Our question should not be, “Will my child be able to get a job?” Our question should be, “Will my child be able to get a job worth having?”
I had the opportunity recently to speak with the Rotary Club of Madison about the future of K-12 education. What follows is an abbreviated transcript of my remarks that morning about the profound and widespread effect of automation on jobs and industries, and some steps that schools might take to prepare young people for the future they will ultimately inhabit.
There was an article in the New York Review of Books that came out this past April, “How Robots & Algorithms Are Taking Over.” This is an excerpt:
Here is what [the] future—which is to say now—looks like: banking, logistics, surgery, and medical recordkeeping are just a few of the occupations that have already been given over to machines. Manufacturing, which has long been hospitable to mechanization and automation, is becoming more so as the cost of industrial robots drops, especially in relation to the cost of human labor…. Meanwhile, algorithms are writing most corporate reports, analyzing intelligence data for the NSA and CIA, reading mammograms, grading tests, and sniffing out plagiarism.
Computers fly planes—Nicholas Carr points out that the average airline pilot is now at the helm of an airplane for about three minutes per flight—and they compose music and pick which pop songs should be recorded based on which chord progressions and riffs were hits in the past. Computers pursue drug development—a robot in the UK named Eve may have just found a new compound to treat malaria—and fill pharmacy vials…. Since replacing human labor with machine labor is not simply the collateral damage of automation but, rather, the point of it, whenever the workforce is subject to automation, technological unemployment, whether short- or long-lived, must follow.
This term, “technological unemployment,” was coined in 1930 in an essay called “Economic Possibilities for Our Grandchildren” by John Maynard Keynes. “We are being afflicted with a new disease of which some readers may not have heard the name,” he wrote, “but of which they will hear a great deal in the years to come — namely technological unemployment. This means unemployment due to our discovery of means of economising the use of labour outrunning the pace at which we can find new uses for labour.... For the first time since his creation man will be faced with his real, his permanent problem: how to use his freedom from pressing economic cares, how to occupy the leisure, which science and compound interest will have won for him, to live wisely and agreeably and well.”
A good example of technological unemployment in our own time, if you think of driving your car as a job (and isn't it?), is the race toward driverless vehicles. Chris Umson, Director of Self-Driving Cars at Google, notes in this TED talk that “for the last 130 years, we've been working around that least reliable part of the car, the driver. We've made the car stronger. We've added seat belts, we've added air bags, and in the last decade, we've actually started trying to make the car smarter to fix that bug, the driver.”
On a personal note, I happen to be a big fan of the Chicago Cubs — they're having a great season; this is going to be the year! — so my wife very romantically agreed that we should drive to Atlanta on our anniversary on July 18th to see the Cubs play the Braves. We left our hotel to go to Turner Field two hours ahead of game time, and yet we barely got to our seats on time. I hadn’t driven in Atlanta in a long time, and I had forgotten how horrible the traffic is. At one point, when we were stuck in the exact same spot for about 15-20 minutes, not moving an inch, I found myself saying this thing that it never would have occurred to me to say even two years ago.
“Before long,” I said to Ruth, “this won’t exist. Computers will drive cars. They can make 10,000 decisions a second, and avoid collisions, and navigate optimal routes, and traffic will simply no longer exist.”
Maybe not my children, but certainly my grandchildren will grow up in a world where the idea of a traffic jam is a complete anachronism because robotic cars will be able to zip people around so efficiently. The principal impediment to efficiency, the human driver, will have been removed from the equation. And this is not a nightmarish, "Terminator"-movie eventuality that I am predicting. Future generations need to have jobs worth having, and driving a car — with its stresses and frustrations, its safety hazards, its time waste — is not a job worth having! We have better, which is to say more human, things to do with our time. And we just aren't good at it. The other day I passed a woman on the highway holding a cigarette in her left hand and texting with her right hand. Not good!
On the evening of August 6th, Randolph will be hosting Neri Oxman, an MIT professor who describes herself as a "material ecologist," to speak to the greater Huntsville community about her work. Please join us for her talk if you are able to come. We have invited Dr. Oxman here because she embodies a visionary way of thinking that takes advantage of technological advancements but is still very human in its essence.
Dr. Oxman has observed that the way we have thought about design since the Industrial Revolution is by parts. She is very interested in singularity of design and using technologies like 3D printing to create uniform design. She challenges in her work the notion that design has to be the way it has always been:
"The world of design as we know it has been subjugated to the rules and legislations of mass production and mass manufacturing. So assembly lines have brought a culture that limits and frames the imagination of designers who think about their designs as an assembly of discrete parts that are put together.”
I am so interested in this quote because with just a few substitutions it impeaches the way that we educate: “The world of education as we know it has been subjugated to the rules and legislations of mass production and mass manufacturing. So schools have brought a culture that limits and frames the imagination of educators who think about their students as an assembly of discrete parts that are put together.”
A typical school imposes three matrices of "discrete parts" on its students: a spatial matrix in the form of uniform and standardized classroom layouts and dimensions; a temporal matrix in the form of the daily schedule; and a program matrix in terms of the particulate curriculum.
You may think that I made up these random start times to make a point: 10:23 a.m. for history, 11:23 a.m. for art, etc. But this is based on a real schedule for a real school in California. How perverse is that? Did you all invite me to our meeting this morning at 7:07 a.m.? Of course not!
One discovers this phenomenon so often in schools, this kind of mechanized thinking, as if kids are on an assembly line, as if failing to get them into class at 9:09 a.m. would be the end of the world. Everything has to run along like an industrial process. We are so accustomed to thinking about schools in this way that it is very hard to think any differently, but this mindset is borne out of mass education in the United States, the movement that began in the late 19th century when education began to be perceived as a right. The idea of free public education took hold across the country, and the way that it was imposed, understandably, was through this kind of mechanized, systematized design. So much about how we live our lives has changed since that time, but so little about how we educate our children has. We live our lives increasingly in terms of individuality and opportunity, yet we continue to educate our children in terms of conformity and standardization. Rather than creating thinkers and dreamers, we persist in manufacturing knowers — despite the fact that computers can neither think nor dream as we can, if at all, and despite the fact that we cannot hope to "know" as quickly, accurately, or voluminously as computers.
In essence, we are spending too much time teaching students to do what they will never be able to do as well as computers and robots, and too little time teaching them to do what computers and robots will never be able to do as well as human beings.
So this is an alternative design that begins to break apart those Industrial Age matrices: modular learning spaces, "deep dive" every-other-day instructional periods, and a curriculum inclusive of cross-disciplinary research and learning opportunities similar to what Finland has recently instituted through its "phenomenon" program. I would also favor alternatives to standardized multiple-choice testing in our schools and a reappraisal of traditional worksheet, quiz, and test formats. Any assessment on which a computer could perform more accurately and more quickly than a human being is a better judge of the sophistication of robotic thinking than of human thinking. This is not to say that there is no role for "robotic thinking" in schools, particularly when students are younger and tasked with mastering basic information (e.g., alphabet sounds, addition and subtraction tables, state and country locations, currency values), but by a certain point we should be privileging human thinking over robotic thinking.
Research projects of individual student origin and execution and multi-disciplinary scope are extremely compelling as implicitly human educational exercises. Students at York School in Monterey, California, undertook such projects in 2014 and 2015. Our students at Randolph conduct similar projects, but I think we have only begun to scratch the surface of their potential.
This graph accompanied an article in the Economist magazine in May. I was fascinated by the creativity that went into it. It depicts use of the London Underground subway system in three dimensions: time by year (left to right), time by hour (top to bottom), and passenger volume (hue intensity). The graph reveals the expansion of London "rush hour" periods year by year. I show this not because you necessarily need to plan your next journey on the Tube, but because it is a fantastic example of compelling data visualization.
Something we can do well that computers can’t is tell a story — and it’s not just that we can do it well, but that we care about it and respond to it. If there is one capacity that I would want to instill in students today, it would be narrative intelligence in all of its forms (written, oral, visual, aesthetic, quantitative, qualitative) and all of its aspects (originality, appeal, relevance, substance). It will stand them in good stead across all career paths and throughout their lives.
If we can shift the work that we do in schools in more relevant directions, those robots may ultimately be driving us to work, but they will no longer be taking our jobs. Thank you.