Brian Potter at Construction Physics is one of our favourite science writers around. And this piece shows why. Potter uses Claude AI to research the question in the title of the piece, which means how much longer has it taken for an invention to be actually made from the time when all the preconditions for the said invention were in place?
Why is this important? “Knowing how long this gap between when an invention becomes possible, and when it actually appears, is useful, because it tells us something about the nature of technology and technological progress. What factors govern whether some new technology appears? How much does mere technical possibility matter, and how much do things like cross-pollination of knowledge, economic feasibility, and political factors contribute? Knowing more about how long it takes for an invention to appear once it becomes technically possible can help us answer these sorts of questions.”
Besides the interesting framing of the research, the piece is also praiseworthy for the way Potter constructs the research project: “This required pinning down what exactly I mean by “could have been invented.” For one, it’s often possible to build a working example of some technology long before it’s capable of solving a real problem. Working incandescent light bulbs were built decades before Edison, but they weren’t useful for providing indoor illumination until Edison developed one that lasted for many hours without blackening or burning out. For another, it’s often possible to build something before the problem that it solves has been articulated. Surgical masks — a cloth covering over the face — could have been invented thousands of years ago, but inventing them only makes sense once the germ theory of disease has been articulated.
Nonetheless, I decided to use “could a working example of this technology be built” as my meaning, ignoring whether that technology would be practical or economically useful.”
Once such clear definitions were put into Claude’s prompt (Potter gives a link to his prompt as well), he gives Claude a list of 190 major inventions from the past to be analysed on the following lines:
“For the output, I had Claude list a range encompassing two dates. The first is the earliest plausible date for when the inventor’s team could have succeeded with some charitable assumptions and a bit of luck. The second is the straightforward date, when multiple independent teams would be likely to converge on a working model of the invention. Along with the date range, I had Claude list the necessary prerequisite technologies and scientific knowledge, and give a short explanation of its reasoning.”
He then shares examples of the output given by Claude to verify, such as this one for the aeroplane: “ The Wright Flyer is a clean case where the binding constraint is the lightweight internal combustion engine. Cayley had laid out the basic principles of fixed-wing flight by 1810, gliders were practical from mid-19th century, and Wenham’s wind tunnel (1871) plus Lilienthal’s glider work (1890s) gave aerodynamic data. The three-axis control concept is team-discoverable through glider iteration — it’s an engineering insight, not a scientific discovery. The hard prerequisite is a roughly 10-hp engine weighing under ~200 lb, which only becomes feasible after the Otto cycle (1876) and Daimler/Benz refinements of the mid-1880s; steam plants of earlier eras were too heavy. With a Daimler-class engine available by ~1885 and Lilienthal-style glider knowledge accumulating, a motivated team could plausibly assemble a Flyer-equivalent in the late 1880s (earliest plausible). By the late 1890s prerequisites were widespread enough that multiple teams (Langley, Maxim, Ader, the Wrights) were actively converging — making 1895–1903 the straightforward window. The historical 1903 date reflects how genuinely difficult the integrated control problem was, not missing prerequisites.”
Upon verification, he concludes that Claude’s got it by and large right: “I think Claude’s answers are probably reasonably defensible most of the time. And what’s more, they show how genuinely difficult it is to answer these sorts of “how early could a technology have appeared?” questions. Even limiting ourselves to questions of technical possibility and not actual commercial or societal usefulness, good answers to these questions require knowing both a lot of history of some particular technology AND having deep technical knowledge of various technologies as they existed at various points in time. Answering “how early could an airplane have been built?” requires knowing not just who the various flight pioneers were and when they did their work, but the state of steam and internal combustion engine technology at various points in the 19th century and how far they could have plausibly been pushed. There are just vanishingly few people with this sort of deep knowledge about even a few technologies, much less 190 of them spread across two centuries. So while I don’t expect the AI’s answers to be perfect, I think it’s probably collectively a much better analysis than you’d get from almost any single human.”
That’s telling about the power of AI. However, what do the results say about how quickly have we humans invented stuff from the time the preconditions were in place?
“…for most inventions, the gap between when it could have been invented and when it was actually invented is not particularly large. Of the 166 inventions Claude estimated a date for, 107 of them (64%) had an “earliest plausible” date 50 years or less from the actual date, and 150 of them (90%) had an “earliest straightforward” date 50 years or less from the actual date. For more than half the inventions, the average earliest straightforward date of invention was 10 years or less from the actual date.
Conversely, there were a relatively small number of inventions where the gap between “could have been invented” and “was invented” was very large. 30 inventions (18%) had an average gap of more than 100 years between “earliest plausible” and actually invented, and eight inventions had a gap of more than 1000 years.
… Many of the longest-delayed inventions — the hypodermic needle, general anaesthetic, stethoscope — are medical inventions. (You could argue the surgical mask could be in this category as well). For the hypodermic needle, this probably needed to wait until the existence of some substance that needed to be injected (such as morphine, first synthesized in 1804), but for other medical inventions this possibly also reflects folks’ reluctance to do inventive-tinkering in a medical context. For general anaesthetic, for instance, the trial and error of getting the dose right was incredibly dangerous, and the inventor Hanaoka Seishu “crippled his mother and blinded his wife perfecting the dose.””
More encouragingly, we are getting better with time: “…the gap between when an invention becomes possible and when it appears has narrowed over time…For the 60 post-1900 inventions, every one has a “straightforward” invention date of 50 years or less than the actual date, and 75% of them have a straightforward date of 10 years or less before the actual date. Of the 30 inventions with a gap of more than 100 years between when they could have been invented and when they actually appeared, 29 of them were invented before 1900. So the process for creating new inventions seems to be getting more and more efficient — opportunities are getting noticed and exploited sooner and sooner, up through 1970 at least”
With AI, we can expect inventions to speed up that much more.
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