The revolutions of our time
Every few years someone announces that everything has changed. Sometimes they are right. In 1543 a book moved the Earth out of the centre of the universe. In 2012 a paper showed how to cut DNA at a chosen spot. In late 2022 a chatbot became a household word. This post asks what makes a revolution, tours the big ones, and ends with a checklist for the next announcement. I am writing in spring 2026, so the last part is a snapshot, not a verdict.
------------+-----------+------------+-----------+------------+---------
year 1600 1700 1800 1900 2000
o 1543 Copernicus: the Earth moves
o 1687 Newton: Principia
1859 Darwin: natural selection o
1905 Einstein: relativity (1905, 1915) o
1925 Quantum mechanics (1900-27) o
1953 DNA double helix o
1971 Microprocessor (transistor 1947) o
2012 CRISPR, deep learning o
2022 ChatGPT o
------------+-----------+------------+-----------+------------+---------
(a handpicked list. Gaps look shorter near the present partly because
recent history is better documented and not yet sorted out)Kuhn's picture
The physicist and historian Thomas Kuhn gave the best-known account in The Structure of Scientific Revolutions (1962). Most of the time, he said, scientists do normal science: solving puzzles inside a shared paradigm, meaning accepted theories, methods and standard examples. It is like writing code against a stable ABI. Sometimes a result does not fit. Most such anomalies are set aside as errors or puzzles to solve later. If enough pile up, confidence erodes into a crisis, a rival paradigm appears, and over time it wins and becomes the new normal.
+----------------------+ +----------------------+
| NORMAL SCIENCE | most are set aside | ANOMALIES |
| solving puzzles in |----------------------->| results the paradigm |
| a shared paradigm | | cannot explain |
+----------------------+ +----------+-----------+
^ too many pile up |
| textbooks are rewritten |
| v
+----------+-----------+ +----------------------+
| NEW PARADIGM | | CRISIS |
| a new way of seeing | | confidence erodes, |
| and new puzzles | | rivals appear |
+----------------------+ +----------+-----------+
^ |
| the winner becomes |
| the new normal a rival paradigm |
+----------+-----------+ gains followers |
| REVOLUTION | |
| rival paradigms |<----------------------------------+
| compete |
+----------------------+Kuhn's most debated idea is incommensurability: rival paradigms can disagree about what counts as a problem or a good answer, so no neutral referee settles the matter by logic alone. Critics were many. Karl Popper thought good scientists test theories critically all the time, not only in crises. Imre Lakatos offered "research programmes" instead. Some read Kuhn as making science irrational, which he denied, listing values such as accuracy, consistency, scope, simplicity and fruitfulness. Historians add that real transitions are slower and messier than the cycle suggests. Treat it as a lens, not a law.
By Kuhn's standard, a revolution is more than something new. It changes which questions are asked, which answers count, and what the textbooks teach. "Paradigm shift" is now applied to every product launch, but most of those fail the test.
A tour of seven revolutions
- Copernican (1543). Nicolaus Copernicus put the Sun at the centre. He was not the first to suggest it (Aristarchus of Samos did, in the 3rd century BCE), and his model still used circles and was no more accurate than Ptolemy's. It won over decades, helped by Kepler's ellipses (1609) and Galileo's telescope (1610).
- Newtonian (1687). Newton's Principia gave one set of laws for falling apples and orbiting moons. Its predictions were bold: the return of Halley's comet in 1758, and the planet Neptune, found in 1846 from its pull on Uranus. The anomaly that eventually undid it was tiny: Mercury's orbit drifts by 43 arcseconds per century more than Newton predicts, which Einstein's general relativity explained in 1915.
- Darwinian (1859). Natural selection, announced with Wallace in 1858, explained the diversity of life without a design plan. The mechanics of inheritance only caught up in the 20th century. The details are in Evolution, illustrated.
- Relativity and quantum (1900-1927). Planck (1900), Einstein (1905, 1915), Heisenberg (1925) and Schrödinger (1926) rebuilt physics. GPS satellites need relativistic clock corrections of about 38 millionths of a second per day, and quantum theory underlies transistors and lasers. The two theories still do not fit together into one, and puzzles such as dark matter are anomalies whose outcome is not yet clear.
- Genetic (1953-2023). Watson and Crick published the double helix in 1953, building on X-ray images made by Rosalind Franklin and Raymond Gosling. The Human Genome Project declared its work done in 2003, and a gap-free genome followed in 2022. CRISPR as an editing tool (Doudna and Charpentier, 2012; Nobel Prize 2020) led to the first approved therapy, for sickle cell disease, in 2023.
- Digital (1936-2007). Turing's computability paper (1936), the transistor (1947), Shannon's information theory (1948), the integrated circuit (1958), the microprocessor (1971), the web (1989-91) and the smartphone (2007). It also changed science itself: simulation and data analysis became a third way to do research, beside theory and experiment.
- AI (2012-now). Neural networks date from the 1950s. What changed was data, computing power and architecture: an image-recognition breakthrough in 2012, the transformer in 2017, ChatGPT in November 2022. The 2024 Nobel Prizes honoured work behind neural networks (Physics: Hopfield and Hinton) and protein prediction and design (Chemistry: Hassabis, Jumper and Baker).
Not all revolutions are the same kind
Kuhn's cycle describes changes in explanation. The digital and AI revolutions are mostly changes in capability, and their effects land on society. Telling the layers apart avoids a lot of confusion.
+------------------+ +------------------+ +------------------+
| EXPLAINS | | ENABLES | | REORGANISES |
| a new theory |----->| a new tool |----->| work, money, war |
+------------------+ +------------------+ +------------------+
quantum theory ---> transistor ---> computers, phones
DNA structure ---> sequencing, CRISPR ---> medicine, farming
Maxwell's equations ---> radio, radar ---> telecom, navigation
Kuhn's cycle describes the first column. The lag between columns is
often decades, and it can run backwards: the telescope and the steam
engine came before the theories that explained them.Real change versus hype
Roy Amara's rule of thumb says we overestimate a technology's effect in the short run and underestimate it in the long run. Analysts popularised a schematic "hype cycle" in the 1990s. Both fit the dot-com episode: the Nasdaq index fell by roughly three-quarters between 2000 and 2002, yet the web went on to change nearly everything. Economists also noticed that computers did not show up in productivity statistics for years (Robert Solow's remark of 1987). The historian Paul David pointed out that electric motors took decades to pay off, until factories were redesigned around them.
effect | (1) (4)
on the | *** ooooo
world | * * oooooo
| * * ooo
| * ooo
| * oo
| * * oo
| * oo
| * * oo **
| * ** (2) oo **********
| ** ** ooo ***********
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| oooooooo (3)
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+------------------------------------------------------------
time ->
* what people expect o what actually changes
(1) a striking demo; everyone extrapolates it in a straight line
(2) the failures show up; the story turns to disappointment
(3) slow work: new tools, standards, habits, rebuilt institutions
(4) late on, the effects exceed what anyone was claiming
(schematic, not data; # = the two curves cross)Why do smart people misjudge this? Because demos are cheap and deployment is expensive. A demo is like a proof-of-concept exploit that works on the author's machine: it proves that something is possible, not that it is reliable, affordable or safe at scale. The gap is filled with standards, training, regulation and habit, and that work is slow.
So how do we judge a claim in the moment? Here is a checklist.
- Is there a mechanism, or just a demo? A result you cannot explain is an anomaly, not yet a theory.
- Has it been measured independently? Cold fusion (1989) is the classic non-replication.
- Does it predict something new that came true? Halley's comet, Neptune, the bending of starlight in 1919 (the original data are messier than the legend, but later measurements confirm the effect) and gravitational waves (2015) all passed.
- Does it survive hostile testing? Ask people who want it to fail.
- What are the base rates? Most announced revolutions fade.
- Who profits from belief? Theranos is the cautionary tale.
- What would change my mind? If nothing could, it is not an assessment.
Benefits and risks, fairly
Every revolution above cut both ways. Physics gave medical imaging, nuclear power and, after fission was found in 1938, the bomb. Darwin's theory was abused as "social Darwinism" and eugenics, though a description of how populations change says nothing about what we should value. Genetics offers a cure for a painful blood disease and the temptation of "designer babies"; in 2018 He Jiankui's germline-edited children were condemned worldwide. The digital age brought open knowledge and also surveillance and misinformation.
AI is the live case. Protein structures, translation and coding help are real gains. Open problems include confident errors, energy use, who benefits, bias, misuse and concentrated power. Serious experts disagree widely, from "another useful tool" to "the most consequential technology yet", and some warn of severe long-term risks while others think attention should stay on present harms. I do not think anyone knows the trajectory, and I distrust anyone who sounds certain either way.
Closing
For a reverse engineer, Kuhn is practical advice. Your tools and assumptions are your paradigm. The anomalies you set aside, a checksum that never matches or a field you called padding, are where the next finding hides. Hold the framework loosely enough to notice what it cannot explain, and tightly enough to get work done.