The trucking industry is not the only potential victim. Driverless vehicles could change car ownership trends, making full ownership an obsolete concept. Alternatives could include fractional ownership, own-and-share, mobility services or paying per ride. Imagine the effect on car dealerships, auto mechanics and even parking attendants if people were to forgo the traditional models of car ownership and commuting. While conversion to 100 percent autonomous vehicles might not be possible, even in the long term, it is safe to predict that a large percentage of cars will eventually be driverless.
Manufacturing continues to be a target for greater use of technology, particularly automation, robotics and AI. Technology comes with the temptations of lowering labor costs, increasing throughput and improving quality. While robots may not supplant all human positions—at least not yet—their continued proliferation throughout manufacturing is assured. America has lost approximately seven million manufacturing positions since its peak in 1979, largely due to technology, yet output has continued to increase.
Simply put, the numbers are staggering. General Motors has lost one-third of the six hundred thousand workers it had in the 1970s, and is outproducing its previous totals. The steel and metals industry has lost over 265,000 jobs, or 42 percent, yet production has increased by 38 percent. One estimate is that by 2020, the United States will be the “most competitive country in manufacturing.”
The same is true for mining, where the labor force has been reduced from over 250,000 to 58,000, due to new ways of mining that require less manpower, thus effectively outsourcing positions to technology. Despite these labor reductions, output continues to grow.
The so-called Internet of Things could affect a wide range of industries. From monitoring industrial controls systems for utilities to health-care delivery, opportunities for reducing labor are evident. Anywhere workers are performing checks, monitoring statuses or adjusting levels has the potential for automation, and ultimately AI. Some might argue that certain tasks require human skills, but, as events like the Chernobyl and Fukushima nuclear accidents demonstrate, human mistakes can cause or contribute to devastating outcomes. Both would have benefited from AI-equipped nonhuman intervention rather than relying on human judgment.
PERHAPS NO sector has greater potential for dramatic change than retail businesses and supply chains. Today, if a customer wants to buy an item—say, a plastic bowl—she can make a trip to the store and purchase the bowl. However, that bowl has traveled a long way to reach store shelves, where the customer picks out the item based on its size, color and shape. It was likely made in a manufacturing facility overseas, shipped by ground conveyance to a port where it was loaded into a crate, placed on a ship for transit across the ocean and ultimately delivered in a reverse process to the store. Of course, the nature of retail stores is to provide choices for customers, which implies that businesses should keep their shelves filled, shoulder the costs of holding inventory and sell products at a low enough price that inventory will move quickly.
Now let’s consider what 3D printing will do to the retail businesses and supply chains of the future. The potential customer now goes online and orders a bowl, able to alter the dimensions to suit her individual preferences. A local 3D manufacturing facility (which has not yet been built) receives the order, prints the bowl, packages it for shipment and places it on a drone that has been configured to deliver packages. The entire process could be completed in hours vice the several months’ journey the first bowl took to reach the retail store. Theoretically costs could be reduced, as the product takes fewer steps, fewer people are involved in “delivery” and there are no inventory holding costs.
This is great for the customer with the new bowl fitting her exact specifications, but what about the workers in the long supply chain that stretched from the overseas factory to the retail store? Having fewer people involved in the process means fewer workers overall. In fact, the early signs of this supply-chain revolution can already be seen in the closure of stores whose business models rely on long supply chains and large inventories.
Of course, as the manufacturing sector evolves, not all positions will be eliminated. Some undoubtedly will result in new positions, such as in 3D manufacturing plants and aerial-delivery service centers. Still, future labor markets are likely to experience volatility while reaching a new normal, and as labor demands are reduced or new workforce skills acquired.
Returning to the question of how to determine what positions are likely to be automated, the answer varies around the globe and from sector to sector. However, trends are uniformly leaning towards a greater reliance on technology to offset human labor demands across virtually all sectors. Today, estimates from McKinsey suggest that some 60 percent of all jobs include at least 30 percent tasks that automation could replace, based on currently demonstrated technologies. A separate study from Oxford University found that of 702 occupations considered, 47 percent of U.S. workers had jobs at a high risk of potential automation.
As technologies mature and machines gain higher levels of performance that meet or exceed human capabilities, displacement of today’s workforce will continue. The McKinsey report suggests that automation technologies could affect 50 percent of the world economy, or 1.2 billion employees and $14.6 trillion in wages. When these people are displaced, what will they do to earn a living and provide for their families?
And what determines whether a job is at risk for automation? Several factors serve as indicators for identifying jobs at risk. First, a job’s technical requirements provide some important indicators. Is it routine or repetitive? Does it require thinking and judgment, or routine activity with little need for creativity? Second, do technical impediments exist for developing the hardware and software required to automate a position? The response likely varies over time as additional technological sophistication is achieved. Perhaps today, with the current level of AI capacity, the answer is no, but what about in the future? Third, does the labor market provide a ready supply of labor at an affordable cost? Does the cost of automation far exceed the cost of maintaining human labor in the position? And, fourth, are there benefits to be gained by automating the tasks. For example, can a dangerous task be automated to protect workers from injuries? Will higher levels of output and quality be achieved? Can an automated system surpass human abilities?
Many are quick to point out that technology and associated automation is not an all-or-nothing proposition. Some functions that have been automated have resulted in the growth of other jobs. For example, per McKinsey, while the internet is credited with eliminating five hundred thousand jobs in France over a fifteen-year period, it simultaneously created over 1.2 million new ones. Likewise, the emergence of the internet economy generated a greater need for statisticians and data scientists.
Still, on balance, trends towards greater use of technology in place of labor are continuing, and will alter future labor markets. As the Economist summarized the Oxford study’s conclusions, “the workforce bifurcates into two groups doing non-routine work: highly paid, skilled workers (such as architects and senior managers) on the one hand and low-paid, unskilled workers (such as cleaners and burger-flippers) on the other.”
THE FUTURE of work has become a topic of serious debate. Some foresee the society of the future as a jobless one in which all work is done by robots. Others take a more measured view, allowing that labor markets will change incrementally, but affirming that societies will be able to adapt and reach a new equilibrium. Those in the incremental camp highlight the need for more STEM education, retraining of people displaced by technology, and safety nets and transition support until they can reenter the job market.
These approaches sound well reasoned and certainly prudent in the near term. However, what if the direr assessment that technology will displace 1.2 billion jobs and $14.6 trillion in wages came to pass? Such measures would likely not be sufficient.
Strategies would then need to be larger and require more resources. They could include the following:
Creation of a robot tax. Bill Gates advocates a robot tax, “as a way to at least temporarily slow the spread of automation and to fund other types of employment.” He calls for governments to use revenues to develop safety nets for the displaced workforce, and perhaps even other social programs. The proposal has been hotly debated, with many saying that the tax would adversely affect innovation and productivity. The European Union has proposed a similar initiative.
Changing the structure of work. Today, work is primarily focused on output. As such, in agriculture, industry and services, workers produce a tangible output that is assessed to have a certain market value for which they are compensated. Very few people work in think tanks, research laboratories and other idea factories. However, if technology has displaced workers in routine and repetitive tasks, perhaps that brainpower could be put to use solving complex, seemingly intractable problems that are or will be facing society. One could see this as an opportunity to create a new age of enlightenment, focused on hard problems and generating ideas.