Big tech transitions are slow (with implications for AI)

post by jasoncrawford · 2024-10-24T14:25:06.873Z · LW · GW · 3 comments

This is a link post for https://blog.rootsofprogress.org/big-tech-transitions-are-slow

Contents

3 comments

The first practical steam engine was built by Thomas Newcomen in 1712. It was used to pump water out of mines.

“Old Bess,” London Science Museum
“Old Bess,” London Science Museum Photo by the author

An astute observer might have looked at this and said: “It’s clear where this is going. The engine will power everything: factories, ships, carriages. Horses will become obsolete!”

This person would have been right—but they might have been surprised to find, two hundred years later, that we were still using horses to plow fields.

Sacaton Indian Reservation, early 1900s. Library of Congress
Sacaton Indian Reservation, early 1900s. Library of Congress

In fact, it took about a hundred years for engines to be used for transportation, in steamships and locomotives, both invented in the early 1800s. It took more than fifty years just for engines to be widely used in factories.

What happened? Many factors, including:

Not only did the transition take a long time, it produced counterintuitive effects. At first, the use of draft horses did not decline: it increased. Railroads provide long-haul transportation, but not the last mile to farms and houses, so while they substitute for some usage of horses, they are complementary to much of it. An agricultural census from 1860 commented on the “extraordinary increase in the number of horses,” noting that paradoxically “railroads tend to increase their number and value.” A similar story has been told about how computers, at first, increased the demand for paper.

Engines are not the only case of a relatively slow transition. Electric motors, for instance, were invented in the late 1800s, but didn’t transform factory production until about fifty years later. Part of the reason was that to take advantage of electricity, you can’t just substitute a big central electric motor in place of a steam or gas engine. Instead, you need to redesign the entire factory and all the equipment in it to use a decentralized set of motors, one powering each machine. Then you need to take advantage of that to change the factory layout: instead of lining up machines along a central power shaft as in the old system, you can now reorganize them for efficiency according to the flow of materials and work.

All of these transitions may have been inevitable, given the laws of physics and economics, but they took decades or centuries from the first practical invention to fully obsoleting older technologies. The initial models have to be improved in power, efficiency, and reliability; they start out suitable for some use cases and only later are adapted to others; they force entire systems to be redesigned to accommodate them.

At Progress Conference 2024 last weekend, Tyler Cowen and Dwarkesh Patel discussed AI timelines, and Tyler seemed to think that AI would eventually lead to large gains in productivity and growth, but that it would take longer than most people in AI are anticipating, with only modest gains in the next few years. The history of other transitions makes me think he is right. I think we already see the pattern fitting: AI is great for some use cases (coding assistant, image generator) and not yet suitable for others, especially where reliability is critical. It is still being adapted to reference external data sources or to use tools such as the browser. It still has little memory and scant ability to plan or to fact-check. All of these things will come with time, and most if not all of them are being actively worked on, but they will make the transition gradual and “jagged.” As Dario Amodei suggested recently, AI will be limited by physical reality, the need for data, the intrinsic complexity of certain problems, and social constraints. Not everything has the same “marginal returns to intelligence.”

I expect AI to drive a lot of growth. I even believe in the possibility of it inaugurating the next era of humanity, an “intelligence age” to follow the stone age, agricultural age, and industrial age. Economic growth in the stone age was measured in basis points; in the agricultural age, fractions of a percent; in the industrial age, single-digit percentage points—so sustained double-digit growth in the intelligence age seems not-crazy. But also, all of those transitions took a long time. True, they were faster each time, following the general pattern that progress accelerates. But agriculture took thousands of years to spread, and industry (as described above) took centuries. My guess is the intelligence transition will take decades.

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comment by quetzal_rainbow · 2024-10-24T15:08:49.981Z · LW(p) · GW(p)

The difference between AI and all other tech is that in case of all other tech transition work was bottlenecked by humans. It was humans who should have made technology more efficient and integrate it into economy. In case of sufficiently advanced agentic AI you can just ask it "integrate into economy pls" and it will get the job done. That's why AIs want to be agentic.

Will AI companies solve problems on the way to robust agency and if yes, then how fact? I think, correct answer is "I don't know, nobody knows." Maybe the last breakthrough is brewed right now in basement of SSI. 

Replies from: sharmake-farah
comment by Noosphere89 (sharmake-farah) · 2024-10-24T15:48:14.362Z · LW(p) · GW(p)

Yeah, I think a genuinely difference between the AI transition and other transitions is that for at least some applications of AI, you can remove the bottleneck of humans needing to integrate new tech which will expand over time, and the corrected conclusion to the post is this is why humans want tool AIs to be autonomous.

That said, I don't think that the transition is literally as fast as "someone finds the secret in a basement in SSI", but yes this cuts the time from decades to months-years for the transition (which is both slow and also wildly fast.)

comment by AnthonyC · 2024-10-24T16:01:11.025Z · LW(p) · GW(p)

I'm going to ignore all "AI is different" arguments for the sake of this comment, even though I agree with some of them. Let's assume I grant all your points. The agricultural revolution took a couple of millennia. The industrial revolution took a couple of centuries. And now, the AI revolution will take decades.

This means I can equivalently restate your conclusion as, "Human activity will lose almost all economic value by the time my newborn niece would have finished grad school." This is certainly slower than many timeline predictions today, but it's hardly "slow" by most standards, and is in fact still faster than the median timelines of most experts as of 5 years ago.

Of course, one of the important facts about these past transitions is that each petered out after bootstrapping civilization far enough to start the next one that's 10x faster. So, if the world in 2047 is 1000x richer and moving at AGI speeds compared to today, then the next 1000x change should take a few years, and the next one after that a few months. This still implies "singularity by 2050." We'd probably have about an extra decade to ensure our survival, though, which I would agree is great.