The Knowledge Economy Is Over. Welcome to the Allocation Economy

This week we're bringing you the best of our AI writing. As 2024 dawned, Dan Shipper asked: What comes after the knowledge economy? In a world enabled by AI, he argued that the most important skill will be allocation—managing the resources to get your job done. Read on to learn what that means and how to succeed in this new world order.—Kate Lee 

Time isn’t as linear as you think. It has ripples and folds like smooth silk. It doubles back on itself, and if you know where to look, you can catch the future shimmering in the present.

(This is what people don’t understand about visionaries: They don’t need to predict the future. They learn to snatch it out of the folds of time and wear it around their bodies like a flowing cloak.)

I think I caught a tiny piece of the future recently, and I want to tell you about it.

Last week I wrote about how ChatGPT changed my conception of intelligence and the way I see the world. I’ve started to see ChatGPT as a summarizer of human knowledge, and once I made that connection, I started to see summarizing everywhere: in the code I write (summaries of what’s on StackOverflow), and the emails I send (summaries of meetings I had), and the articles I write (summaries of books I read).

Summarizing used to be a skill I needed to have, and a valuable one at that. But before it had been mostly invisible, bundled into an amorphous set of tasks that I’d called “intelligence”—things that only I and other humans could do. But now that I can use ChatGPT for summarizing, I’ve carved that task out of my skill set and handed it over to AI. Now, my intelligence has learned to be the thing that directs or edits summarizing, rather than doing the summarizing myself. 

As Every’s Evan Armstrong argued several months ago, “AI is an abstraction layer over lower-level thinking.” That lower-level thinking is, largely, summarizing.

If I’m using ChatGPT in this way today, there’s a good chance this behavior—handing off summarizing to AI—is going to become widespread in the future. That could have a significant impact on the economy.

This is what I mean by catching the future in the present and the non-linearity of time. If we extrapolate my experience with ChatGPT, we can glean what the next few years of our work lives might look like.

The end of the knowledge economy

We live in a knowledge economy. What you know—and your ability to bring it to bear in any given circumstance—is what creates economic value for you. This was primarily driven by the advent of personal computers and the internet, starting in the 1970s and accelerating through today.

But what happens when that very skill—knowing and utilizing the right knowledge at the right time—becomes something that computers can do faster and sometimes just as well as we can? 

We’ll go from makers to managers, from doing the work to learning how to allocate resources—choosing which work to be done, deciding whether work is good enough, and editing it when it’s not. 

It means a transition from a knowledge economy to an allocation economy. You won’t be judged on how much you know, but instead on how well you can allocate and manage the resources to get work done. 

There’s already a class of people who are engaged in this kind of work every day: managers. But there are only about 1 million managers in the U.S., or about 12% of the workforce. They need to know things like how to evaluate talent, manage without micromanaging, and estimate how long a project will take. Individual contributors—the people in the rest of the economy, who do the actual work—don't need that skill today.