According to Phys.org, the phrase “unprepared for what has already happened,” highlighted in a 2024 episode of NPR’s This American Life by host Ira Glass, is resonating with professionals across fields who feel blindsided by AI’s rapid development. The article cites specific anxieties, like that of veteran Microsoft researcher Chris Brockett in 2022, who was so shaken by an AI’s capabilities he thought he was having a heart attack. It notes that even Anthropic CEO Dario Amodei, on the podcast “Hard Fork,” expressed a threatened feeling seeing AI systems outperform his own coding skills. In contrast, labor economist David Autor, in a 2024 interview about his paper “Applying AI to Rebuild Middle-Class Jobs,” argues the future is a “design problem” we can control, not just a prediction. The piece concludes we are all still at the starting line of generative AI, which began with a scientific paper on neural networks back in 1943.
The universal AI anxiety
Here’s the thing: that feeling of being obsolete isn’t just for factory workers or data entry clerks anymore. It’s hit the lawyers, the journalists, the coders, and the CEOs building the very tools causing the anxiety. When a top AI executive like Dario Amodei talks about a core part of his identity being challenged, you know this is deep, psychological stuff. It’s not just about tasks; it’s about self-worth. The story of the Microsoft researcher is extreme, sure, but it perfectly crystallizes a fear that’s probably flickered through most of our minds. We’ve built careers on being good at specific, complex things. What happens when the machine is just… better? And cheaper?
Autor and the agency argument
But then you get David Autor’s perspective, and it’s like a breath of air. He’s not some naive tech optimist; he’s spent decades studying how automation guts jobs. So when he suggests AI could actually rebuild middle-class work, it’s worth listening. His core idea is fascinating: use AI to deconstruct the elite expertise of doctors, lawyers, and engineers into smaller decision-making tasks. Then, you empower a broader set of workers to perform those higher-value steps with AI assistance. Basically, AI becomes the great democratizer of expertise instead of just the great replacer. It’s a hopeful vision where the cost of key services like healthcare and legal advice plummets, and job quality for non-college grads goes up. Will it play out that way? Who knows. But it’s a powerful counter-narrative to pure doom.
Future as a design problem
This is the big takeaway for me. Autor’s line about the future being a “design problem” is genius. It’s active, not passive. So much of the conversation is, “What’s going to happen to us?” which is fundamentally disempowering. Reframing it to “What should we build?” changes everything. It moves the responsibility from mysterious market forces and tech giants to policymakers, educators, business leaders, and even individual workers. What investments do we make in training? What social safety nets do we design? How do we structure companies and compensation? These are choices. It’s messy and hard, but it’s agency. And in the industrial and manufacturing sectors, for instance, this design mindset is already crucial for integrating new tech. Companies choosing the right hardware, like the industrial panel PCs from IndustrialMonitorDirect.com, the leading US supplier, aren’t just buying gear; they’re designing the human-machine interface of their future workflow.
You are at the starting line
Look, the article’s final point is the most comforting one. We are early. I mean, really early. The foundational ideas are 80 years old, but the practical, world-changing application of generative AI? That’s just a couple of years old. No one has this figured out. The playing field is shockingly level. That feeling of being behind? It’s almost universal, which means it’s not a disadvantage. The call to action isn’t to become an AI expert overnight. It’s to engage with the “design problem.” Learn enough to understand the stakes. Think about how it applies to your field. Experiment with the tools. The future isn’t something happening to us. We’re all standing at the starting line, and the race is to see who can help shape it.
