In the 20th century, the school as a factory metaphor appeared.
Our schools are, in a sense, factories, in which the raw products (children) are to be shaped and fashioned into products to meet the various demands of life. The specifications for manufacturing come from the demands of twentieth-century civilization, and it is the business of the school to build its pupils according to the specifications laid down.
The school as a factory metaphor worked for the past century, as education mainly was linear: get an education, get a job, retire. Information was at a premium and scarce, so it was perfectly logical for schools to cram information into children’s brains with notions about mathematics, literature, geography, history, biology, etc.
But in the 21st century, we have access to a few lifetimes of information with all the shades of disinformation (information meant to deceive – e.g., trolls posting fake information) and misinformation (defined by Nina Schick in her Deep Fakes and the Infocalypse book as “bad information with no malicious intent behind it” – e.g., our friends and family sharing disinformative content).
If current laws still apply, children and teenagers in school these years will retire in the 2070s-2080s. As pandemics, wars, and AI have shown, we can’t precisely predict what will happen one year from now. And yet, schools and parents are preparing youths for jobs that will either become obsolete, automated, or not yet invented.
So, what kind of education do we and our children need to succeed? What knowledge is essential today?
Almost five decades ago, Alvin Toffler published a ground-breaking book, Future Shock (still in print, which is an extraordinary feat for a book that tries to predict the future). In his book, Toffler adapts the concept of culture shock to a rapid pace of technological changes. Culture shock happens when we find ourselves in unfamiliar environments. The new environmental reference points (language, food, clothes, social norms, mindsets, etc.) are strikingly at odds with what we carry from home. This experience can be profoundly disorienting or traumatic.
Toffler argued that due to the rampant technology-related change, we would experience future shock, similar to culture shock. Immerse ourselves too quickly into an unknown future, where the scale and speed of change are exponential, and we experience shock waves.
To survive the future shock,
The illiterate of the 21st century will not be those who cannot read and write but those who cannot learn, unlearn, and relearn.
Alvin Toffler
As we have fast food, fast fashion, and fast entertainment, we could, unfortunately, acquire fast or volatile knowledge and build our temporary expertise on quicksand. Training ourselves in a specific field, only to be rendered obsolete as that field no longer met the latest demands, explains why we should aim to be strategic in our learning, accumulating fundamental and unchanging knowledge and knowing how to retrieve it.
Paul Graham, computer scientist, entrepreneur, and co-founder of Y Combinator — the start-up launcher of Airbnb, Dropbox, Stripe, DoorDash, Reddit, etc. — also writes about the importance of adaptability rather than fixed plans, advocating for a flexible mindset. In a high school graduation speech he never delivered, Graham writes that:
There are other jobs you can’t learn about because no one is doing them yet. Most of the work I’ve done in the last ten years didn’t exist when I was in high school. The world changes fast, and the rate at which it changes is itself speeding up. In such a world, it’s not a good idea to have fixed plans.
And yet every May, speakers all over the country fire up the Standard Graduation Speech, the theme of which is: don’t give up on your dreams. I know what they mean, but this is a bad way to put it, because it implies you’re supposed to be bound by some plan you made early on. The computer world has a name for this: premature optimization. And it is synonymous with disaster.
… I propose instead that you don’t commit to anything in the future, but just look at the options available now, and choose those that will give you the most promising range of options afterward.
Walter Isaacson’s biography, The Code Breaker of Jennifer Doudna, the 2020 Nobel Prize winner in Chemistry for her work on CRISPR, a powerful gene-editing technology, offers an intriguing perspective on the importance of life sciences in the modern era.
If I had to do it all over again—pay attention, you students reading this—I would have focused far more on the life sciences, especially if I was coming of age in the twenty-first century. People of my generation became fascinated by personal computers and the web. We made sure our kids learned how to code. Now, we will have to make sure they understand the code of life.
Walter Isaacson – The Code Breaker
CRISPR is an extraordinary discovery because it makes it easy to change the world. The potential applications of this technology range from treating diseases like cancer to developing crops resistant to drought and disease, which could significantly mitigate food shortages amid climate change.
However, the accessibility and ethical implications of gene editing remain controversial. Feng Zhang, a biochemist known for his contributions to CRISPR technologies, highlights potential social inequalities:
“Look at what parents are willing to do to get kids into college,” he remarks. “Some people will surely pay for genetic enhancements. In a world where some don’t have access to eyeglasses, it’s hard to imagine equal access to genetic enhancements.”
Walter Isaacson – The Code Breaker
Words with significant concerns, as already in 2018, the birth of gene-edited babies without ethical oversight, signals alarming trends.
Integrating ethical accountability into education connects deeply with the concerns about judgment and accountability highlighted by tech leaders and thinkers. For example, Satya Nadella, the CEO of Microsoft, wrote in his book Hit Refresh about several critical skills he thinks will be essential for future generations to develop to remain relevant. These include:
Empathy: Nadella points out that empathy is a particularly challenging skill to emulate through coding, making it especially valuable in a world where human interactions intersect with AI.
Education: People are changing careers more frequently than ever before, and skills that were highly sought after a decade ago may now be obsolete. Continual learning is crucial to keep pace with the intense economic and employment landscape fluctuations.
Creativity: Nadella argues that while machines can enhance and augment our creativity, the intrinsic human impulse to create will remain central.
Judgment and Accountability: Even as we grow accustomed to accepting outputs from machines, such as medical diagnoses or computer-generated legal decisions, there is still a strong expectation for human accountability. Consider recent news where a lawyer in British Columbia faced repercussions for attempting to use hallucinations produced by ChatGPT in a legal application. Air Canada’s experience with a misleading AI chatbot resulted in being ordered to pay damages to one of their clients. Or consider that students today may one day decide how and when to apply CRISPR technology in ethically complex situations.
In his book When More is Not Better, Roger L. Martin stresses a critical perspective on how models are traditionally taught in education and suggests a paradigm shift toward a more engaged learning process. The goal is for students to move beyond passive acceptance of existing knowledge and actively participate in creating and redefining knowledge.
Despite humanity’s long and painful history of being shown to be wrong about what was previously held to be certain, we keep teaching models as if they are not models but rather reality—the true unshakeable reality, rather than what they are: the best interpretation of reality humanity has been able to come up with yet.
Instead, we need to teach students—at all levels—that all models are wrong, otherwise they wouldn’t be models in the first place. Rather than teaching students to uncritically adopt models, with all their implicit flaws, we need to teach students how to critically evaluate models. Even more important, we need to teach students how to build new ones. That is what human advancement is about: building better models.
To improve the quality of their models, students need to be taught to interact more closely with the real world. The closer to the real world you get, the better grounded your models of it will be. If we want students to build more-effective models of their world in order to be able to design more-useful action, we need to help them learn how to access more directly observable data on that world. Otherwise, they will default to using interpretations of somebody else’s directly observable data.
Roger L. Martin – When More is Not Better
In a similar vein of connecting theoretical education with practical application, the CareProfSys recommender system, developed under the guidance of Maria-Iuliana Dascalu, seeks to enhance students’ transition from academic environments to the workforce. CareProfSys employs a hybrid approach to recommend career paths aligning with students’ skills, educational backgrounds, and interests. Moreover, the system’s innovative use of Virtual Reality (VR) to simulate job scenarios offers a dynamic way for users to gain tangible insights into various professions. This immersive experience makes theoretical models of career paths more concrete and empowers students to make informed decisions by providing a better understanding of potential job realities. This bridging of theoretical models with practical experiences exemplifies the critical engagement that Martin advocates for in his book, ensuring that students are not merely recipients of existing knowledge but active participants in shaping their futures.
Another angle to address is the implications of generative AI technologies, which can produce vast amounts of plausible yet potentially unreliable content. In an essay published in 2005 and then included in the 2016 edition of Chronicles of a Liquid Society, Umberto Eco discusses the challenges and opportunities presented by the Internet of the early 2000s, which are eerily prescient of the latest AI concerns.
The challenge Eco identified — distinguishing good copying from mere replication — becomes even more complex when AI can create text that mimics different writing styles and seamlessly integrates or hallucinates data. For Eco, a student who can effectively select and integrate information from various sources demonstrates a valuable academic ability.
There again, the student may present research that seems, and is, correct, but has been cut and pasted directly from a website. I tend to regard this situation as less serious, since copying well is not a simple art, and a student who knows how to copy well is entitled to a good mark. Besides, before the Internet, students could copy from a book they’d found in the library, and the issue was the same, even though more physically tiring. In the end, a good teacher always notices when a text has been copied indiscriminately and will sniff out the trick. There again, if it has been copied selectively, the student deserves full credit.
Umberto Eco – Chronicles of a Liquid Society
Eco proposes an exercise in which students are tasked with finding unreliable arguments on the Internet and then critically analyzing why these arguments fail to hold up under scrutiny. Especially nowadays, learning and explaining why certain information is credible is a highly transferable skill that will pay dividends multiplied.
But I think there’s one effective way of exploiting the defects of the Internet for educational purposes. For a class exercise, homework, or university essay, give the following subject: “Find a series of unreliable arguments available on the Internet, and explain why they are unreliable.” Here is research that demands critical skill and an ability to compare different sources, and that enables students to practice the art of discrimination.
Umberto Eco – Chronicles of a Liquid Society
The unpredictability of education in the 21st century is quite extraordinary. We must create a new metaphor for the school in the 21st century because we need schools as environments that prioritize adaptability, ethical discernment, and critical evaluation. Perhaps it will not be the strongest or the smartest who will withstand, but the fittest, as Darwin said. One lives and learns, and those who learn live.