Prologue: Welcome to THAMES Academy

In this book, we argue that the revolution being wrought by accelerating advances in artificial intelligence, machine learning, and robotics necessitates equally dramatic new pedagogies, some of which our teachers have yet to invent. 

In succeeding chapters, we’ll visit schools where these changes are already beginning to take root. But to better illustrate the full scope of what’s possible, and what must take place, let’s engage in a time-honored thought experiment of “looking backward” to imagine what could be in the near future. In our case, a somnolent Massachusetts high school principal — let’s call him Rumple — falls asleep late one afternoon in January 2020. He awakes to find that he has, astonishingly, slept straight though the intervening twenty years. It is the year 2040. 

He emerges from his secluded home one spring morning to find that the neighborhood hasn’t changed much, aside from the strange little cars in everyone’s driveways. In his own driveway, the faded blue Honda Accord that’s forever burning oil is gone, replaced by (and he’s not really sure how it got there) a vehicle the size and approximate shape of a doublewide lounge chair with a gently curving roof. 

Not exactly sure how long he has been asleep, Rumple does the first thing that comes to mind: he skips the strange car and walks to his old familiar school, just a few blocks away. 

Like the neighborhood, the high school seems to have changed little. It’s still a solid, three-story, red brick edifice at the heart of a residential area, though a sign on the front door now reads “Winterville THAMES Academy.” Not quite sure what to make of this — the Thames River is in England, thousands of miles away — he pulls on the massive door, anticipating that, as always, it’ll be locked. To his surprise, it opens easily. “Hmm, they’ve really let security lapse,” he says to himself. 

What he doesn’t know is that he has just activated an automated infrared/X-ray/iris scanner. By the time Rumple walks the several steps to the spot where his old office used to be, the system has silently identified him as an unarmed, middle-aged male, previously unregistered, no prior school contact — he’s rated “harmless,” with a 72 percent probability he’s a visiting grandparent. The system returns a 24 percent probability he’s there to complain about kids on his property, a 4 percent probability he’s lost. 

He stands at the front office, but no one is there to greet him. As he looks around for the receptionist, a pleasant but disembodied female voice says, “Welcome,” while a device resembling an ATM issues a thin plastic sticker that reads, “Two-Hour Pass — Restricted.” He pulls the sticker from the machine and pats it onto his chest. While he doesn’t know it, the sticker will, if needed, limit which areas he can enter, triggering an alarm if he strays. 

Moments later, he comes face-to-face with the principal —  let’s call her Bellamy — a woman in her late 30s with a ready smile and a firm handshake. She’s standing there because her Oculus Everyday glasses alerted her to the unfamiliar old man in the vestibule and suggested she go meet him before he gets too far. 

With the reader’s permission, we’ll skip over the moment of revelation, the scenes of amazement, of Rumple’s dawning realization that it’s 2040 and most of what he knew is gone or going fast. We’ll only mention that Bellamy, the new principal, immediately recognized him and now, sitting across the couch from him in her office, informs him that she was, in fact, a former student of his, at this very high school, back when it was plain old Winterville High. 

Over a bracing cup of coffee, he gets his bearings and soon realizes that he has stumbled upon something educators live their whole lives dreaming about: the ability to see not only how their own work has turned out but how schools, students, and teachers have changed over a generation — for better or worse. 

Bellamy, sensing that he’s lost in thought, tries to bring him back to the “present.” 

“I graduated in the spring of 2020 — just a few months after you . . . fell asleep.” 

“You did?”

“Indeed,” she says.

Rumple snaps out of his reverie — like most good teachers, he has a kind of deep, if imperfect, memory for his former students. And, of course, hers was the last class he remembers. Once he realizes who Bellamy is, he recalls that she had aspirations to major in computer science. 

“You were going to work in tech — I remember you were smitten with Silicon Valley,” he says. 

“Yes, exactly!” she answers, pleased that he remembered. 

“So . . . how did you end up here, back in your hometown — as a high school principal?” 

“Well, some things don’t work out as planned, which sometimes is a very good thing. It’s a long story.” 

Just then, Bellamy’s glasses remind her that it is almost lunchtime, and she offers to take Rumple out for a hot meal. 

“I’ll let my assistant know I’m taking a long lunch,” she says as they rise. They walk through the unoccupied outer office and Bellamy says in a loud, clear voice, “I won’t be back for a while, Annie. Could you please call for my car? Also, can you reschedule my afternoon appointments?” A green light above the door blinks and that familiar, disembodied female voice says, “Your car is on the way. Your appointments have been rescheduled. Have a good afternoon, Dr. Bellamy.” 

Doctor Bellamy, eh?” Rumple queries approvingly, impressed. Bellamy smiles with a mixture of pride and humility. 

“Yes, well . . .” 

“Don’t forget,” the disembodied voice interrupts, “you also have a series of parent meetings beginning at 9 a.m. tomorrow and a Friday deadline for a grant proposal that is 62 percent complete. Based on past successful applications, your proposal currently has a 23 percent probability of being funded. Would you like to hear a few ways to improve it now?” 

“No, thank you, Annie,” she says, taking Rumple by the arm and leading him through the door. “Have a nice afternoon.” 

“Thank you. I’ll send those suggestions as an addendum to my previous memo. Have a nice afternoon.” 

Rumple looks behind them to see the office lights dim. “Your assistant?”
“She keeps me on track, but she can be a bit . . . solicitous,” Bellamy says. “I need to tweak her helpfulness settings. She’s killing my long-term memory.” 

At the curb, almost as soon as they approach, a tiny self-driving car appears, much like the ones Rumple saw when he first ventured forth from his home. They climb in, travel several blocks, and soon arrive at a brightly lit neighborhood restaurant with inviting outdoor seating. Once they emerge from the car, it beeps once and drives off. 

“Self-parking,” Bellamy says. 

“Amazing,” Rumple says as he watches the car roll down the block and disappear around a corner. 

A greeter welcomes them warmly and asks Bellamy how her family is, then guides them to an outdoor table and disappears. They take a seat and, though it’s only just noon, Bellamy surmises that Rumple’s morning might call for a drink or two. She clears her throat and says, “Could we have a lime seltzer and . . . ?” she looks at Rumple. “What are you drinking?” 

“Um, scotch,” he says. “On the rocks.” 

“Scotch on the rocks — make it a Macallan Twelve-Year. Oh, and an order of your antipasto,” Bellamy says. 

Rumple blinks. “Who are you talking to?” 

“The kitchen,” she says, pointing to a pulsing, green-lit button situated next to a microphone embedded in the table. She pushes the button and it turns red. Seconds later, a tiny automated cart sidles up to the table. She removes the glass, hands it to Rumple, then lifts out a glass bottle of seltzer for herself and toasts their health. Rumple takes a substantial swallow of scotch and places the glass on the table. 

“Amazing,” he says. Just then another cart arrives, carrying a large plate of Italian meats, cheeses, olives, pickled vegetables, and a small loaf of bread. 

“The bread here is addictive,” Bellamy says. “They make it in house.” She lifts the plate and the robot cart speeds off. As he watches it round a corner, Rumple recalls that Bellamy had said she’d worked in tech after graduation. 

“Oh yes,” she says. “I studied computer engineering. I spent four years after college at Apple, teaching Siri — remember her? — how to more accurately suggest to users where to buy an upright piano or a ripe dragon fruit. The problems were delightful — try teaching a bot the difference between Elvis and Elvish — but the work, to be blunt, got dull. I left and went to grad school to study history.” 

“History? Good god, I studied history!” Rumple says, the scotch taking the chill off his singular morning. 

“I loved it, but my parents were not amused,” Bellamy says. “They thought tech was the living end. They’d spent years reading about how we’d soon need fewer teachers, how online learning would make us all obsolete. But I saw that a shift was happening. As much as all of us in tech believed that we could solve every problem with the brute force of data and computing, I knew we’d always need teachers — maybe just not the same kinds of teachers.” 

Rumple fears what’s coming next and takes a large slug of his drink, but Bellamy changes the subject: “In grad school, I studied nineteenth- and early twentieth-century industrialization,” she says. “It changed how we worked and where we lived. Even with all that time for workers to adjust — more than a century — the entire industrial era was fraught with conflict: the Populist revolt, union struggles, rapid urbanization, and massive immigration.” 

“Of course,” Rumple says. 

“And of course, in the late twentieth century, vast portions of the workforce shifted to service sector jobs.” 

“Yes,” Rumple says. “I remember that. I lived through it. But please — I have to ask: What else happened after I dozed off?” 

“Well, actually it happened before you dozed off,” Bellamy says. 

“Before? I remember the 2008 recession, but . . .” 

“I hate to bring this up,” Bellamy replies, biting her lip, “but do you remember 2016?” 

“Yes, of course,” Rumple says, then deflates slightly into his chair. 

“I was just a high school first-year at the time,” Bellamy says. 

“‘First-year’? You mean freshman?” 

“We call them first-years now, sir,” she says. “‘Freshman’ is considered insufficiently gender-inclusive. In any event, historians now agree that the rise of Donald Trump and his raw populist anger were largely a response to automation.” 

“Automation? You mean immigration.” 

“Oh no,” she says, plucking an olive from the plate. “Automation.” 

“So, you’re saying . . . robots brought us Trump?” 

“You have to remember,” Bellamy says, “American manufacturing jobs were disappearing, and millions of blue-collar workers were angry and bewildered. Even though unemployment was low at the time, those who were employed experienced decades of wage stagnation and insecurity.” 

“Yes, but . . .” 

“Trump blamed immigrants and offshoring, of course, but these were responsible for just a fraction of all that. Here’s the amazing thing: after the 2008 recession, manufacturing actually picked up. Demand for American-made goods rose in the decade before 2016. To meet the demand, manufacturers stepped up production.” 

“So why the anger?” Rumple asks. 

“Well, manufacturing recovered, but the manufacturing job market didn’t.” 

“I’m not sure I follow you.” 

“Companies increased production not by hiring more people, but by bringing in an ever-growing army of industrial robots. US companies were producing more goods than before, and they were doing it here — but with fewer human workers. I remember reading about a textile mill in North Carolina where fewer than 150 people did the work once done by 2,000. On the overnight shift, eleven people ran a facility as big as four soccer fields.” 

“You mean football fields?” Rumple says. 

“Oh no,” Bellamy says. “American football was outlawed years ago as inhumane — all those brain injuries to young people. What a disaster! The United Nations eventually categorized the NFL as a human rights violator. It relocated to Eastern Europe.” 

“Fascinating,” he says. 

“Indeed,” she says. “But as many of us focused on industrial automation, a bigger crisis was taking hold, and it wasn’t on the factory floor. It was on the trading room floor, in the pharmacy, the medical examination room, and the courtroom. It was in the newsroom, the psychiatrist’s office, and the attorney’s conference room. While millions fretted about robots replacing blue-collar workers, artificial intelligence and machine learning began colonizing highly skilled, college-educated, ‘thinking’ professions like ours. Digital technology began doing for brain work what the steam engine and its descendants had done for muscle power. As technology improved — and unlike human brain power, it has always improved exponentially — its only limitation was the imagination of programmers, designers, and forward-thinking innovators within the professions themselves.” 

“I fear where this is going,” Rumple says. 

“Over the next few years — just the blink of an eye in historical terms — millions of college-educated white-collar workers saw their jobs transformed. Many workers reskilled, but millions found themselves left behind, hustling to make ends meet in jobs that had once been full-time but were suddenly part-time, since many of the low-grade, routine, repetitive tasks they’d always done were suddenly automated.” 

As he listens, Rumple can’t help but look out the window. He watches as dozens of those tiny, self-driving cars zoom by. “You know,” he says, “I just realized that in just the few hours I’ve been, well, awake, I’ve seen four good middle-class service jobs — receptionist, secretary, driver, and waiter — performed entirely by robots.” 

“Then you see my point,” Bellamy replies. Sensing his despair, she adds, “Of course, technology almost always creates new kinds of jobs. It’s true, robots brought our drinks and our appetizer, but they also freed up the restaurant owner to build and operate his own in-house bakery — mostly automated, of course — and spend more on high-quality ingredients.” 

“The bread is amazing,” Rumple admits. 

“All the same, the transition took years, with many false starts and stops.” 

“How bad was it?” Rumple asks. 

“Well, imagine an economy in which the ranks of the bluecollar unemployed or underemployed swelled with the addition of white-collar workers — expensively educated millions who always assumed their ‘knowledge economy’ jobs would render them immune to technological obsolescence. The politics of anger took on a new scale altogether.” 

“Oh my,” Rumple says. “Then what happened?”

“Do you really need to ask that?”

“Yes!” Rumple says, sitting forward in his chair. “Please tell me: What happened?

Bellamy smiles. “Our education system came to the rescue — as it always does.” 



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