I use AI daily—for writing, editing, fixing my website, untangling jargon, creating art, and exploring endless possibilities. While I’ve had the opportunity to pursue an MA, much of my life has been spent working with my hands, and not the keyboard-stroking kind. When my knees protested against laying tiles at the young age of 30, I encountered what many face today with AI: the necessity to retrain and pivot or be simply left behind.
The irony isn’t lost on me that I chose graphic design in 1995—a field in its death throes. I should have opted for web design, but hindsight is always crystal clear. And the truth is: despite having a good head for concepts and occasional wit, I never quite became the code wizard I would have needed and even liked to be. Yet being an Aquarius (if you believe in such things), I’m drawn to future technologies. This technological optimism is most likely responsible for the fact that I have navigated the (supposedly) bloodless tech revolutions of the past three decades with more curiosity than fear.
The tech industry’s narrative about AI often reads like a Silicon Valley fairy tale: disruption leads to progress, efficiency equals success, and anyone displaced should simply “learn to code.” As someone who has retrained multiple times, I recognize this oversimplification for what it is—a convenient myth that ignores the human cost of technological change.
This reality becomes particularly clear during my conversations with Paul at our local pub. He is a 60-year-old scaffolder by trade and, though he’d be mortified if I revealed it publicly, a budding ballroom dancer by night. His story perfectly illustrates the complexity of skill adaptation that tech evangelists often miss.
“No way I’m touching any AI,” he declares after I buy him a pint.
“You’re already using AI every day,” I point out. “Your social media, Google searches, even Siri correcting your terrible spelling—it’s all AI. Same tech, different labels.”
Paul doesn’t realize how his dance training—the balance, coordination, and new movement patterns—has already enhanced his scaffolding work. He’s unconsciously using skills from one domain to excel in another, demonstrating exactly how human adaptation actually works: subtle, organic, and building on existing strengths. There’s no reason the same couldn’t happen with AI.
The language divide in technology mirrors an uncomfortable class divide. When tech bros throw around terms like “machine learning” and “neural networks,” they’re often just describing glorified spell-checkers. The real issue isn’t the technology itself but who controls it and who benefits from its deployment.
While venture capitalists celebrate another billion-dollar valuation, warehouse workers face increasingly brutal algorithmic management, delivery drivers race against AI-optimized schedules, and content moderators bear psychological scars from their work. The tech industry’s obsession with disruption often translates to worker exploitation wrapped in shiny marketing jargon.
“They say AI is stealing our jobs,” Paul grumbles into his beer.
“Mate, no AI is scampering up that scaffolding anytime soon,” I respond. “But I believe the question we should talk about isn’t whether AI will take our jobs—it’s who gets to decide how it’s used and who benefits from it.”
The democratization of AI shouldn’t mean forcing everyone to become programmers. Instead, AI should adapt to our needs, becoming as accessible as any other tool in a craftsperson’s kit. The path forward isn’t about turning warehouse workers into cybersecurity experts—it’s about ensuring technology serves human needs rather than merely maximizing shareholder value.
Paul heads off to his dance class, honing new skills which he will unconsciously carry back to tomorrow’s scaffolding work. His adaptation isn’t the result of a coding bootcamp offered at the local job centre or, God forbid, a corporate retraining program. This is how real people incorporate new skills and technologies: on their own terms, in ways that make sense for their lives and work.
I remain enthusiastic about AI’s potential while clear-eyed about its challenges. The technology itself isn’t the villain—but the venture capitalists and tech executives treating workers as obstacles to AI optimization certainly make it seem so. The future of AI depends not on more elegant algorithms but on redirecting its development toward human benefit rather than merely human replacement. Surely the people who do coding for a living can work with that angle? Isn’t that their job, no retraining required?
As I settle our tab, I reflect that perhaps this is why I’m both an AI advocate and critic. Like any powerful tool, AI’s impact depends entirely on who wields it and for what purpose. The revolution we need isn’t technological—it’s social. And that’s a conversation worth having, whether in corporate boardrooms, computer labs or over pints at the local pub.