP, which introduced its SAP Leonardo package of digital tools and services earlier this year to help customers navigate this transition, suggests organizations have an opportunity to save an astounding US$3 trillion to $4 trillion annually through task-based automation, and that over time, that will secure future growth and jobs.
Like Manyika, SAP and other technology companies argue that digitization and machine learning will lay the foundation for countless new scenarios, opportunities, and business models that enable companies to create more, higher qualified and better paid jobs. In evidence, they point to historical precedent.
Technology had a major impact on the workforce during the Industrial Revolution in the 18th and 19th centuries when many tasks became more automated and the types of jobs available changed as a result. Consider this: at the turn of the 19th century, 41 percent of U.S. jobs were based on agriculture. A hundred years later, the number had plummeted to just 1.9 percent.
Over that period, technology adoption transformed economies, but it didn’t lead to mass unemployment. “Technology rarely automates major occupations completely,” wrote James E. Bessen, author of a Boston University study released in late 2015. “Many occupations were eliminated for a variety of reasons.
“In many cases, demand for the occupational services declined (e.g. boardinghouse keepers); in some cases, demand declined because of technological obsolescence (e.g. telegraph operators). This, however, is not the same as automation. In only one case — elevator operators — can the decline and disappearance of an occupation be largely attributed to automation.”
Call to action: Responsibility of private and public sector
Nevertheless, companies, governments and education institutions all have a role to play in managing the transition to a digital economy. As MGI’s James Manyika says, “The disruptions to the world of work that digital technologies are likely to bring about could pose significant challenges to policy makers and business leaders, as well as workers.”
Among the measures that he and others suggest we should consider are working with education providers to improve STEM skills and foster adaptive and life-long learning among students. Companies should also play a more active role in education and training to ensure employees have the skills they need.
In addition, he argues that governments should consider creating incentives for private sector investment to treat human-capital like other capital and create public-private partnerships to stimulate investment in enabling infrastructure.
More controversially, we should rethink transition support and safety nets for displaced workers and consider the introduction of a Universal Basic Income that would replace Social Security and other benefits for those under retirement age.
Even if such measures are ultimately rejected, the time to discuss and debate their efficacy is now. If we focus on the past rather than the opportunities that new technologies and approaches from companies like SAP present, we risk making a big mistake. After all, no-one wants to be the modern-day equivalent of the last elevator operator!