Book Review: The Structure of Scientific Revolutions
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As part of DCI’s efforts to “build a new field” (of blockchain and cryptocurrency technology), and as part of my personal interest in paradigm shifts, I recently read The Structure of Scientific Revolutions by Thomas S. Kuhn. (It popularized the term “paradigm shift”!) In this book, Kuhn examines the history of science to understand how new scientific fields (and their associated paradigms) are created. In other words, the process of paradigm-nature fit. Read on to learn about: the definition of paradigms, how they’re created, and how they map them onto political revolutions!
What is a Paradigm?
First off, let’s look at Kuhn’s definition of a paradigm. Paradigms are an integral part of scientific field, not just a set of methodologies:
Rather than being elementary logical or methodological distinctions, which would thus be prior to the analysis of scientific knowledge, [paradigms] now seem integral parts of a traditional set of substantive answers to the very questions upon which they have been deployed. That circularity does not at all invalidate them.
And paradigms are not just the observations themselves:
“Observation and experience can and must drastically restrict the range of admissible scientific belief, else there would be no science. But they cannot alone determine a particular body of such belief. An apparently arbitrary element, compounded of personal and historical accident, is always a formative ingredient of the beliefs espoused by a given scientific community at a given time.”
In his postscript from 1969, Kuhn gives a bit more texture to his definition of a paradigm. First, as a “constellation of group commitments” that come in three forms:
- Symbolic Generalizations that can be “deployed without question/dissent”. (f = ma)
- Beliefs in particular models. (e.g. Molecules of a gas behave like tiny elastic billiard balls in random motion.)
- Values (primarily used for decision making in times of crisis).
Second, Kuhn sees paradigms as an example (an “exemplar”) shared by a community. Upon reflection, Kuhn sees this “exemplar” definition as quite important: “The paradigm as shared example is the central element of what I now take to be the most novel and least understood aspect of this book.”
By “shared example”, Kuhn means: “the concrete problem-solutions that students encounter from the start of their scientific education.” Or, “learning from problems to see situations as like each other, as subjects for the application of the same scientific law or law-sketch.” In my words, I’d define these “prototypical examples” as something like “the ability to see two problem-solution sets as isomorphic.”
(For other definitions of paradigms, see “water” from DFW and “leverage points” from Donella Meadows.)
Process: Normal Science ➡ Crisis ➡ New Paradigm
How then do new scientific fields (with their associated paradigms) come into existence? This happens through a process: from the “puzzle-solving” of normal science, to a crisis (brought on by anomalies), and finally to a new paradigm that “solves” that crisis.
Normal Science: Legibilizing Puzzle-Solving that Perpetuates Itself
“Normal science” is the process of “puzzle solving” that we normally associate with science. It rests on a foundation of commitments:
“The existence of this strong network of commitments — conceptual, theoretical, instrumental, and methodological — is a principal source of the metaphor that relates normal science to puzzle-solving.
In other words, a paradigm can only solve problems it can legibilize:
“A paradigm can, for that matter, even insulate the community from those socially important problems that are not reducible to the puzzle form, because they cannot be stated in terms of the conceptual and instrumental tools the paradigm supplies.”
This set of assumptions are strongly committed to by the scientific community:
“Much of the success of the enterprise derives from the community’s willingness to defend that assumption, if necessary at considerable cost. Normal science, for example, often suppresses fundamental novelties because they are necessarily subversive of its basic commitments.”
In other words, it’s a classic case where the system wants to perpetuate itself.
Crisis Creates Paradigmatic Competition for Intellectual Mindshare in Answering Interesting Questions
However, “normal science” can’t just go on forever. Instead, the scientific process eventually finds anomalies that force a “crisis”, which leads to the creation of a new paradigm that solves that crisis (and then competition between the new and old paradigms). Kuhn writes:
“Crisis and theory change also go hand in hand. Anomalies become intractable.”
This process for finding anomalies is fascinating. Why does normal science find anomalies/novelties when it so often first rejects them? How is:
“normal science, a pursuit not directed to novelties and tending at first to suppress them, nevertheless so effective in causing them to arise?”
This is because paradigms become increasingly fine-tuned to detect anomalies:
“Novelty ordinarily emerges only for the man who, knowing with precision what he should expect, is able to recognize that something has gone wrong. Anomaly appears only against the background provided by the paradigm. The more precise and far-reaching that paradigm is, the more sensitive an indicator it provides of anomaly and hence of an occasion for paradigm change.
These anomalies kickstart a “crisis”, a:
“Proliferation of competing articulations, the willingness to try anything, the expression of explicit discontent, the recourse to philosophy and to debate over fundamentals.”
These paradigms then begin to compete with each other:
“Paradigms gain their status because they are more successful than their competitors in solving a few problems that the group of practitioners has come to recognize as acute. …paradigm debates always involve the question: Which problems is it more significant to have solved?”
Most importantly, they compete for scientists’ time with interesting unsolved problems. New paradigms:
attract an enduring group of adherents away from competing modes of scientific activity…[with questions] sufficiently open-ended to leave all sorts of problems for the redefined group of practitioners to resolve.
In other words, a new paradigm must both: create a coherent foundation and leave open a bunch of interesting questions:
“The consequences of the viewpoint being discussed are not exhausted by the observations upon which it rested at the start.”
In fact, this crisis and paradigmatic competition is necessary to the survival of a new paradigm. Without a crisis, no one cares:
Theories developed in the seventeenth century by Rey, Hooke, and Mayow failed to get a sufficient hearing because they made no contact with a recognized trouble spot in normal scientific practice.
I like to think of these two stages as “progress from error” (normal science) vs. “progress from confusion” (crisis leading to paradigm shift):
“The pre-paradigm period, in particular, is regularly marked by frequent and deep debates over legitimate methods, problems, and standards of solution, though these serve rather to define schools than to produce agreement.”
Francis Bacon states this from the perspective of normal science:
“Truth emerges more readily from error than from confusion.”
Paradigm Shift: The Data Itself Changes
Finally, a paradigm emerges as a successful perspective to prioritize, answer, and solve problems. (i.e. It’s found paradigm-nature fit.) Once this happens, one of the craziest aspects of a paradigm shift is that the data itself changes based on the new paradigm. In fact, this is Kuhn’s main goal: “my most fundamental objective is to urge a change in the perception and evaluation of familiar data.”
In an extreme case, this could be phrased as something like “the world is entirely dependent on the lens you view it through”.
“When [the chemical revolution] was done…the data themselves had changed. That is the last of the senses in which we may want to say that after a revolution scientists work in a different world.”
“It is rather as if the professional community had been suddenly transported to another planet where familiar objects are seen in a different light and are joined by unfamiliar ones as well.”
Or, a rephrasing of this phenomenon: In situation X, with paradigm Y, we perceive Y. But, in situation X, with paradigm Z, we perceive Z.
“Initially, only the anticipated and usual are experienced even under circumstances where anomaly is later to be observed.”
In other words, scientists see what they expect to see. However, even once they successfully accept the new paradigm/theory, the data doesn’t just “show up perfectly”. Instead:
“Even after accepting the theory, they had still to beat nature into line, a process which, in the event, took almost another generation. When it was done…the data themselves had changed. That is the last of the senses in which we may want to say that after a revolution scientists work in a different world.”
I love this phrase, to “beat nature into line”. The process through which you make the world conform to your new paradigm.
This idea that “the data itself changes” leads to a related idea — that two folks who see the world through two different paradigms can only say there is a “misunderstanding”, not that each other are completely “wrong”:
“…[This is a] misunderstanding between the two competing schools. The laymen who scoffed at Einstein’s general theory of relativity because space could not be ‘curved’ — it was not that sort of thing — were not simply wrong or mistaken.”
One final note on the data itself changing: once it changes, the system feels tautologically true, and impossible to see it in a different way.
“These anomalies will then no longer seem to be simply facts. From within a new theory of scientific knowledge, they may instead seem very much like tautologies, statements of situations that could not conceivably have been otherwise…It has often been observed, for example, that Newton’s second law of motion, though it took centuries of difficult factual and theoretical research to achieve, behaves for those committed to Newton’s theory very much like a purely logical statement that no amount of observation could refute.”
Political Revolutions
There’s a great section at the end where Kuhn maps political revolutions onto scientific revolutions:
“Political revolutions are inaugurated by a growing sense, often restricted to a segment of the political community, that existing institutions have ceased adequately to meet the problems posed by an environment that they have in part created.”
This is a beautiful articulation of our current situation. The institutions co-created by the Industrial Revolution paradigm are no longer adequate for the global problems they have birthed. Kuhn goes on to explain institutional co-evolution and how we “exit” a given institutional set:
“Political revolutions aim to change political institutions in ways that those institutions themselves prohibit. Their success therefore necessitates the partial relinquishment of one set of institutions in favor of another, and in the interim, society is not fully governed by institutions at all…In increasing numbers individuals become increasingly estranged from political life and behave more and more eccentrically within it. Then, as the crisis deepens, many of these individuals commit themselves to some concrete proposal for the reconstruction of society in a new institutional framework. At that point the society is divided into competing camps or parties, one seeking to defend the old institutional constellation, the others seeking to institute some new one. And, once that polarization has occurred, political recourse fails. Because they differ about the institutional matrix within which political change is to be achieved and evaluated, because they acknowledge no supra-institutional framework for the adjudication of revolutionary difference, the parties to a revolutionary conflict must finally resort to the techniques of mass persuasion, often including force.”
Finally, here’s a quick brainstorm for how I’d apply this to crypto field building and paradigm shifts generally.
Crypto Field Building:
- What is the crisis that we’re responding to? Is it in an academic field like computer science, economics, law, complex systems, or ethics? Or perhaps it’s a response to more macro technosocietal and political crises? (e.g. #LateStageCapitalism)
- How can we win over intellectual mindshare? This happens for developers (e.g. through trust as a primitive, developer integrity, and meaning more generally). But it should also happen among academics (e.g. how many Nobel Prize / Turing award winners do we have?).
- How can we do a better job of both legibilizing the field and outlining the wide array of unsolved problems?
- How can we more clearly describe what it feels like to “go down the crypto rabbit hole”? How does our perspective change, and how does the data itself change?
Paradigm Shifts
- I really like the idea of a shared example, exemplar, or prototypical example. I think I see self-taxing as a version of this. (Given current societal problems, what is a solution to them?) Also, self-taxing seems also be part of a possible commitment set.
- The crisis process feels adjacent to the ideas in the Collapse of Complex Societies, which describes how societies collapse under the weight of their own complexity.
- The “mindshare” piece feels related to the nonviolent movement space, e.g. Crypto is Networked Nonviolent Protest. (In addition to the mindshare, a new paradigm needs capital.)
Also see:
- Open Philanthropy Project’s report on early field growth
- Patrick Collison and Michael Nielsen on Science Is Getting Less Bang for Its Buck
Thanks for reading! For more, check out my google doc of book highlights here.
