Model shows how scientific paradigms rise and fall
[This figure shows 12 consecutive states of a system driven by the model, with one unit of time equaling one update for every agent. In the first picture, a new idea is dominating but small specks of color represent a finite innovation rate. A new state dominates between the third and fourth pictures, and in the fourth, fifth, and sixth pictures, two coherent states coexist. New individual dominant states arise in pictures nine and twelve. Image credit: S. Bornholdt, et al. ©2011 American Physical Society.]
Scientific concepts such as climate change, nanotechnology, and chaos theory can sometimes spring up and capture the attention of both the scientific and public communities, only to be replaced by new ideas later on. Although many factors influence the emergence and decline of such scientific paradigms, a new model has captured how these ideas spread, providing a better understanding of paradigm shifts and the culture of innovation.
The model shows how a system with one dominating scientific paradigm transitions into a system with small clusters of ideas, some of which continue to grow until one dominates, and the process repeats with new ideas. The dynamics of the rise and fall of scientific paradigms depends on the system’s innovation rate. Systems with high innovation rates tend to contain a high degree of noise, along with many small domains of ideas that are constantly generated and replaced. In contrast, systems with low innovation rates tend to have low noise and a state that remains dominant for a long time until a single event replaces it.