27 September 2023

We, robots: If robots steal so many jobs, why aren’t they saving us now?

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Matt Simon* says we’ve been led to believe that robots and AI are replacing humans en masse, but the COVID-19 catastrophe is blowing up that myth.

Modern capitalism has never seen anything quite like the novel coronavirus.

In a matter of months, the deadly contagious bug has spread around the world, hobbling any economy in its path.

And that’s all because of the vulnerabilities of the human worker.

When we get sick — or we have to shelter in place to avoid getting sick — the work that depends on people grinds to a stop.

Why haven’t the machines saved us yet?

This economic catastrophe is blowing up the myth of the worker robot and AI takeover.

We’ve been led to believe that a new wave of automation is here, made possible by smarter AI and more sophisticated robots.

Yet our economy still craters without human workers, because the machines are far, far away from matching our intelligence and dexterity.

You’re more likely to have a machine automate part of your job, not destroy your job entirely.

“Robots can very successfully augment human activities,” says Julie Carpenter, a roboticist and research fellow at the Ethics and Emerging Sciences Group at California Polytechnic.

“They can do the labour we don’t want to do or can’t do, and are especially successful at carrying out tasks that we consider repetitive, boring, or dangerous”.

But they’re not very smart, especially when it comes to problem-solving.

During the pandemic, this contrast between humans and machines has become particularly fascinating in Amazon’s warehouses.

Earlier this month, Amazon officials announced that in response to the coronavirus they were hiring 100,000 additional humans to work in fulfillment centres and as delivery drivers, showing that not even this mighty tech company can do without people.

But it, too, is automating parts of jobs.

In one warehouse, the company has deployed squat robots that ferry packages between human workers — doing the heavy lifting while leaving the fine manipulation of objects to people.

“Their need for human labour may fall through time, but for now the growth in demand for their products outstrips any gains from automation,” says Dean Baker, senior economist at the US Center for Economic and Policy Research and visiting professor at the University of Utah.

And if longer-standing industries are any indication, the machines will need human co-workers for some time.

“Even the heavily automated industries still rely on humans for essential tasks,” says Baker.

Hospitality workers have been particularly hard hit, as bars and restaurants and hotels have closed.

Hospitality is the operative word here.

There’s a reason you don’t see too many robot bartenders — well, two reasons, actually: Robots can’t match our manipulation skills, and no one goes to a bar to banter with a machine.

“We know that robots are great at certain things right now, like repetitive work,” says Carpenter.

“And they can do that forever.”

“What’s not so great is anything that has to do with a human-centred context, a cultural context.”

For example, we may never be able to automate the industry that now needs it the most: medicine.

Doctors and nurses and other health workers around the world are working themselves to exhaustion, and many are falling ill.

A hospital isn’t like an automotive factory floor; bedside manner matters.

Patients — especially those stricken with this new disease — are severely ill and scared as hell.

“Whether it’s physical or emotional, people need to feel like their pain is being heard, that their implicit suffering is made explicit and have that reflected back to them,” Carpenter says.

Good luck teaching a machine to empathise with a human on the brink of death.

And indeed, it’s this empathy gap that makes many roboticists think that for this reason alone, we shouldn’t automate other particularly sensitive jobs, like police work and education.

It’s not even clear if we could make robots and AIs sophisticated enough to handle the job.

In Italy, overwhelmed hospital staffers have been making devastating triage decisions, prioritising those who can be saved.

But would you ever task a machine with deciding who lives and who dies?

Hell, we’re having a hard time even figuring out how the algorithms that run autonomous cars should make safety decisions, and that’s divorced from the much larger scale of coronavirus triage.

“I hate to say this, because it’s so overdone, but it’s like the trolley problem, times billions,” says Carpenter.

The trolley problem is a classic thought experiment: If you’re driving a trolley and you see five people on the track ahead, but only one person on a side track, do you pull the lever to switch tracks, actively making a decision that will kill one person?

Or do you do nothing, and passively let the five others die?

These are not decisions we want machines to be making when it comes to hospital care.

“Robots are great at augmenting human skills,” says Carpenter.

“But as the situation now is clearly demonstrating, we absolutely very much need humans to understand larger situations and make decisions.”

Still, robots can go a long way toward assisting humans in a hospital, but they’re particularly tricky to design.

Consider an autonomous robot named Tug, which wheels through the corridors delivering drugs to nurses and food to patients.

Its creators went to great lengths to make it helpful yet polite.

It gently beeps so humans know it’s nearby, and when it waits for elevators, it tells you so: “Waiting for doors to open.”

Some hospitals dress it up in costumes to amuse kids.

It’s a tool, not an employee in and of itself.

By helping deliver supplies, it frees up nurses to do what they do best as humans: interact with patients.

Overestimating robots and AI underestimates the very people who can save us from this pandemic: doctors, nurses, and other health workers, who will likely never be replaced by machines outright.

They’re just too beautifully human for that.

* Matt Simon is a science journalist at WIRED. He tweets at @mrMattSimon.

This article first appeared at www.wired.com.

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