radical Insights.

Weekly Research and Commentary on the Future of Business and Technology.

The Rise of the Machine (Learning) Economy.

Apr 2, 2024

Buckle up, friends. We’re about to take a wild ride into the future of work, courtesy of our old pal Jevons and his pesky paradox dating back all the way to 1865.

For the uninitiated, Jevons Paradox says that as a technology gets more efficient, we end up using more of it, not less. Classic example: LED light bulbs. Super energy-efficient compared to incandescents, but now we’re covering every square inch of our houses in them. More efficiency, more consumption.

Everything Is Software Now

Marc Andreessen (the founder of Netscape and proto-VC) once said that software is eating the world, but for most of history, custom software has been a pricey proposition. Typically, only governments and deep-pocketed companies could afford to build the good stuff from scratch.

But what if AI could make bespoke software as cheap and easy as whipping up a spreadsheet? Suddenly, every mom-and-pop shop, local charity, and everything in between can have a custom app perfectly tuned to their needs.

And that means the demand for software will explode like a supernova. Sure, a lot of the basic grunt coding will get automated away. But someone still needs to dream up all these new applications, architect the systems, and manage the AI doing the dirty work.

The New Programming Elite

So contrary to what you might hear from the Chicken Littles of the tech world, AI won’t be the end of programming jobs. But it will be the end of programming as we know it. The new kings and queens of code will be the ones who can work hand-in-virtual-hand with AI to imagine, design, and deploy software at lightning speed. They’ll use machine learning like a power tool to build smarter, more adaptive applications that evolve with the needs of the user. They will spend (much) less time coding and much more time designing (and debugging).

And this will be true not only for programmers and the world of software but for many jobs which predicate themselves on knowledge—the proverbial “white-collar job.” Think accountants, analysts, marketeers, finance, HR—the list goes on and on.

Not Everyone Wins the AI Lottery

Now, I’m no starry-eyed optimist. (Okay, maybe a little.) I know AI will absolutely demolish some (programming) jobs. If your work can be fully automated and there’s no net new demand, it’s time to pivot. Fast. While there were about the same number of bank tellers in the US in the late 2010s as there were in the 1970s despite a flood of ATMs, the same isn’t true for travel agents.

But for most of the software world, I believe we’re looking at a classic case of Jevons Paradox in action: skyrocketing efficiency, plummeting costs, and a tsunami of new demand. The pie gets bigger, even if the slices are divvied up differently.

So what’s the average white-collar worker to do? As much as you can, surf the AI wave; don’t fight it. Learn to work with machine learning, not against it. Use AI to automate the boring bits so you can focus on juicier, more creative work. And take a close, hard look at the elasticity of demand in your industry—you don’t want to be stuck in an industry with inelastic demand, one where efficiency gains do not lead to increased demand but rather plummeting prices.