Sometimes technology does nearly eliminate certain categories of jobs: for example, I was watching the 1958 movie Auntie Mame last week, in which the fabulous Rosalind Russell–portraying a character from the early 1930s–has a short comedic take on being a switchboard operator at a law firm. I had to explain to my teenagers what she was doing, and that such a job used to exist. But it is more common for technology to alter jobs, rather than to eliminate them.
Michael Chui, James Manyika, and Mehdi Miremadi have been exploring what jobs are likely to be altered more or less by technology. They present some results in \”Where machines could replace humans—and where they can’t (yet)\” in the July 2016 issue of the McKinsey Quarterly. They are working with data from the US Department of Labor, through which they have a list of 800 occupations and 2,000 tasks that are performed in the context of those occupations. By estimated which tasks are most likely to be automated, they can figure out which occupations are most likely to be altered substantially by new technology. I\’ll start here with a quick overview of their findings, and then offer some more nuances thoughts.
The columns of this figure show six activities that are (broadly) involved in many jobs. The rows show job categories. The size of the circles shows what share of time on the job is spent in each activity. The color of the circle shows how easy it is, within that to automate that activity. Thus, the first row shows that in food service, a large share of time is spent on tasks \”predictable physical tasks\” that are fairly easy to automate. Indeed, one minor surprise of these findings is that \”accommodations and food service\” jobs, rather than manufacturing, have the highest technical potential for automation.
Here are a few more detailed insights:
1) Just because part of a job is automated doesn\’t mean that the number of workers in that job necessarily declines. I posted about a year ago on the example of \”ATMs and a Rising Number of Bank Tellers\” (March 3, 2015) about how the dramatic rise in automatic teller machines has been accompanied by a rising number of bank tellers–although the job of \”bank teller\” has also evolved during this time. The McKinsey researchers offer another example. How would the deployment of bar-code scanners affect the number of cashiers? I would have guessed that their number would fall, and I would have been wrong. The authors write:
\”Even when machines do take over some human activities in an occupation, this does not necessarily spell the end of the jobs in that line of work. On the contrary, their number at times increases in occupations that have been partly automated, because overall demand for their remaining activities has continued to grow. For example, the large-scale deployment of bar-code scanners and associated point-of-sale systems in the United States in the 1980s reduced labor costs per store by an estimated 4.5 percent and the cost of the groceries consumers bought by 1.4 percent. It also enabled a number of innovations, including increased promotions. But cashiers were still needed; in fact, their employment grew at an average rate of more than 2 percent between 1980 and 2013.\”
2) In a number of cases the question isn\’t about whether a certain task can be automated, but whether the task happens in a repetitive and predictable context, or in a flexible context. They write: \”Within manufacturing, 90 percent of what welders, cutters, solderers, and brazers do, for example, has the technical potential for automation, but for customer-service representatives that feasibility is below 30 percent.\”
3) Automation isn\’t just about physical jobs that can be automated by robots. A large tasks performed by well-paid white-collar workers that involve collecting and processing data are vulnerable, too.
Across all occupations in the US economy, one-third of the time spent in the workplace involves collecting and processing data. Both activities have a technical potential for automation exceeding 60 percent. Long ago, many companies automated activities such as administering procurement, processing payrolls, calculating material-resource needs, generating invoices, and using bar codes to track flows of materials. But as technology progresses, computers are helping to increase the scale and quality of these activities. For example, a number of companies now offer solutions that automate entering paper and PDF invoices into computer systems or even processing loan applications. And it’s not just entry-level workers or low-wage clerks who collect and process data; people whose annual incomes exceed $200,000 spend some 31 percent of their time doing those things, as well.
4) Just because it\’s technically feasible for certain tasks to be automated doesn\’t mean they necessarily will be automated.
\”Technical feasibility is a necessary precondition for automation, but not a complete predictor that an activity will be automated. A second factor to consider is the cost of developing and deploying both the hardware and the software for automation. The cost of labor and related supply-and-demand dynamics represent a third factor: if workers are in abundant supply and significantly less expensive than automation, this could be a decisive argument against it. A fourth factor to consider is the benefits beyond labor substitution, including higher levels of output, better quality, and fewer errors. These are often larger than those of reducing labor costs. Regulatory and social-acceptance issues, such as the degree to which machines are acceptable in any particular setting, must also be weighed. A robot may, in theory, be able to replace some of the functions of a nurse, for example. But for now, the prospect that this might actually happen in a highly visible way could prove unpalatable for many patients, who expect human contact. The potential for automation to take hold in a sector or occupation reflects a subtle interplay between these factors and the trade-offs among them.\”
My own job as Managing Editor of the Journal of Economic Perspectives has been dramatically affected by technology over the years. When the journal first started in 1986, we had what was then a very innovative idea: authors would mail us floppy disks with the text of their papers. I would edit the actual paper, and mail it back to the authors to edit further. We would then mail the paper to the typesetter on the floppy disk. At the time, this was red-hot newfangled stuff! The task of hands-on editing remains very similar to 30 years ago, but there are lots of dramatic changes. The ways in which we communicate with authors have been fundamentally changed by email, attachments, shared mailboxes on the cloud, and easy conference calls. The tasks of looking up past articles and checking references used to require trips to the library, and are now done casually without leaving my desk. The distribution of the journal used to be all-paper, and then available online by subscription, and then with individual articles freely available online, and now with entire issues that can be freely downloaded and read on a tablet or a smartphone.
Most jobs will be altered by technology. And most of us find that even as technology replaces certain tasks, it creates the possibilities for new tasks that could not previously be done–or at least couldn\’t be done very cheaply or easily. This continual updating of jobs is one of the prices we pay for prosperity.