In this blog post, based on Thomas Kuhn’s theory of paradigms, we will examine the process of scientific development, the evolution of paradigms, and what the future holds for paradigms in science.
How did Thomas Kuhn explain the development of science?
In the past, historians of science believed that science developed through the simple accumulation of individual scientists’ discoveries and achievements. However, Thomas Kuhn challenged this conventional view of science. In ‘The Structure of Scientific Revolutions’, he argued that such a perspective was based solely on the completed scientific achievements recorded in classical texts and science textbooks. He explains that science does not develop through accumulation but rather through scientific revolutions, which are non-accumulative processes. In this article, we will examine the process of scientific development centered on Kuhn’s concepts of scientific revolutions and paradigms, and consider what characteristics paradigms will take on as science continues to advance.
Kuhn introduced the concept of a “paradigm” to explain scientific revolutions. A paradigm, as a scientific achievement, possesses two characteristics. First, it must be a groundbreaking achievement distinct enough from existing competing theories; second, it must possess sufficient flexibility to leave behind enough research questions for subsequent researchers to solve various problems. Kuhn defines a scientific revolution as the process by which an existing paradigm is replaced, either completely or partially, by a new paradigm. Furthermore, the period during which scientific research is conducted under a single dominant paradigm is called “normal science.”
Kuhn presents three examples of such paradigm shifts. The first is Copernicus’s proposal of the heliocentric model to replace Ptolemy’s geocentric model; the second is Lavoisier’s proposal of the oxygen theory to overcome the limitations of the phlogiston theory. The third is the case of Einstein, who reinterpreted the concept of absolute space-time in Newtonian mechanics through the theory of relativity.
A common feature of paradigm shifts observed in these three cases is that the change occurred at the point when the shortcomings of the existing paradigm became clearly apparent. Ptolemy’s geocentric model failed to accurately explain the positions of the planets and their precession, and the phlogiston theory could not adequately account for the increase in mass of substances during combustion. Furthermore, Newtonian mechanics revealed various limitations as optics and electromagnetism advanced. Kuhn describes this situation as a “crisis of normal science.” A crisis of normal science does not arise simply because of the failure of a few scientists; rather, it emerges when the majority of scientists consistently fail to solve problems within the existing paradigm through normal scientific methods. This is because normal science is fundamentally conservative in nature, seeking to refine the existing paradigm.
Why are scientific paradigms different from cultural trends?
Meanwhile, the concept of “paradigm” as used in ‘The Structure of Scientific Revolutions’ is a term with a wide range of meanings. Kuhn directly addresses this in “A Reconsideration of the Paradigm,” published after the book’s release. He reflects that the term “paradigm” could be interpreted differently by each reader and, ironically, that this was one of the reasons the book became so widely read. Today, the term “paradigm” is widely used not only in science but also in nearly every field, including technology, politics, economics, culture, and the arts.
Although paradigms are utilized in various fields as described above, paradigms in science and technology differ in nature from those in culture and the arts. In the fields of culture and the arts, the term “paradigm” can be understood to mean something closer to a fad or trend. In these fields, paradigms often recur cyclically.
For example, retro fashion that was popular in the past may regain popularity, and idol culture, which had been in decline for a while, may once again attract attention. Of course, there are also trends that never resurface. However, the process seen in science—where a crisis arises due to internal problems within the existing paradigm, leading to a shift to a new paradigm—generally does not occur in culture and the arts. In these fields, it is simply a matter of individual tastes and social trends changing.
In contrast, paradigms in science and technology are fundamentally non-cyclical. This is because, in science, a shift to a new paradigm can only occur once multiple scientists have clearly identified the flaws in the existing one. Therefore, when a new paradigm takes hold, it also means that the previous paradigm no longer possesses core explanatory power. For example, determining the existence of the ether was once a very important subject of research in classical electromagnetism. Similarly, before the oxygen revolution, measuring the mass of phlogiston was a major research task. However, today’s science textbooks do not cover experiments to calculate the density of the ether or measure the mass of phlogiston, and it is highly unlikely that such research will reemerge as a central focus of science in the future.
The same applies to the field of technology. It is unrealistic to expect that, in the future, we will routinely use ENIAC—the first electronic computer—instead of tablet PCs, or that steam locomotives will once again become the main mode of transportation instead of high-speed trains. Furthermore, paradigms do not exist in infinite numbers; they are formed through the process by which scientists select the theory they deem most appropriate from among those currently available. If, over time, existing paradigms continue to be discarded and the emergence of new paradigms gradually becomes more difficult, we can imagine a scenario in the distant future where the number of available paradigms itself gradually decreases.
As science advances, will it become harder for new paradigms to emerge?
Here, we need to consider the concept of the “scope” of a paradigm. Kuhn, too, distinguished between two main uses of the term “paradigm” in ‘A Reconsideration of the Concept of a Paradigm’. One is a broad sense that encompasses all the shared assumptions of a particular scientific community, while the other is a narrow sense that refers to a single, particularly important assumption among them. In this article, we use the term “large paradigm” in a sense closer to the first definition. In other words, it refers to a paradigm that has had a profound impact on the history of science and represents a field in which many scientists have conducted research over a long period. Conversely, a “small-scale” paradigm refers to one that has had a relatively minor impact on the history of science, involves a smaller number of researchers, and has a shorter duration of research.
When examining the scale of a paradigm from a cost perspective, we can consider three examples. The first example is Galileo’s observation of Jupiter’s four moons using a telescope. Today, some 400 years later, humanity is developing and operating space telescopes costing billions of dollars to observe the early stages of the universe. The second example is that optical microscopes were used to discover cells, atomic force microscopes were developed to observe structures at the atomic level, and the Large Hadron Collider (LHC)—a massive international collaborative research facility—was utilized for the discovery of the Higgs boson. The third example is semiconductor technology. While memory capacity increased rapidly in the past, as the miniaturization of semiconductors neared its physical limits, performance improvements have since been achieved through various methods, such as new architectures, stacking technologies, High-Bandwidth Memory (HBM), and advanced packaging.
In the first example, it is difficult to definitively determine whether the discovery of Jupiter’s moons or the observation of early-universe celestial bodies is the greater achievement in the history of science. In the second example as well, opinions may vary on whether the discovery of the cell, the atom, or the Higgs boson represents the most outstanding achievement. Similarly, in the third example, the increase in memory capacity alone does not directly reflect the magnitude of a scientific achievement. However, what these three examples reveal is that, as science advances, achieving results on a scale comparable to those of the past often requires significantly more resources, equipment, and collaboration.
The increasing specialization of research fields is another characteristic that emerges as science advances. Of course, while the world’s population and the number of researchers have grown significantly compared to the past, the range of research fields has become far more diverse. Consequently, the size of the scientific community dedicated to a specific subfield may become relatively smaller. When considering the scientific field as a whole, it can be argued that the pace of scientific progress has accelerated significantly compared to the past. However, when looking at a single subfield, there is a possibility that the pace of development in normal science may slow down compared to the past as research becomes more specialized.
In such a situation, grand paradigms requiring massive research funding and a large number of researchers may emerge less frequently than in the past, and the frequency of new paradigms of a similar scale emerging may also decrease. Scientists researching relatively small fields also require increasingly more research funding and specialized equipment. This is why scientists sometimes joke, “If I had been born in the pre-Einstein era, might I have discovered the theory of relativity?” Of course, this is merely a hypothetical scenario, but it is clear that the difficulty of research has increased significantly because current scientific research builds upon countless past achievements. In such an environment, the temptation to violate research ethics may also grow. Manipulating research results or committing plagiarism to secure more funding or produce research outcomes seriously hinders the progress of science.
If this situation continues, in a future society where science is far more advanced, the emergence of new paradigms may become rarer than in the past, and the boundaries between “normal science,” “crises of normal science,” and “paradigm shifts” may become even more blurred than they are now. Thus, while Kuhn’s model of development centered on scientific revolutions applies well during periods when paradigms are abundant, it may need to be understood differently in a society where science is highly mature. Of course, there are still numerous scientific challenges for humanity to uncover, and new fields of research—such as artificial intelligence, quantum technology, space science, and life sciences—continue to emerge. Nevertheless, there are quite a few fields today where the pace of progress feels slower than in the past due to technical limitations, enormous research costs, and difficulties in practical application. Therefore, how scientific paradigms will evolve in the future and what relationship they will have with the advancement of science are questions that remain worthy of deep consideration.
