The emergence of blended learning, ed tech, and online secondary schools might cause educators to wonder what their role might be in the future, when machines rule the world.

The authors of The Second Machine Age describe the coming revolutionary changes to all aspects of our lives, but their recommendations for how individuals and schools can better prepare themselves fall flat.

Below, I highlight key sections from the book and extend the recommendations to support the claim that teachers must primarily be designers and facilitators of learning.

We’re Going Parabolic!

We’ve arrived at an absolutely unique and critical turning point in human history resulting from an imminent full realization of the capabilities of machines (i.e. where we currently sit on the curve of Moore’s Law), Erik Brynjolfsson and Andrew McAfee argue in The Second Machine Age.

Their case is rhetorically bolstered by the use of the first person plural throughout, as the authors themselves are apparently always in agreement, which is just a bit creepy. Nevertheless, they do lay out an effective case.

After all, there’s no denying something must be afoot to explain why contemporary Americans find themselves:

• having conversations about the blockchain with their barbers
• willingly trading any semblance of privacy for the convenience of being able to hear their favorite Wang Chung song by simply shouting at a nearby speaker
• living in a putatively evolved democratic republic whose president is you know who
  

I appreciated the section on Moore’s Law, which law I’ve often wondered about since it seems unacceptably bizarre to have an output “law” dependent on so many inputs. The authors quote the actual passage from a 1965 article in Electronics magazine, wherein Gordon Moore observes that computing power relative to component costs increased, by a factor of two, each year for about ten years and, as he put it, “[while] the rate of increase is a bit more uncertain, there is no reason to believe it will not remain nearly constant for at least ten years” (40).

I had pictured Gordon Moore as a sort of Bill-Gates-like Hammurabi, raining down legislation like lightning bolts from a throne made of ones and zeros, but in reality he timidly–with the rhetorical equivalent of an index finger spectacle-adjustment and a shy giggle–suggested that computing power per unit of resource would double every year.

What’s crazy is he turned out to be right, or right enough, and the authors point out how unique this progress is. For just one example, the authors note that “there was no period of time when cars got twice as fast or twice as fuel efficient every year or two for fifty years” (41). In addition to the domain uniqueness, humans are ill-equipped to reckon with the nature of this sort of doubling, as evidenced by the old saw the authors relate of the clever man who asked the emperor of the Gupta Empire for a grain of rice doubled on each square as his reward for inventing chess. The emperor granted the request without hesitation and with the declaration “Make it so!” “If his request were fully honored,” the authors wryly remark, “the inventor would wind up with 2 to the 64, or more than eighteen quintillion grains of rice” (45). The emperor’s folly completes the nerd-fantasy, where knowing a bit of math allows you to pull one over on the powerful, since “making it so” is physically impossible.

Those of us reading the book will not be like the emperor; the authors invite us into the group that recognizes the profound consequences of both the mathematics and the implications of Moore’s Law.

A Process for Educators to Ride This Gnarly Wave

First for individuals hoping to educate themselves: the authors concede that their recommendations about how people “can remain valuable knowledge workers in the new machine age are straightforward: work to improve the skills of ideation, large-frame pattern recognition, and complex communication” (197, emphasis mine).

The authors acknowledge that in order to switch the skills taught (from the traditional three R’s to those listed above), schools must change. Precisely how is not made clear, beyond their recommending that more students access Montessori-type schools, since the founders of Google, Amazon, and Wikipedia all attended such schools and because they offer opportunities for self-organizing learning.

Rather than pushing my thinking, the recommendations section, bland as it is, corroborated several of the practices pushed as many effective schools: design thinking, authentic work, and reflection.

Designing Thinking specifically scaffolds and supports ideation. The frequently deployed Stanford d.school’s Designing Thinking Process asks students to grapple with a challenge by empathizing with those who experience it, then define the problem, then ideate by brainstorming solutions that can be prototyped and tested

Here’s the process in visual form:

Humans Deserve Worthy Work

As important as the process in developing students’ “large frame pattern recognition” is the authenticity of the problem. Lucky students at great schools regularly tackle problems such as gun violence, homelessness, childhood obesity, and the disappearance of community spaces, which require them to nimbly apply learning, thinking, and ideas from one frame to another. For example, they can plumb the depths of their own motivations in order to ideate around how a community might address health issues related to poor nutrition–a domain leap that computers currently cannot do.

Finally, because this sort of learning is so much more amorphous than the traditional narrow academic skills, assessment must also be much more personalized and reflective, and allow students draw their own conclusions about growth through regularly scheduled (and ad hoc) dialogue with teachers, peers, and professionals in the field.

Authentic work + human-centered process = significant learning.

The End.

Postscript

Just as a kind of thought experiment, or a bit of ideating: what if we live today inside a giant Turing Test, and we are all both examiners and examinees? We have elected as president the most human candidate, which has perhaps come to mean the least computer-like. No computer could possibly be as unpredictable, as openly but self-blindly flawed, as bizarrely conscience-free, as confusingly multi-masked, as downright human as you know who–not even a computer would believe he is a computer.

I can’t escape the image of him suited and smiling against the backdrop of a post-apocalyptic hellscape, hair intact, and in that not so puny, inexhaustible voice, still talking.

Doggedly stupid persistence in the face of mathematics and physics seems to be the stuff of humans. Be aware that in some versions of the clever chess-inventor story, when the emperor realizes he’s been had, he orders the clever man beheaded. Just because you computers can do much of our work, it doesn’t mean we should let you computers have all the fun. And right now we can still pull the plug.