Failing the Third Machine Age: When Robots Come for Grandma

Why “caregiver robots” are both inhuman and economically destructive

Zeynep Tufekci
Jul 22, 2014 · 11 min read

A cheerily written op-ed in the New York Times proclaims: “It’s time for robot caregivers”.

Why? We have many elderly people who need care, and children—especially those with disabilities—the piece argues, and not enough caregivers.

Call in the machines, she says:

“We do not have anywhere near enough human caregivers for the growing number of older Americans.”

This how to fail the third machine age.

This is not just an inhuman policy perspective; it’s economically destructive and rests on accepting current economic policies and realities as if they were immutable.

Let me explain. When people confidently announce that once robots come for our jobs, we’ll find something else to do like we always did, they are drawing from a very short history. The truth is, there’s only been one-and-a-three-quarters of a machine age—we are close to concluding the second one—we are moving into the third one.

And there is probably no fourth one.

Humans have only so many “irreplaceable” skills, and the idea that we’ll just keep outrunning the machines, skill-wise, is a folly.

First machine age came to replace human muscle power. Industrialization took over many tasks that were previously done by humans, especially those that required brute force, but required less of human intricate abilities. Producing basic yarn and cloth became automated, but not fine embroidery.

Fine and well, you say, who wants to dig ditches and pick vegetables in farms in back-breaking labor? Bring on mechanized agriculture and bulldozers!

However, as it played out, the people relieved from having to pick vegetables or dig ditches were not instead given the option to spend the time in libraries, reading up on their future jobs. They were declared redundant—and, crucially, more expensive and less docile than the machines. They were abandoned. There are worse things than being exploited, and being redundant and unable to make a living is one of them. In Europe, they swarmed into cities, which became a bleak, overcrowded nightmare of Dickensenia—oh, wait.

That misery is what Dickens was writing about. No metaphor.

But, look, you say! A few generations later, those people’s children moved into better jobs that weren't dependent on muscle power. They became teachers, clerks and lawyers. It’s true, but remember: there were a few waves of revolutions, couple of bloody wars, and a massive state intervention in response to widespread conflict that set up structures like minimum wage, weekend, labor protections, retirement and the rest…

This was not a peaceful, easy transition.

It was not “they came for our jobs, and we simply and quietly just moved to new ones.”

Then came the second machine age which automated mental labor. The machines came for the clerks and bookkeepers. Calculators, typewriters, printing press, diagnostic systems, automated planes… The jobs that children of manual laborers had sought refuge in were now under threat. A whole range of mental labor skills became automated, and this continues to this day.

In fact, automation usually follows this path: first, the job is broken down into pieces, and “lower-end” pieces are first outsourced to cheaper labor (China in the 20th century or rural laborers that fled to cities in 19th century), then automated and replaced with machines, then integrated into even more powerful machines.

And this automation always moves up the value chain. First, the machine does the arithmetic, but the human is still solving the integrals. Then Matlab comes for the integrals. Next, machines are doing mathematical proofs, and so up it goes the value chain, often until it hits a regulatory block, hence Silicon Valley’s constant desire to undermine regulation and licensing. Doctors are somewhat safe, for example, because of licensing requirements, but technology can find a way around that, too: witness the boom in cheaper radiologists located in India, reading US-based patients x-rays and MRIs; and “homework tutors” that tutor US-based kids remotely from China.

For example, it was nurses who used to take blood pressure. Then it became nurse’s assistants or a medical assistant—much lower-paid jobs that require less training. Then came machines that perform a reasonable job taking your blood pressure, and the job became even less skilled. More and more, you only see your doctor for a few minutes so that her highly-paid time is dedicated to only that which she can do—is licensed to do—, and everything else is either automated or done by someone paid much less.

This arrangement has advantages but it is not without trade-offs. Your doctor will miss anything that requires a broader eye and reflection, because she’s spending very little time with you, and the information she has about you in front of her is low bandwidth—whatever the medical assistant checked on a chart. She may or may not notice your slightly pale skin if it’s not noted on the chart. Most of the time, that’s okay. Sometimes, though, patients spend months and years in this “low-bandwidth” medical care environment while nobody puts two-and-two-and-three-and-that-pale-skin and wait-didn’t-you-have-a-family-history-of-kidney-disease together.

Occasionally, loss of holistic awareness due to division of labor between humans and machines ends up in disasters. This is a worry for flying planes that are so automated that the pilots lose their ability react in manual mode. For example, Air France 447 crashed over the Atlantic, killing 228, because the pilot forgot how to react to a stall—put the nose down, not up. Something every pilot, and most anyone who’s watched a few movies, knows. But when the automated system went down, that pilot simply got confused, and stalled the plane till it crashed.

So, what’s the trade-off here? In general, we are safer (automation makes airline flying safer, in general) except in the long-tail: pilots are losing both tacit knowledge of flying and some of its mechanics. But in general, we, as humans, have less and less understanding of our machines—we are compartmentalized, looking at a tiny corner of a very complex system beyond our individual comprehension. Increasing numbers of our systems—from finance to electricity to cybersecurity to medical systems, are going in this direction. We are losing control and understanding which seems fine—until it’s not. We will certainly, and unfortunately, find out what this really means because sooner or later, one of these systems will fail in a way we don’t understand.

Let’s get back to what happens to humans when the machines come for our mental labor. But remember, my argument is made in the context of current political and economic realities. It’s based on a world in which humans are valued only so far as they are economically productive.

There nothing wrong with not having to calculate logarithm tables by hand, an onerous task undertaken by previous era mathematicians. I often wonder what it must have been like to have compiled one of those essential logarithm books, only to live to the age of machine calculators and see it all become for naught. An act of intense labor—and love, as it was an essential service—that made engineering and navigation (and also, incidentally was crucial to war efforts as is much technological developments) possible became redundant in a *poof*—taken over by a much more reliable, cheaper machine.

But, once again, machines don’t replace humans under conditions of prosperity for all humans—they do so under capitalist market conditions in which machines are chosen because they are cheaper and more docile than humans: they don’t object, talk back, organize, strike, slack. And people made redundant by machines aren't given the choice of spending their in leisure or learn the next set of skills that humans will take refuge in.

But wait, you say, there’s a next set of skills, surely?

That has been the historical argument: sure, robots may replace us, but humans have always found a place to go.

As I recounted, there are really only one and a maybe two thirds examples of such shifts, so far, so forgive me if I find such induction unconvincing. Manual labor (one), mental labor (still happening) and now mental skills are getting replaced, we are retreating, partially into emotional labor—i.e. care-giving.

And now machines, we are told, are coming for care-giving.

We are told that this is because there aren't enough humans?

Let’s just start with the obvious: Nonsense.

Of course we have enough human caregivers for the elderly. The country –and the world— is awash in underemployment and unemployment, and many people find caregiving to be a fulfilling and desirable profession. The only problem is that we –as a society— don’t want to pay caregivers well and don’t value their labor. Slightly redistributive policies that would slightly decrease the existing concentration of wealth to provide subsidies for childcare or elder care are, unfortunately, deemed untouchable goals by political parties beholden to a narrow, über-wealthy slice of society.

Remember: whenever you hear there’s a shortage of humans (or food), it is almost always a code for shortage of money. (Modern famines are also almost always a shortage of money, not food). Modern shortages of “labor” are almost always a shortage of willingness to pay well, or a desire to avoid hiring the “wrong” kind of people.

The author gives the example of Japan as forefront of this development, because, she says, of “workforce shortages.” It’s a good example because it really highlights what shortage of humans actually means: a deep hostility to the “wrong” kind of humans. Japan is notoriously anti-immigrant, and also hostile to women’s rights in terms of childcare and family-career balance. As a result, more and more Japanese women choose not to have children: hence the shortage of Japanese children to take care of parents. And the country refuses to address its demographic crisis by any easing of immigration policies—hundreds of thousands ethnic Koreans who have been in Japan through multiple generations, for example, do not have Japanese citizenship and can only assimilate if they more or less give up their Korean identity.

So, it’s not a shortage of caregivers, it’s a shortage of caring.

Next, consider that emotional labor is all that’s left to escape to as humans workers after manual and mental labor have been already been mostly taken over by machines.

(Creative labor is sometimes cited as another alternative but I am discounting this since it is already discounted—it is very difficult, already, to make a living through creative labor, and it’s getting harder and not easier. But that’s another post).

US Bureau of Labor Statistics projects the following jobs as the ones with the largest growth in the next decade: Personal care aides, registered nurses, retail salespersons, home health aides, fast-food, nursing assistants, secretaries, customer service representatives, janitors…

It’s those face-to-face professions, ones in which being in contact with another human being are important, that are growing in numbers—almost every other profession is shrinking, numerically.

No there won’t be a shortage of engineers and programmers either—engineers and programmers, better than anyone, should know that machine intelligence is coming for them fairly soon, and will move up the value chain pretty quickly. Also, much of this “shortage”, too, is about controlling workers and not paying them—note how Silicon Valley colluded to not pay its engineers too much, even as the companies in question had hoarded billions in cash. In a true shortage under market conditions, companies would pay more to that which was scarce. Instead, wages are stagnant in almost all professions, including technical ones.

Many of these jobs BLS says will grow, however, are only there for the grace-of-the-generation that still wants to see a cashiers while checking out—and besides, they are low-paid jobs. Automation plus natural language processing by machines is going to obliterate through those jobs in the next decade or two. (Is anyone ready for the even worse labor crisis that will ensue?) Machines will take your order at the fast-food joint, they will check out your groceries without having to scan them, it will become even harder to get a human on the customer service line.

What’s left as jobs is those transactions in which the presence of the human is something more than a smiling face that takes your order and enters into another machine—the cashier and the travel agent that has now been replaced by us, in the “self-serve” economy.

What’s left is deep emotional labor: taking care of each other.

And emotional labor is already greatly devalued: notice how most of it is so little paid: health-aides and pre-school teachers are among the lowest paid jobs even though the the work is difficult and requires significant skill and emotional labor. It’s also crucial work: economists estimate a good kindergarten teacher is worth about $320,000 a year, when measured as adult outcomes of those children she teaches well. (And yes, devalued emotional labor is mostly a female job around the world—and the gendered nature of this reality is a whole other post).

And the argument, now is that we should turn care over to machines as well, because, there is a “shortage of humans”.

What are seven billion people supposed to do? Scour Task Rabbit hoping that the few percent who will have money to purchase services have some desires that still require a human?

Turning emotional labor to machines isn't just economically destructive; it’s the very description of inhuman.

In my view, warehousing elderly and children—especially children with disabilities—in rooms with machines that keep them busy, when large numbers of humans beings around the world are desperate for jobs that pay a living wage is worse than the Dickensian nightmares of mechanical industrialization, it’s worse than the cold, alienated workplaces depicted by Kafka.

It’s an abdication of a desire to remain human, to be connected to each other through care, and to take care of each other.

The author says we will be fine with machines because look how much we stare into our phones! What a misunderstanding! That is the opposite of what most are doing on the phone: as I’ve long argued, it’s a desperate desire to remain connected to each other, in a world that makes this hard through suburbs, long work-hours and other physical barriers. Social apps –the ones we use talk to each other— are the biggest slice of almost everyone’s usage of technology. (It’s also why people are fleeing into “walkable” downtowns, away from the cold, humongous malls that can only be reached through cars.)

“Oh look, people are on their phones therefore it’s okay to let machines to take care of them” is a major fallacy, and a major misunderstanding of modern technology use.

So where to go? Here’s where not to go. Expecting all care work to be unpaid and done voluntarily (almost solely by women) is not the path forward.

I don’t mourn if Deep Blue beats Kasparov. Chess is a fine game, but it’s a pretty rigid game, invented by us as a game exactly because it doesn't play to our strengths—that’s why it’s a challenge and a game worth playing. If we were naturally good at it, there’d be no point to it as a game. I don’t mourn not having to dig ditches—though abandoning our flesh as if it were irrelevant is turning out not to be a good idea. Many of us hop on exercise machines that go nowhere to counter our coerced sedentary lifestyle, a development surely bemusing to our ditch-digging ancestors.

But surely we should mourn if we put our elderly and our children in “care” of metal objects animated by software because we, the richest society globally the world has ever seen, with so much abundance of wealth that there are persistent asset bubbles—indicating piles of wealth looking for something anything to invest in—as well as hundreds of millions, if not billions, of under and unemployed people around the world looking for a way to make a living in a meaningful way, cannot bring together the political will to remain human through taking care of each other, and making a decent living doing so.

The Message

Thanks to Clive Thompson

Zeynep Tufekci

Written by

Thinking about our tools, ourselves. Assistant prof at UNC iSchool. Princeton CITP fellow, Harvard Berkman faculty associate, Sociology.

The Message

A Pandaemonium Revolver Collection. Season 2 stars @anildash @alanalevinson @ftrain @hipstercrite @itsthebrandi @jamielaurenkeiles @vijithassar @yungrama @zeynep. Season 1 available on DVD shortly.

Zeynep Tufekci

Written by

Thinking about our tools, ourselves. Assistant prof at UNC iSchool. Princeton CITP fellow, Harvard Berkman faculty associate, Sociology.

The Message

A Pandaemonium Revolver Collection. Season 2 stars @anildash @alanalevinson @ftrain @hipstercrite @itsthebrandi @jamielaurenkeiles @vijithassar @yungrama @zeynep. Season 1 available on DVD shortly.

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