A few weeks back my book review of two “the robots are taking over” came out over on The New Stack. Here’s some responses, and also some highlights from a McKinsey piece on automation.
Don’t call it “automation”
There is much more to this topic. Nick Carr’s book, The Glass Cage, has a different perspective. The ramifications of new technology (don’t call it automation) are notoriously difficult to predict, and what we think are forgone conclusions (unemployment of truck drivers even though the tech for self-driving cars needs to see much more diversity of conditions before it can get to the 99%+ accuracy) are not.
Lisanne Bainbridge in her seminal 1983 paper outlines what is still true today.
From that paper:
This paper suggests that the increased interest in human factors among engineers reflects the irony that the more advanced a control system is, so the more crucial may be the contribution of the human operator.
When things go wrong, humans are needed:
To take over and stabilize the process requires manual control skills, to diagnose the fault as a basis for shut down or recovery requires cognitive skills.
But their skills may have deteriorated:
Unfortunately, physical skills deteriorate when they are not used, particularly the refinements of gain and timing. This means that a formerly experienced operator who has been monitoring an automated process may now be an inexperienced one. If he takes over he may set the process into oscillation. He may have to wait for feedback, rather than controlling by open-loop, and it will be difficult for him to interpret whether the feedback shows that there is something wrong with the system or more simply that he has misjudged his control action.
There’s a good case made for not only the need for humans, but to keep humans fully trained and involved in the process to handle errors states.
Hiring not abating
Vinnie, the author of one of the books I reviewed, left a comment on the review, noting:
For the book, I interviewed practitioners in 50 different work settings – accounting, advertising, manufacturing, garbage collection, wineries etc. Each one of them told me where automation is maturing, where it is not, how expensive it is etc. The litmus test to me is are they stopping the hiring of human talent – and I heard NO over and over again even for jobs for which automation tech has been available for decades – UPC scanners in groceries, ATMs in banking, kiosks and bunch of other tech in postal service. So, instead of panicking about catastrophic job losses we should be taking a more gradualist approach and moving people who do repeated tasks all day long and move them into more creative, dexterous work or moving them to other jobs.
I think Avent’s worry is that the approach won’t be gradual and that, as a society, we won’t be able to change norms, laws, and “work” over fast enough.
As more context, check out this overview of their own study and analysis from a 2015 McKinsey Quarterly article:
The jobs don’t disappear, they change:
Our results to date suggest, first and foremost, that a focus on occupations is misleading. Very few occupations will be automated in their entirety in the near or medium term. Rather, certain activities are more likely to be automated, requiring entire business processes to be transformed, and jobs performed by people to be redefined, much like the bank teller’s job was redefined with the advent of ATMs.
our research suggests that as many as 45 percent of the activities individuals are paid to perform can be automated by adapting currently demonstrated technologies… fewer than 5 percent of occupations can be entirely automated using current technology. However, about 60 percent of occupations could have 30 percent or more of their constituent activities automated.
Most work is boring:
Capabilities such as creativity and sensing emotions are core to the human experience and also difficult to automate. The amount of time that workers spend on activities requiring these capabilities, though, appears to be surprisingly low. Just 4 percent of the work activities across the US economy require creativity at a median human level of performance. Similarly, only 29 percent of work activities require a median human level of performance in sensing emotion.
So, as Vinnie also suggests, you can automate all that stuff and have people focus on the “creative” things, e.g.:
Financial advisors, for example, might spend less time analyzing clients’ financial situations, and more time understanding their needs and explaining creative options. Interior designers could spend less time taking measurements, developing illustrations, and ordering materials, and more time developing innovative design concepts based on clients’ desires.