Per-Hour Learning Potential / Utility: ★★★★★ (5/7)
Readability: ★★★ (3/7)
Challenge Level: 4/5 (High) | 264 pages official
Blurb/Description: Considered a landmark book in scientific history, “The Structure of Scientific Revolutions” popularized the term “paradigm shift” and explores how scientific progress actually gets done.
Summary: This is one of those books that gets cited widely: Richard Thaler cites it as an inspiration in “Misbehaving” (M review + notes), and even Stephen Covey mentions it in “The 7 Habits of Highly Effective People” (7H review + notes).
Does it live up to the citation count? Partially. Is it an entirely and irrevocably true description of how the world works? Probably not. But neither are most books, and this is still one that’s worth reading (even if that’s not today, given its difficulty.)
Highlights: In terms of concepts, this book synthesizes a lot of different mental models to explain how ideas are formed, developed, and (ultimately) broken – while physical science is the focus, there are obviously far broader takeaways here for understanding the development of thought and the discovery of better ways of doing things. Kuhn presents a thoughtful and rational analysis of how scientific progress actually occurs.
Lowlights: Unfortunately, this book is academic – i.e., dense, repetitive, and difficult to read; while it isn’t overly long in the absolute sense (200 pages), it’s one of those books that routinely uses two or three pages of text to convey what could/should have been covered in one page or less.
There’s also a lot of time spent on what amount to unimportant semantic differences that seem to distract from rather than build to the core point (for example, the discussion of “rules” vs. “paradigms” – huh?).
This is definitely one of those “right time” books that I think most people should read, but it should be later on in your education, after you understand enough of the underlying phenomena to appreciate the useful parts of the material and synthesize your own ties between Kuhn’s concepts and other real-world applications, while being comfortable skimming / not getting bogged down in the minutiae.
Finally, the book’s perspective has been challenged by others – see Peter Godfrey-Smith’s “Theory and Reality” (TaR review) if you care to go even deeper.
You should buy a copy of The Structure of Scientific Revolutions if: you’re prepared to slog through a difficult read to get some thought-provoking insights.
Reading Tips: skim heavily. Also, this is a book that seems to drop off sharply toward the end and simply extend/repeat things already said… there is an interesting-but-not-useful contrast between natural sciences and softer sciences in the “Progress through Revolutions” chapter, but I didn’t read anything noteworthy after that.
Pairs Well With:
Reread Value: 2/5 (Low)
More Detailed Notes + Analysis (SPOILERS BELOW):
IMPORTANT: the below commentary DOES NOT SUBSTITUTE for READING THE BOOK. Full stop. This commentary is NOT a comprehensive summary of the lessons of the book, or intended to be comprehensive. It was primarily created for my own personal reference.
Much of the below will be utterly incomprehensible if you have not read the book, or if you do not have the book on hand to reference. Even if it was comprehensive, you would be depriving yourself of the vast majority of the learning opportunity by only reading the “Cliff Notes.” Do so at your own peril.
I provide these notes and analysis for five use cases. First, they may help you decide which books you should put on your shelf, based on a quick review of some of the ideas discussed.
Second, as I discuss in the memory mental model, time-delayed re-encoding strengthens memory, and notes can also serve as a “cue” to enhance recall. However, taking notes is a time consuming process that many busy students and professionals opt out of, so hopefully these notes can serve as a starting point to which you can append your own thoughts, marginalia, insights, etc.
Third, perhaps most importantly of all, I contextualize authors’ points with points from other books that either serve to strengthen, or weaken, the arguments made. I also point out how specific examples tie in to specific mental models, which you are encouraged to read, thereby enriching your understanding and accelerating your learning. Combining two and three, I recommend that you read these notes while the book’s still fresh in your mind – after a few days, perhaps.
Fourth, they will hopefully serve as a “discovery mechanism” for further related reading.
Fifth and finally, they will hopefully serve as an index for you to return to at a future point in time, to identify sections of the book worth rereading to help you better address current challenges and opportunities in your life – or to reinterpret and reimagine elements of the book in a light you didn’t see previously because you weren’t familiar with all the other models or books discussed in the third use case.
Kuhn starts by dimensionalizing the issue he is trying to address and the manner in which he will do so; for example, he focuses on the physical rather than biological sciences, and also does not comment on:
“the role of technological advance or of external social, economic, and intellectual conditions in the development of the sciences.”
Kuhn starts by positing that even theories that have been discarded were not necessarily unscientific in their conception, making it:
“difficult to see scientific development as a process of accretion.”
The corollary to this:
“education [in fundamental questions] is both rigorous and rigid; these answers come to exert a deep hold on the scientific mind.”
That leads to:
“normal science, the activity in which most scientists inevitably spend almost all their time, is predicated on the assumption that the scientific community knows what the world is like…
normal science… often suppresses fundamental novelties because they are necessarily subversive of its basic commitments.”
“the profession can no longer evade anomalies that subvert the existing tradition,”
“the extraordinary investigations that lead the profession… to a new basis for the practice of science.”
Kuhn wants to dimensionalize how and why these paradigm shifts occur. Kuhn defines “normal science” as:
“research firmly based upon one or more past scientific achievements… acknowledge[d] for a time as supply the foundation for its further practice.”
Textbooks, according to Kuhn, set the “paradigms,” i.e.: they
“implicitly define the legitimate problems and methods of a research field for succeeding generations of practitioners.”
Paradigms (ex. “Newtonian physics”) are shared by researchers in a field and rarely disputed.
Kuhn notes that in the absence of a unifying paradigm, it is hard to have cohesion in the study of any independent discipline, and that over time, paradigms are reached.
This tends to lead to a number of outcomes – increased efficiency/directedness in research, as well as increased specialization / unintelligibility of the research to those who do not share the paradigm.
Kuhn refers to this type of science as “normal science” – since paradigms tend to provide good explanations for only a small set of problems, normal science represents:
“an attempt to force nature into the preformed and relatively inflexible box that the paradigm supplies.”
Kuhn adds, on product vs. packaging among other things:Phenomena that will not fit in the box are often not seen at all... |scientists| are often intolerant of |new theories| invented by others. - Thomas Kuhn Click To Tweet
Okay, so that was a lot. Let’s unpack it. The “paradigm” can be viewed as a relatively inflexible, field-wide schema that permits through only material in accordance with what is already known.
It’s perpetuated by a number of mechanisms, including status quo bias – people are doing what has been done; authority bias – people are doing what they were taught; local vs. global optimization – you’re climbing the hill that you’re on; finally, incentives – if you’ve been doing things one way, you have a good reason to continue to want to do it that way.
How does this play out in the real world? Although there are criticisms of Kuhn’s view – as overviewed in Peter Godfrey-Smith’s “Theory and Reality” – I can point out one situation where it’s nearly spot-on.
Richard Thaler’s “Misbehaving” (M review + notes) is my favorite book, because it is both the best book on behavioral economics / cognitive biases that I’ve ever read (of countless many), but it’s also unique in that it explores how those cognitive biases played out in the development of behavioral economics as a legitimate field of study.
Thaler’s book explores these concepts in various ways: the completely and profoundly “rational actor” hypothesis was the entrenched “paradigm” from which “normal science” (economics, in this case) proceeded. (See humans vs. econs .)
Indeed, it proceeded so bizarrely and brutally that Thaler notes on Page 96 that it got to the point where humans, known for not being able to delay gratification very well, are now (per Robert Barro) modeled as econs who think not only about the long-term impact of a windfall on their children’s inheritance and grandchildren’s inheritance, but also the offsets of the deficit impacts of a tax cut and so on…
And incentives and commitment bias were clearly in full gear. On page 43, he mentions how one unusually candid economist literally asked Thaler: if your newfangled theory is correct, what do I do? I’ve spent my entire career figuring out how to do it the old way…
“academics don’t like to talk about research in the abstract […] but if scientists from one field start presenting their research findings in the manner that the colleagues in their field expect, the scientists from other disciplines are soon overwhelmed by technical details they do not understand, or bored by theoretical exercises they find pointless.”
Maps up to Kuhn pretty well so far. Indeed, Thaler actually references Kuhn extensively in his “Anomalies” chapter.) Another example could be found in Meredith Wadman’s “The Vaccine Race” (TVR review + notes) and David Oshinsky’s “Polio: An American Story” (PaaS review + notes)
Some bad science (overinterpretation of data) set back the polio hunt: Albert Sabin and a colleague managed to successfully grow poliovirus in cultures of fetal nerve cells, but not in other cells for fetuses; nerve cells do not make for good vaccines (injecting them can cause allergic encephalomyelitis, i.e. inflammation of the brain and spinal cord).
It turns out that polio can and does grow in other types of cells – John Enders, for example, noticed that poliovirus is found in large quantities in fecal matter (suggesting it grows in the intestines, which don’t have a profusion of nerve cells like the brain and spinal cord.) The specific strain of polio tested would only grow in nerve tissue, but it was not representative of all strains.
See also pages 17 – 19 of “Polio: An American Story” (PaaS review + notes) for some background on Simon Flexner, who (at least per Oshinsky) was likely one of the primary reasons that the strain of polio often studied only reproduces in nerve cells.
Oshinsky doesn’t specify there, but my intuition is that it’s a function of trait adaptivity and selection or optimization. (Flexner repeatedly passed the virus through nerve tissue, so the virus ended up either via selection or optimization only being able to reproduce in that sort of tissue.)
Wadman’s whole book also overviews paradigms on human vs. monkey cells and on cancerous vs. non-cancerous cells.
It’s not all bad, though; Kuhn reiterates that scientific progress is better with paradigms (I’m editorializing here, but – whether guided by, or in opposition to, at least paradigms provide a framework to reference and organize thoughts around – there are many flaws in Origin of the Species, for example, but it was undeniably a huge step forward for progress in the biological sciences.)
Kuhn cites three aims; i.e., designing real-world experiments to compare the theory’s predictions to reality (ex. seeing if light travels faster in air than water), and fact-finding (such as nailing down constants, atomic weights, specific mechanisms by which the general paradigm is assigned, etc).
Kuhn also discusses theoretical work aimed to clarify aspects of the paradigm (for example, incorporating air resistance into a theory that simplified by assuming no air resistance – which makes the theory more precise, but still keeps the same paradigm in place.)
Kuhn brings up the “puzzle vs. mystery” issue explored in more depth by Leslie in “Curious” (C review + notes). Kuhn notes that puzzle-solving is often (my word not his) autotelic (see Csikszentmihalyi’s Flow), with the process proving to be its own reward – independent of social utility.
One of the core attractions of this behavior of solving puzzles within the constraints of an existing paradigm is the guarantee of a solution – exploring “mysteries” (Leslie’s lingo, not Kuhn’s, and I’m editorializing here) might prove to be unfruitful, whereas (still editorializing), to borrow a phrase from Achor, “all that matters is getting published.”
In Chapter V, Kuhn extensively discusses the difference between “paradigms” and “rules” which A) seems a bit semantic and B) I frankly don’t understand nor care to at this time, as it doesn’t seem particularly useful.
Kuhn starts to get more into the meat of things with a discussion of how new paradigms generally come to be: they start with someone noticing “anomalies” of nature that don’t fit the facts (ex. Thaler…) and then following up on them.
He continues with an extended, albeit mildly interesting, discussion of how discovery is usually not a moment but rather a process. He also reiterates that paradigms, paradoxically, are important in the process of paradigm shifts:
“anomaly appears only against the background provided by the paradigm.”
Or, contrast bias.
To summarize the entire next chapter, the emergence of a new theory usually occurs when the old theory either fails to answer many problems, or becomes so complicated in its “adjustments” that it can no longer be taken seriously.
Tying it back to Thaler: CAPM once you adjust for momentum, value, etc… it’s clearly somewhere between “a joke” and “utterly delusional” and yet for some reason still taken seriously. As Thaler quips on p. 229 of “Misbehaving” (M review + notes) about the new “profitability” risk factor:
“it is difficult to tell a plausible story in which highly profitable firms are riskier than firms losing money.”
Kuhn notes that counterexamples to a paradigm are usually discarded until a whole different paradigm can be substituted therefore, because:
“to reject one paradigm without simultaneously substituting another is to reject science itself.”
Anomalies and crisis often lead, in Kuhn’s view, to philosophical analysis or “thought experiments.” Kuhn continues with an observation about age:
“Almost always the men who achieve these fundamental inventions of a new paradigm have been either very young or very new to the field whose paradigm they change.”
“what a good thing it would be, if every scientific man was to die when sixty years old, as afterwards he would be sure to oppose all new doctrines.”
Now we come to revolution: Kuhn makes the analogy to politics:
“society is dividend into competing camps… because [parties] differ about the institutional matrix within which political change is to be achieved… [they] must finally resort to techniques of mass persuasion.”
There is little room for overlap because:
“[paradigms’] role is necessarily circular. Each group uses its own paradigm to argue in that paradigm’s defense… [the argument] cannot be made logically or even probabilistically compelling for those who refuse to step into the circle. The premises and values shared by the two parties to a debate over paradigms are not sufficiently extensive for that.”
There’s an interesting logical argument from pages 99 – 103 that I need to go back and reread because I don’t wholly understand it, but I feel like it’s important… it deals with the idea of treating a previous (now incorrect) paradigm as a “special case” of the newer, more correct paradigm, and why that is wrong?
Kuhn addresses the ties between paradigms and worldview / schema:
“what a man sees depends both upon what he looks at and also upon what his previous visual-conceptual experience has taught him to see.”
He cites a number of experiments in perception and relates the shift in paradigms to these. While a lot of this chapter is pretty semantic, Kuhn eventually notes, very similarly to what he has said previously, that:
“paradigms are not corrigible by normal science… scientists then often speak of… the ‘lightning flash’ that ‘inundates’ a previously obscure puzzle, enabling its components to be seen in a new way that for the first time permits its solution.”
Kuhn is here referencing intuition, which as Kip Tindell of The Container Store might say, “only comes to a prepared mind.” It’s a well-corroborated phenomenon in science: see, for example, Richard Rhodes’ “The Making of the Atomic Bomb” (TMAB review + notes), which demonstrates a number of these.
The actual mechanism behind intuition is interesting. REM sleep is implicated in some of it – see, for example, Dr. Matthew Walker’s “Why We Sleep” – REM sleep is critical for creativity and abstract cross-linking of phenomena.
Kuhn also provides an example of progress in one field being driven by someone from another field (and thus with a different paradigm) coming in and looking at already-known facts in a different way. This is, of course, exactly what happened in “Misbehaving” (M review + notes): economics injected with a good dose of psychology.
Various of the books I’ve read examine other interplays: between neuroscience and psychology, for example, or design and public policy (here I’m referencing Sunstein/Thaler’s “Nudge” – NDGE review + notes). John Lewis Gaddis does a particularly good job of exploring this process in “The Landscape of History” LandH review + notes), terming it “consilience” – Gaddis stresses, throughout the book, the importance of:
“remaining open to what insights from one field can tell you about another.”
Kuhn believes that textbooks hide the existence of revolutions by only presenting ideas from previous paradigms insofar as they are still valid or useful.
An example that comes to my mind is the Bohr Model from intro chem – they told us it was wrong but useful. Another is “The Up Side of Down” (UpD review + notes), for example, Megan McArdle notes that current theories are presented as obvious facts and old theories are presented in a way that makes the proponents seem hilariously out of touch with reality.
Reality is, of course, a lot more complicated; plenty of really smart scientists went down rabbit holes. There are lots of great examples of this. Two of my favorite books touching on the topic are Richard Rhodes’ “The Making of the Atomic Bomb” (TMAB review + notes) and David Oshinsky’s “Polio: An American Story” (PaaS review + notes). In both cases, the progress of science was actually halted by very, very smart scientists making mistakes.
Anyway, back to Kuhn. Kuhn disagrees with Karl Popper, who believes that a negative test:
“necessitates the rejection of an established theory.”
In contrast, Kuhn believes that:If any and every failure to fit were ground for theory rejection, all theories ought to be rejected at all times. - Thomas Kuhn Click To Tweet
Therefore, Kuhn takes a probabilistic view.
Kuhn quotes Darwin and Planck, who were both pessimistic about older scientists accepting their new paradigms (they believed that the young would take up the mantle), Kuhn seems to be somewhat more optimistic.
First Read: 2017
Last Read: 2017
Number of Times Read: 1
Planning to Read Again?: probably not