Perspective: Technology for Today’s Innovators, and Tomorrow’s
We are living in an exceptional new technological era. Yet looks can be deceiving. In fact, what most strongly defines our current age is not all the new technology we see arising, but all the technology we now take for granted. In a way no previous generation has experienced, the presence of digital technology is assumed in practically all aspects of our lives. Unfortunately, however, there is one singular, perilous exception—the way we structure and arrange teaching and learning.
We have adapted to technology’s almost invisible ubiquity with breathtaking rapidity. Only a bit more than a decade ago, GPS was still a novelty. Most people didn’t own cell phones. CDs and DVDs dominated their markets, and pagers and fax machines were commonplace. Today, technology has changed everything. Well, almost everything.
Sure, technology permeates our schools, but that fact is deceptive. It’s the things technology has not changed about education that deserve our real attention. Despite the sudden wave of pandemic-related Chromebook purchases and the whiplash turn toward Zoom instruction, the curriculum itself has remained practically impervious to change.
Today’s K-12 students exist in a world utterly defined by computation and technology. Data is everywhere. AI is on our doorstep. CRISPR, quantum computing, drones, and biosensors are the stuff of the present. Yet most students’ textbooks and class syllabi could have been plucked from their grandparents’ classrooms. To riff on one of my favorite of Conrad Wolfram’s sayings, it’s time to teach school as if computers existed.
We need to consider what it means to live and work in today’s technological society—and the one just around the corner, too. Students need the competencies and habits of mind our world demands. Educators must redefine the way we approach schooling, ensuring that perspectives reflecting our technology reality reinforce everything we do.
We’re already accomplishing some of this—promoting computer science and disseminating high school data science courses, for instance. But we must dive deeper and not delude ourselves into thinking that pushing a subject slightly downward from the undergraduate level into high school represents success. Similarly, elementary or middle school goals cannot be determined by merely watering down lists of current workplace skills. We must rethink K-12 learning wholesale with our eyes on new horizons.
A different approach is possible. Transformation is sweeping the workplace, and emerging professions offer an inspirational lens on the future. MIT Technology Review‘s recent selection of “35 Innovators Under 35” is an object lesson. This incredible list’s through-the-keyhole view into the future can also stand as a useful template for our educational destiny.
Partnering with artificial intelligence. Today’s innovators are finding manifold ways that AI can solve tomorrow’s problems, through a diversity of applications that is truly striking. From solutions to climate change to machine learning-based solutions for pain management, novel AI designs bypass existing theory and practice and aim straight at the problems they can solve. Mining large, available pools of data, AI innovators pinpoint the potential for inventive, unimagined discoveries in long-neglected corners of science and industry. Preparing learners for a world in which AI is central means seeing computers and computation as almost equal partners with humans in navigating and solving problems. From elementary school onward, students should learn not only how computing works and how to think computationally, but also gain experience identifying how computing and AI can serve as fundamental tools for approaching the world. Current research in AI education and computational thinking can help us pave the way to age-appropriate onramps for learning to apply AI to all manner of problems.
Working with DNA as a tool. Another area that begs for educational innovation is the burgeoning world of bioengineering. The advent of CRISPR technology and the recent proof of mRNA’s vast utility have fundamentally shifted our orientation toward biology—from seeing it as a set of systems to be observed to recognizing that it holds the active tools of our future. We need to help students see biology not as a series of facts but rather as a manipulable system. As students learn about biological processes and classification, they should be guided to see the mechanisms of biology as tools that can be used to unlock secrets, and to view medical problems as opportunities for innovative applications of miniature machines and biological building blocks. This requires significant rethinking. We must consider how to view biology education wholly differently, embracing practice-focused topics that lean into the future as much or more than they reiterate the historical past.
Seeing with sensors, and doing with drones. We must also prepare learners for a future of ubiquitous sensing and innovative action. Operating within a world where robots can be as tiny as blood vessels and sensors can be constructed from biological components demands that students see the world as a series of opportunities for both exploration and manipulation. Our curriculum must take for granted that the Internet of Things and the deluge of drones, robots, satellites, and all manner of connected machines now extend our hands and eyes to practically all scales and sites. We can monitor the entire globe from space, reach into the rubble of a disaster area, or bring the equivalent of miniature wrenches and tweezers into microscopic locations. Important new perspectives come along with this potential. Students should come to see that these tools unlock an incredible power. As soon as they understand how anything in the world functions—whether a biochemical reaction or a warehouse-scale workflow—they can turn around and apply their toolbox to directly manipulate that same process. This requires us to fundamentally rethink what “hands-on” learning means, and perhaps even to question the nature of engineering education itself.
Solving problems with data. In a future where data are everywhere, learners must be ready to use data as a medium, seeing everything around them—from music to words to photographs to brainwaves—as data. Learning how that data can be used to answer questions, shed light on the operation and interconnectedness of their world, and identify new problems to be solved is crucial. We must ensure that learners have multiple opportunities to see datasets as founts of original questions, so they are empowered and proficient at using data as a means to action. We must help them view the world as a source of data that can be used to solve problems, expose inequities, and confront social issues head on.
Putting it all together. One of the clearest lessons from the innovators of today (or any age) lies in their ability to combine disparate ideas in a way that renders them greater than the sum of their parts. Whether uniting quantum computing and agriculture or marrying innovative polymers and circuitry to solve biological problems, the innovators in MIT’s lineup aren’t merely working in innovative fields—they’re working at the interfaces between them. Learners must be prepared to work within a future filled with technology. We must give them opportunities to merge, mix, and mash up their knowledge and ideas.
Bringing all of these changes about—and doing so in a way that ensures all learners gain rich experiences in an equitable fashion, no matter their grade level, background, or ZIP code—is the true challenge of the coming decades. And though it’s indeed the task of a lifetime, taking the long view reveals that it is absolutely essential to our future, and the future of our children.
Learners must be prepared to work within a future filled with technology. We must give them opportunities to merge, mix, and mash up their knowledge and ideas.
Chad Dorsey (cdorsey@concord.org) is President of the Concord Consortium.