Disruptive Technologies and the Future of Labor


This paper was inspired by a questionnaire from the Millennium Project, a wonderful think tank you ought to visit.

In 1900 41% of Americans worked on farms. One hundred years later this figure had dropped to 2%. This widely cited statistic dramatically depicts the power technology has to save labor and make way for the further flowering of human potential. Although the Luddite forecast did not come to pass, since labor merely shifted, this does not mean this revolution will be like the last. The question now is not if machines will replace the majority of human workers, but when. When will it happen, how will it happen and how will governments address the social and economic disruptions created by the exponential advancement of artificial intelligence, robotics, nanotechnology, synthetic biology and unforeseen synergies between these fields? One cannot destroy a thunderstorm by facing the other way. The inevitability of widespread job displacement must be prepared for now to avoid unpleasantness or catastrophe.

The International Labor Organization estimates global unemployment is currently 6.1%. This is, for most people, an acceptable rate. Public programs, private charities and family members can take care of them. What will this figure look like in ten, twenty or thirty years? By 2020 a great number of jobs in retail and the food service industry will be gone. In the first world it is already more cost effective to replace McDonald’s workers with computerized cashiers. The challenge of making cheap and fully automated fast food “chefs”  has not yet been surmounted. Since machines are notoriously bad at dealing with the unexpected it seems unlikely one will see fully robotic factories or restaurants in the 2020’s, although the number of people required will be slashed and they will serve as little more than passive observers who come to the rescue when, as AI pioneer John Mccarthy put it, “the world changes behind [their] backs.” One famous example of this ineptitude comes from a jam manufacturer. Here machines put the jam in the jars and screw on the lids but do not place the jars on the conveyor belt.

This is because they are delivered in cardboard boxes that do not keep them in place. This lack of consistency, easily dealt with by a human being, is difficult for a machine that expects to see the jars in an exact location at an exact time. This is but one example of Moravec’s paradox, which says it is “comparatively easy to make computers exhibit adult-level performance on intelligence tests or playing checkers, and difficult or impossible to give them the skills of a one-year-old when it comes to perception and mobility.” Although still true to some extent, Moravec is becoming less relevant by the day. Baxter, a robot that can be taught by human workers, does not need to be finetuned by thousands of lines of code. Globally unemployment will likely rise by 5 or 6 percent within the next half decade as machines become cheaper than third world workers and the skills possessed by first world workers become easily duplicated by increasingly sophisticated software.

Yet the professions most likely to be hit by this shift are not exclusively menial or low income. Strides have been made in dispensing with doctors in making diagnoses. In reading X Rays, CAT scans and the like human intelligence will still be needed to check the AI’s conclusions. The same can be said for members of the financial sector who are being replaced by lightning fast algorithms.  In a conversation with AI researcher Peter Rothman I was told about facial recognition software used by banks. For the most part it was accurate, but occasionally it made serious and rather silly mistakes. Thankfully there were humans around to correct its errors. Although Bill Gates foresees robots that can move patients around, it is doubtful an affordable, or even incredibly expensive android, will be able to serve as a nurse or caregiver within the next 30 years. There are simply too many variables to account for and there is, of course, the preferences of the patient, which more than likely lean more towards carbon than silicone. This is also true for psychiatrists, bartenders, musicians, personal trainers, teachers, gourmet chefs, actors, cosmetologists, surgeons and dentists. It would be foolish to say they cannot or will not be replaced, but their professions at this time seem better protected than others.

If significant changes are not made to current education systems unemployment will explode in the 2030’s, going beyond 25%. As the future becomes more distant it becomes increasingly difficult to predict. As a halfwit I do not want to be confused with a complete idiot. 2040 and 2050 are too far away to forecast with any certainty whatsoever. It is hard enough to guess at what will happen three months from now. Yet the Millennium Project, as I understand it, is more concerned with finding solutions than with precise projections (which are nearly impossible to come to anyway). My gut feeling is unemployment will remain constant or drop after a sharp climb in the 2020’s.

This rise could be mitigated if nations begin to invest heavily in their infrastructure or, if, they decide to go to war with one another. Otherwise the loss of aggregate demand and another financial crisis brought on by 18 year land mania cycle (which allowed economist Fred Foldvary to correctly predict the time and nature of the 2008 crisis) will compound human suffering greatly. Remember, one is only considered unemployed if one wants work. Because consumer goods will be cheaper and alternative sources of income will, perhaps, be stumbled upon by the jobless. DIY synthetic biology and 3d printing will disrupt labor market, but they will also reduce the cost of living and give many enthusiasts a tremendous amount of self-sufficiency. Thanks to modern biology, a closet or garage can serve as a sprawling farm or pharmacy. Nanotechnology will make a profound impact upon numerous sectors, but since it is such a broad and relatively nascent field, it is hard to predict how it will evolve. Treat it as a bevy of Black Swans.

Due to the regulations of various health agencies  it may be widely adopted later rather than sooner. In Ungifted: Intelligence Redefined Scott Barry Kaufman dissects the failings of schools to identify unique or unusual talents.I doubt publicly sponsored institutions, and their infamous sluggishness, will adapt to accommodate different types of students with different interests. While the introduction of new tests and approaches could help, and while his major points are true and give one a fuzzy feeling deep inside, IQ tests are still useful and meaningful. Those who score exceptionally well should not be allowed to slip through the cracks anymore than those who are not misdiagnosed by them. In his essay the Inappropriately Excluded Michael Ferguson claims people with extremely high IQs are underutilized because they are an “affront” to established ways of doing things. To paraphrase Buckminster Fuller, it is foolish to assume each and every person needs a career. More now than ever a breakthrough made by a single scientist can generate prosperity for thousands, millions or billions of people. Besides the humanitarian aspects of these tragedies, if the most intelligent and creative members of society are being thrown into a one-size-fits-all system, how can the world expect to achieve innovative terminal velocity within the next decade? The focus can not only be in training armies of mediocre minds.

They are already becoming obsolete. The current fetish for specialization, though justified given its necessity in many instances, will in the coming decades do more to bog down progress than accelerate it. In The Second Machine Age Brynjolfsson and Mcafee explore the importance of new combinations by citing the economist Martin Weitzman: “In such a world the core of economic life could appear increasingly to be centered on the more and more intensive processing of the ever-greater numbers of new seed ideas into workable innovations… In the early stages of development, growth is constrained only by the ability to process them.” Thus, curricula should not be confined to a single specialization. Having students who know all the functions in the Python’s libraries may not be the best thing for them or society. Rather, a broad exposure to disparate disciplines in elementary school, which have been mistakenly deemed too difficult for children, would lay the foundation for further exploration. As Maria Droujkova said about the current state of math education, “[it] has nothing to do with how people think, how children grow and learn, or how mathematics is built.”

Mathematics, she goes on to say, is about structures and patterns, not “little manipulations of numbers.” In other words, what are considered advanced topics like calculus, can and ought to be taught to young children. Human calculators have long since been supplanted by machines, which is fine. Mathematics is not about crunching numbers anymore than learning is about memorization, particularly in an age in which information can be stored and recalled so easily. While the assistance of AI and cybernetic brain implants could give ordinary people polymathic powers, it would not be prudent to hold our breath. Rather, it is critical to focus on those born with unique talents and those born with the sort of intellects needed to function at higher levels. The question becomes how? How can governments facilitate the development of human potential in its gifted citizens and provide for those who have slightly less to offer the modern world? Like the buried banknotes Keynes infamously discussed, research can serve as a general and ongoing financial stimulus. Unlike the burying and digging up of currency, however, research has other benefits. Like the monuments of antiquity it can consume an enormous amount of labor, that is, if laborers has access to the resources needed to do research. Retraining for a specific task is an ineffective solution.

A recently revamped factory may now only need a couple watchmen and a few quality assurance managers. This positions will be competed for by hundreds or thousands of now displaced links on its once organic assembly line. Moreover, by the time they are retrained, it is likely their new job will also be gone! By keeping their current curriculums and failing to address individual needs, public schools are grooming children for a world that no longer exists. Maker hubs, coding bootcamps and the like are much less expensive to run and much better at quickly giving people the experience the need to make useful contributions than a university, which requires unneeded prerequisites and tuition money. The notion of every person being self-employed seems ridiculous, but every person, as hinted to above, can become self-sufficient. For this outcome a government initiative seems unnecessary. Self-interested parties will learn how to make household items and grow food from their neighbors or the internet.


Graphic courtesy of Brian Tomasik, His article is here.

What about death by titanium terminators? What about inequality? Above is a graph of predictions made by those inside and outside of the AI field. There is something striking about the data: those who are most skeptical of the emergence of strong AGI (Artificial General Intelligence) have the most hands-on experience in developing software.  As Monica Anderson writes, “The purpose of intelligence is prediction. Humans have used their minds to predict the behavior of sabertooth tigers, the right day in spring to plant the crops, and the behavior of opponents in games like chess and tennis…The insight that the complexity and unpredictability of the world enforces a limit on prediction quality – and hence intelligence – pretty much invalidates the AI Singularitarians’s [to borrow a phrase from Ben Goertzel] ‘Scary Idea.’” The lack of AGI may also put a cap on just how many jobs will be, in the long run, lost to computer programs. Intuition and intelligence are two different things, to take another page from Ms. Anderson. Perhaps “intuitive” algorithms will be made. Augmented humans have the potential to do more good and evil than purely synthetic contraptions. There is no need to reinvent the wheel and I am under the impression the brain is considerably more difficult to recreate.  For the sake of the following paragraph let us assume unemployment levels become problematic or catastrophic. What then?

Can inequality be solved by taxation or fiscal stimulus? As wonderful as it would be to have armies of formerly jobless twenty somethings beautifying our state parks, this does not seem like a sustainable state of affairs or, for that matter, a very good use of their time. Although given the present state of infrastructure in many developed nations, it may be wise to begin revamping roads, water towers and like while pushing unemployment back into its hole. Eventually universal basic income will be necessary. Basic income elicits clenched fists among those who believe unearned money exudes sulphuric fumes hewn in Hell’s Ninth Circle, and the arguments against it take on the same sort of emotional tone one would expect from a roundheaded pilgrim than an empathetic social engineer, but handouts are preferable to chaos. Now what? What if the future is boring? Already people can happily fill their empty hours with television, video games and, on occasion, books. Virtual reality and mood-altering drugs will be more refined and more prevalent. These, along with a falling cost of living, could play a significant stabilizing role in the 2030’s.

While many envision a Jetsons world teeming with massive metropolises, it seems more likely disruptive technologies, like drones and 3d printers, will make rural living more affordable and more desirable. Rent prices will not plummet. They can only be expected to rise. Fuel is a bit of a wild card and will be addressed in a later paper. The adverse effects of urban environments are numerous and, I would imagine, the spreading out of people will do much for humanity’s overall happiness. In these artificial paradises people may become indifferent to domestic and geopolitical matters. Innovation normally does not spread evenly, but as the internet makes paths into more and more remote regions one can expect even poor nations to adopt the cutting edge. Kenya’s wholehearted embrace of Bitcoin may seem shocking, but more and more people will become involved with far-flung projects in software and biology thanks to the decreasing costs of entry and a widening dissemination of information. That’s all for now.

Works Cited

Anderson, Monica. “Problem Solved: Unfriendly AI.” Problem Solved: Unfriendly AI (n.d.): n. pag. Syntience. Syntience, 5 Mar. 2011. Web. 27 Mar. 2015. <http://syntience.com/unfriendlyai.pdf&gt;.

“Automation, Jobs, and the Future of Work.” Automation, Jobs, and the Future of Work. Mckinsey and Company, 12 Dec. 2014. Web. 26 Mar. 2015. <http://www.mckinsey.com/Insights/Economic_Studies/Automation_jobs_and_the_future_of_work?cid=other-eml-alt-mgi-mck-oth-1412&gt;.

Brynjolfsson, Erik, and Andrew McAfee. The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. N.p.: n.p., n.d. Print.

Foldvary, Fred E. “The Depression of 2008.” The Gutenberg Press (n.d.): n. pag. Www.foldvary.net. Gutenberg Press, 18 Sept. 2007. Web. 27 Mar. 2015. <http://www.foldvary.net/works/dep08.pdf&gt;. Kaufman, Scott Barry. Ungifted: Intelligence Redefined. N.p.: Basic, n.d. Print.

Manyika, James. “Disruptive Technologies: Advances That Will Transform Life, Business, and the Global Economy.” Disruptive Technologies: Advances That Will Transform Life, Business, and the Global Economy. Mckinsey and Company, 13 May 2013. Web. 26 Mar. 2015. <http://www.mckinsey.com/insights/business_technology/disruptive_technologies&gt;.

“Michael W. Ferguson.” : The Inappropriately Excluded. Michael Ferguson, Nov. 2014. Web. 26 Mar. 2015. <http://michaelwferguson.blogspot.com/p/the-inappropriately-excluded-by-michael.html&gt;.

Rawlinson, Kevin. “Microsoft’s Bill Gates Insists AI Is a Threat.” BBC News. BBC, 29 Jan. 2015. Web. 27 Mar. 2015. <http://www.bbc.com/news/31047780&gt;.

Vangelova, Luba. “5-Year-Olds Can Learn Calculus.” The Atlantic. Atlantic Media Company, 03 Mar. 2014. Web. 27 Mar. 2015. <http://www.theatlantic.com/education/archive/2014/03/5-year-olds-can-learn-calculus/284124/&gt;.

Walker, Mark. “BIG and Technological Unemployment: Chicken Little Versus the Economists.” Jetpress.org. Journal of Evolution and Technology, 24 Feb. 2014. Web. 24 Mar. 2015. <http://jetpress.org/v24/walker.htm&gt;.

Wiseman, Paul. “Robots Are Replacing Us Faster Than We Expected.” Inc.com. Inc, 10 Feb. 2015. Web. 25 Mar. 2015. <http://www.inc.com/associated-press/robots-are-replacing-human-factory-workers-at-fast-pace.html?cid=sf01002&gt;.



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