✨⚡ The Up Wing combo of AI and energy
Imagine a new economic architecture where growth feeds on itself
My fellow pro-growth/progress/abundance Up Wingers,
Paul Romer, a Nobel laureate, identified a profound truth that’s a core element of Up Wing economics: Although “Eureka!” moments of scientific discovery are obviously important for generating transformative technologies, most game-changing advances emerge by rearranging existing knowledge. His theory of combinatorial innovation suggests that much progress comes from cleverly recombining what we already know into an effectively infinite number of recipes.
Romer: “Every generation has perceived the limits to growth that finite resources and undesirable side effects would pose if no new recipes or ideas were discovered. And every generation has underestimated the potential for finding new recipes and ideas. We consistently fail to grasp how many ideas remain to be discovered.”
Consider the ubiquitous smartphone. Apple invented neither the microprocessor nor the touchscreen, GPS nor wireless communication. Yet by wedding these technologies, it created the “one device” (as Steve Jobs called the first iPhone) that continues to reshape human society. Just as 26 letters generate millions of words, established technologies can be alchemically shuffled into configurations that seem magical.
Romer's insight about combinatorial innovation has never been more relevant than right now, as two new fascinating papers suggest when viewed in … well, combination.
Man and machine working together
In “Artificial Intelligence and Technological Unemployment,” economists Ping Wang (Washington University in St Louis) and Tsz-Nga Wong (Federal Reserve Bank of Richmond) examine how AI affects jobs and the economy by treating it as technology that gets smarter by working alongside humans. The more people use AI tools, the better AI becomes at those tasks. And as AI improves through this learning process, it eventually becomes good enough to replace many of the workers who taught it. The researchers find this cycle of self-improvement could eliminate 23 percent of existing jobs long-term but boost productivity by 366 percent.
The good news here for workers: While AI eventually surpasses human capabilities in individual tasks, it doesn't lead to mass unemployment because human productivity becomes so dramatically enhanced through AI collaboration. The tipping point occurs if human-AI partnerships become so powerful — assuming AI continues to improve — that companies prioritize finding humans to work with their AI rather than replacing them entirely. Like the computer revolution that ultimately generated more jobs than it eliminated, continuing AI advancement could deliver tremendous job creation through this collaborative dynamic rather than widespread displacement. (As I see it, what we are talking about here is powerful AI that's short of full human-level AI or beyond.)
As the authors simply put it, “AI creates and destroys jobs.” Too often, we only think about the latter bit.
Energetic growth
Then there’s “Climbing the Energy Ladder: How Energy Resources Hinder, Facilitate, and Fuel Economic Growth” by economist Derek Lemoine (University of Arizona,) in which he explains that the type of energy we use determines whether our economy can grow. Wood and muscle power kept humanity poor for millennia because they were limited by available land. Coal helped enable the Industrial Revolution by breaking this constraint — you could dig up as much as needed. Oil continued this but introduced a new risk: If wells don't produce enough energy relative to drilling costs, growth stalls.
Solar panels offer something unprecedented, according to Lemoine: potentially unlimited growth through automated production where solar-powered robots make more panels and robots indefinitely. As he see see it, our future depends on keeping solar energy's return-on-investment high enough to avoid an "energy cliff" while achieving full automation. If EROI drops too low, society could spend so much energy producing energy that there's little left for everything else, causing economic stagnation despite having renewable power.
Now it seems to me that the logic here would also apply to nuclear, advanced geothermal, and fusion. Any of these could enable "energy-fueled growth" if they achieve high enough ROI and can be cheaply produced by automated systems. I assume the economist likely focused on solar because it's currently scaling fastest with the steepest cost declines, but I would think that the theoretical framework here applies to any manufactured energy technology meeting these criteria.
Better together
Think about the feedback loops these technologies create together. When AI systems learn from human workers, they don't just automate existing processes, they fundamentally alter what's possible. Pair this with Lemoine's vision of self-replicating energy infrastructure, and you get a pretty amazing scenario where human-AI teams optimize the design and manufacture of solar panels and batteries — or other new energy technologies — which then power the AI systems that design the next generation of panels.
This isn't simply a matter of greater efficiency gain. It's a new economic architecture where growth feeds on itself, where scarcity factor moves from physical resources to useful applications of infinite, intelligence-infused recipes. When our tools can improve themselves and power their own improvement, we're building an economy that discovers and makes its own building blocks.
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