Million Robot Revolution Delayed—iPhone Manufacturer Foxconn Hires More Humans

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Terry Gou is CEO of electronics manufacturer Foxconn. He’s also a big proponent of replacing humans with robots in factories. Gou said Foxconn would replace human workers with a million robots in three years. That was three years ago.

Since that first announcement, Gou has indeed pursued robotics, developing his own robotic arms (or Foxbots as they’re called) to replace humans in his automated factories of the future. But his million robot workforce has yet to materialize.

What has materialized?

Earlier this year, Foxconn said it was preparing to deploy 10,000 Foxbots costing $20,000 to $25,000 to make iPhones. It was said the robots could produce some 30,000 devices a year and Foxconn would add some 30,000 robots annually.

Car assembly lines have long been automated, but some manufacturing jobs still require a human touch.

Car assembly has long been automated, but some manufacturing still requires a human touch.

It isn’t a million robots, but would represent a pretty serious challenge to human workers if accurate and scaleable. To date, the reason factories like Foxconn’s aren’t fully automated is because robots are unable to match the dexterity of human hands and lack the judgement to perform quality control checks on the assembly line.

But instead of the bots driving mass layoffs, the firm reportedly hired a record 100,000 human workers to cope with demand for the latest iPhone. Further, the robots, it was said, would merely assist existing human workers, not replace them.

And then it surfaced that Gou was dissatisfied with his first generation Foxbots. They were not up to snuff in terms of proficiency and flexibility. Generation two is forthcoming. But it’s apparent Gou’s million robot revolution is nowhere in sight.

So who cares if a CEO made an overexuberant forecast? For one, too often big claims make headlines and aren’t scrutinized down the road to see how well they hold up. But there’s another good reason to keep checking in on Gou’s Foxbots.

In the past, we’ve written about worries that robots will replace humans and cause structural unemployment—that is, non-cyclical long-term joblessness. To a degree, Foxconn’s progress represents an early benchmark for such concerns.

Here we have a manufacturing giant with every reason to pour resources into automation. They’ve had three years to develop robots dexterous enough to maneuver circuit boards, place touch screens, and generally automate processes.

Factory robots still require precisely programmed conditions to work well.

Most factory robots still require precisely programmed conditions to work.

The task, however, has proven more difficult than it first appeared, the development has been slower, and human-level performance harder to match. Further, the number of bots is less than promised by two orders of magnitude, and the number of human workers required isn’t down at all—in fact, at least for now, it’s rising.

I don’t take this as evidence the robot revolution won’t happen. Or that it’ll be much slower than expected. But I do think it offers insight into how hard robotics still is—particularly when it comes to physical tasks humans can do without blinking an eye.

Common wisdom has it that the first wave of robots automated manual and physical tasks. But that’s not quite right. There is are still a significant number of manual and physical jobs that are much more easily and cost-effectively performed by humans.

This class of labor includes any job that is unpredictable from one iteration to the next. Such labor might require the worker see and react to a changing environment, to move their position and carefully perform the task from a different orientation, to sort objects of varying size and shape, or to make judgment calls on inspection.

Today’s robots, for example, could never build a house on their own. However, although robots aren’t capable of such feats yet—they likely will be in the future.

For example, computer vision, a key component necessary for recognizing and adapting to changing environments, is progressing at a rapid clip currently.

Team Schaft's robot opening a door at the 2013 Darpa Robotics Challenge trials.

Team Schaft's robot opening a door at the 2013 Darpa Robotics Challenge trials.

The accuracy with which machines can look at a picture or video feed and recognize what they see doubled in the last year. Already there are robots, like the one made by Google-acquisition Industrial Perception, that can look at a stack of haphazardly stacked boxes, recognize their orientations, and decide how best to pick them up.

The robots taking part in the DARPA Robotics Challenge still readily show their limitations—but they also show how much is within reach in the coming years. Challenges include opening doors, driving cars, and using tools made for humans.

Even so, I wonder if intelligent programs may, counterintuitively, replace many jobs of the mind before robots take over all manual and “unskilled” labor—in AI and robotics, the latter problem has pretty consistently proven the harder nut to crack.

The creators of Siri, for example, are hard at work on a new digital assistant that some experts say is the future of intelligent agents. And they’re not alone—Google and Facebook have been collecting AI experts like baseball cards in recent years.

Intelligent, natural language software will be useful on a smartphone or in an automated home—but it could also mark the end of call centers in India or China.

Robot writers are already constructing formulaic earnings reports and sports recaps. It’s not a terribly far reach to find them searching out multiple primary sources, parsing them for facts, and blogging secondary news articles. Watson’s natural language processing abilities already approximate such a process.

future-robot-foxconn-article-3What about the ultimate extrapolation, where robots do everything humans do only much better? That isn’t in sight yet. But it’s certainly conceivable in the coming years.

One of Arthur C. Clarke’s famous three laws of prediction is, “When a distinguished but elderly scientist states that something is possible, he is almost certainly right. When he states that something is impossible, he is very probably wrong.”

So if robots and artificial intelligence match and then thoroughly whip humans at their own game—what then? That is the billion dollar question with no answer.

Some predict a leisure society, some mass unemployment and misery. But why utopia or dystopia? Perhaps it will simply be the real world. A rocky transition in the short run—as we’ve seen in historical episodes of steep productivity gains—and a new economy later on, complete with a wide variety of jobs we simply can’t imagine right now.

Image Credit: Shutterstock.comDARPASteve Jurvetson

Jason Dorrier

Jason is managing editor of Singularity Hub. He cut his teeth doing research and writing about finance and economics before moving on to science, technology, and the future. He is curious about pretty much everything, and sad he'll only ever know a tiny fraction of it all.

Discussion — 8 Responses

  • Mark Lewis October 13, 2014 on 10:23 am

    The last line here simply doesn’t make sense in the context three paragraphs before it. It isn’t a question of whether we can imagine the job or not. You are positing a future where the machines are smarter and more dexterous than humans. Anything humans can do, the bots can do better. If that statement is true in general, there is no point in hiring a human, whether we can imagine the task today or not.

    • De-Shing Ch Mark Lewis October 15, 2014 on 6:48 pm

      the unskilled worker will be replaced by a robotbuilder ( engineer etc.), so where is the problem?
      the unskilled worker will change his profession (maybe an engineer) and the company will increase his productivity.

      overall the economy will increase his productivity.
      it is good, that foxxcon become more productive.

      • Chris F De-Shing Ch October 17, 2014 on 1:36 pm

        Great idea. We’ll just have the displaced factory workers retrain as nuclear physicists or biotech PhDs. Why didn’t I think of that ? Then there’ll be jobs for everyone !

  • VeryconcernedinCanada October 17, 2014 on 2:45 pm

    Some of your readers are missing the point, and it’s REALLY IMPORTANT.
    I’ve been following the progess of robots for many years.
    So far, the best guess i’ve seen is from Oxford, guessing that “50% of ALL jobs will be lost to automation, in the next 20 years”. That doesn’t mean that they will retrain as engineers, because automation WILL BE the engineers of the future. There isn’t one job, (except for artistics endeavours), that won’t be eventually covered by automation. ALL OF THEM! The real question is for our academia friends in economics. How are you preparing for this transition? If not done correctly, it will be a disaster. It’s not a matter of “IF” it will happen, only a matter of “when”. For those of us over 45, a 20 year time frame “isn’t that long”. Check the NOC codes, and think carefully. EVERY SINGLE ONE will be done by automation, 1/2 of which will occur within 20 years. The only single job that won’t be covered is……a Priest!….. Scary……. Imagine even 20 years from now, with a 50% worldwide unemployment rate. Untenable, unless WE begin to change how we think.

  • Alfred Hansson October 22, 2014 on 11:45 am

    I agree that jobs will continue to drop with improved technology. This means that we have to start to prepare now for the future. While manufacturing prices will continue to drop with ever more automation there will, with traditional model be fewer and fewer that at able to pay for the goods. On the whole I think the development per see is good but we have to introduce a completely new economic model in the longer run. Exactly how that will look like remains to be seen.

  • zawy October 7, 2015 on 11:55 am

    People have to first abandon the idea that they can or should control evolution. We are a product of it and eventually will do nothing more than to advance it. It is not blind or random. Evolution is the physics principle of least action, which is the most general form of Newtonian dynamics (more general than Hamiltonian and Lagrangian). It seeks to minimize the average kinetic energy (think waste heat) while maximizing average potential energy (think high-energy chemical bonds). The averages are taken over any and all time scales. The limit is quantum fluctuations, aka black body radiation, aka the 2nd law of thermodynamics emitting excess entropy to the universe. The Earth thereby can decrease entropy locally, emitting 17 photons of lower energy in random directions for every photon received from the direction of the Sun.

    We will continue to find employment that helps direct more and more money towards fewer and fewer people. This is the legal goal of corporations: reduce the number of expensive employees as much as possible for the benefit of the fewest possible shareholders. It seeks profit, but that does not have a legal requirement of actually helping people.

    The reason economics works like this is because silicon, metal, and carbon-carbon bonds store more potential energy than biological bonds. This is the reason we are in the beginning of the 6th great extinction episode. These higher-energy bonds far superior at acquiring energy from the sun with silicon (bye bye photosynthesis), moving matter with metals that direct electromagnetism (bye bye muscles), creating stronger structures with steel and carbon-carbon bonds (bye bye bones), and modeling ways in how to do all of these more efficiently by using metals, silicon, and carbon-carbon bonds to direct electrons or photons instead of 100,000 times heavier molecules and ions that wet brains have to move around. Bye bye economic relevance of brains.

    Economics is evolution’s way of discovering “economizing” ways to do all the above. “Copies” that evolution seems to depend on is less entropy, but it is really a side-effect of least action: when you are searching the highest energy bonds to do your work, you limit your selection to a narrow range compared to random selection.

    If we are “good” then the thing that create us, least action, is “good”. And as we are replaced, it is just “good” increasing. Acceptance is the option no one discusses.

  • Oleg Alexandrov October 12, 2015 on 5:06 pm

    Again and again we are seeing the same moral of the story. The world will change, but the change will be gradual, though perhaps the rate may slowly speed up. Outlandish predictions, whether of singularity or of doom don’t come to pass.

    • zawy Oleg Alexandrov October 13, 2015 on 2:12 am

      It depends on how you define doom. For the ones remaining after a population dies off, life can be really good. An example is the renaissance after the black plague. Currently there is doom in Syria, Greece, and Argentina. Let’s say doom is when 10% die or leave their country of birth because conditions are that bad. So bad they can’t find enough income to have children or their children just leave. Latvia for example has had a 25% decrease in the population since the USSR breakup. Lithuania 11%. There can be a milder sort of doom that is still devastating to the ones having to go through it: Things are not as economically as good as they were in the past for Americans under age 30. The coming technologies require fewer and fewer low-skilled jobs, which is where the young are mostly employed. Only the few with the best technology skills can be employed, and their primary source of employment is in finding ways of not needing to hire other people, including the technologists. When the dollar breaks the U.S. is not going to be so easy. All those banking, housing, and military jobs will to go away, unless the military is able to keep the world dependent on the dollar.

      But getting back to more serious forms of doom where people have to die off instead of simply being the final non-breeding end of their personal 4 billion year old evolutionary path, it’s good to keep in mind that something like 80% of all humans that were ever alive where born in the past 100 years. A massive species die-off is usually the next step. We see many ways this can occur. As global wealth shifts to fewer and fewer hands, the decision process for who gets to live and who doesn’t is already being made. About 10% of all humans that were ever born are alive today. Initial species beginnings aside, this might be a first in the 4 billion year history of evolution. We are used to being in a special time and seeing amazing things, so I do not expect this to make the kind of impression that it should. People enjoy killing each other and I expect us to return to that historical tradition soon enough, with most of us not realizing the evolutionary reason is to make way for machines that are able to create higher potential energy bonds than biology.