Reclaiming human intelligence in the Age of AI

Long before artificial intelligence (AI) could deliver the mysteries of the universe on a platter or double as a digital confidante, I built my understanding of the world the hard way. 

As a teenager, I’d spend hours crouched over a boombox, rewinding songs to transcribe the lyrics on looseleaf paper, then staring at the ceiling trying to decipher their meaning. Afterward, I’d lie on my bedroom floor writing diary entries, scaffolding my big emotions onto those song structures. Nothing prepares you to solve complex problems quite like teenage melodrama.

Without realizing it, I was building resilience through a masterclass in productive struggle,  learning to decompose, reconstruct, find patterns and solve problems on my own. It wasn’t about what I was learning, but how: a deeply iterative, reflective process of toiling that laid the groundwork for how I think and learn today.

I’ve been reflecting on this experience since the launch of Canada’s National AI Strategy: AI for All and its action to create a national AI literacy initiative. Under Pillar 2: Empowered Canadians, the document defines AI Literacy as “the understanding that lets Canadians recognize AI, judge its outputs, and decide for themselves where it belongs in their lives.” Sounds reasonable enough, but cultivating AI literacy is more complex than “recognizing AI and judging its outputs”.  

AI literacy demands that we intentionally build foundational human skills, anchoring the technology in what makes us uniquely human. AI can provide remarkable possibilities but also poses more serious threats. The promise and the peril are often two sides of the same coin. AI gives youth a powerful lens to see the world in new ways or it can simply do the thinking for them. 

That is the fear. That AI will take away human creativity, shortcut curiosity, breed cognitive laziness and lead to social isolation. It turns out that when you make everything feel effortless and seamless, you lose the benefits of doing things the hard way. It’s not just the what that is of concern. It’s the how that is potentially even more damaging. 

And this is exactly why AI literacy can’t just be about teaching kids how to engineer prompts on a new tool to generate the desired response. It has to include that messy human process to generate deep learning.  

Core principles for AI literacy

Any direction, policy or funding directed to AI literacy in Canada must be built on a few core principles to ensure Canadians can benefit from AI without losing the important skills and abilities that will allow us to shape this technology, rather than it shaping us. 

First, the foundation must be human agency. Critical thinking must be the primary goal of any AI literacy program, with humans in the driver’s seat. We must help youth remember that the use of any digital technology is part of a social contract which we define as digital citizenship. Like national citizenship, digital citizenship offers rights, but also demands responsibility and accountability. 

Secondly, we must help youth remain creative and curious. We want them to ask why and what and how, but we don’t want them arriving at answers artificially. We must nurture productive struggle so they learn the joy in searching for answers, in digging for truth and in toiling through song lyrics or poetry stanzas or 500-page novels or even Python code for passion. 

Human creativity remains the best defence against cognitive offloading. AI looks backward, but we want kids to look forward and imagine better, brighter, more equitable futures. To do this, AI literacy programs must include unplugged, land-based, outdoor, hands-on components. 

Next, collaboration must happen with real humans in real life. We want youth to learn how to negotiate, stand up for their ideas, fight for what they think is right and good, learn to debate differing opinions respectfully and effectively, but also learn to compromise to get to a productive collective outcome. We want them to find comfort in discomfort because that is where learning happens. This can and must be built into AI literacy programs. The use of screens and tech tools must be fully integrated within a context of human collaboration.   

Finally, we must intentionally teach logic. Every industry has its own term for this. Computer scientists call it computational thinking. Scientists and mathematicians might call it reasoning. The lawyers, case analysis. The investigators, forensics. The doctors, differential diagnosis. The artists and engineers, design thinking. The communications and business people, crisis management. 

Solving problems, deciphering mysteries, fixing what is broken, improving what isn’t working: this is what makes us human. But doing this requires human intelligence, which is learned through practice, through toil, through struggle. If we don’t get this right, we risk losing our human agency. 

The path forward

If we put human skills and judgment at the centre of AI education, we will build a stronger foundation for the future. By investing as much in responsible use as in technical capability, we can ensure the next generation controls technology rather than being controlled by it.

But the window of opportunity is closing for the kids living through this moment of rapid AI adoption. This must be addressed now in every classroom and every AI literacy program, because the future of education isn’t about teaching machines to think; it’s about ensuring our children don’t forget how to. 

Whether through deciphering a song, analyzing complicated texts or books, or staring up at the stars, AI literacy must begin with what humans do best: struggling through complexity to make sense of our world.

Note: Artificial intelligence was used to assist with editing of this article. All ideas, analysis and opinions are the author’s own.