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History as a giant data set - mklabgr - 09-05-2026
History as a Giant Data Set: How Analysing the Past Could Help Save the Future
Author: Laura Spinney
Publication:The Guardian
Publication date: 12 November 2019
The article explores cliodynamics, an emerging discipline that treats history as a vast data set and uses mathematics, statistics and computer modelling to search for recurring patterns in the rise and decline of societies. Its central figure is Peter Turchin, originally a mathematical biologist, who argues that social systems can be studied much like ecological systems. His models suggest that societies often experience long “secular cycles” of prosperity and instability, driven by interacting factors such as population pressure, declining living standards, competition among elites, inequality and weakening state finances. These ideas build substantially on the earlier work of Jack Goldstone, who developed a political stress indicator, usually denoted $\Psi$, to represent the combined pressures generated by mass mobilisation, elite competition and fiscal weakness.
A major development behind this approach is the availability of enormous historical databases such as Seshat, which collects quantitative information about hundreds of societies across thousands of years. Researchers can use indirect evidence—coin hoards, skeletal remains, building sizes, wages, demographic records and even environmental proxies—to reconstruct variables that cannot be measured directly. Turchin argues that such data reveal recurring long-term cycles as well as shorter roughly 50-year “fathers-and-sons” oscillations in political violence. Applied to the United States, his models showed rising structural political stress from around the 1970s onward, which led him years in advance to identify the period around 2020 as one of elevated instability.
The article nevertheless emphasizes that cliodynamics is probabilistic rather than deterministic. It cannot predict the exact event that triggers a revolution or crisis; instead, it attempts to measure whether a society has become structurally vulnerable, in much the same way that meteorology estimates the probability of severe weather. Critics—particularly many traditional historians—argue that human behaviour is too contingent and culturally specific to be captured reliably by equations, and that large historical databases may reproduce biases or strip evidence of its context. Turchin's more ambitious claim is therefore not that mathematics can foretell history, but that quantitative models might eventually function as an early-warning system for societies, identifying dangerous structural pressures and allowing governments to intervene before instability turns into collapse.
Key takeaways
- History may contain measurable recurring patterns, rather than being entirely a sequence of unique events.
- Cliodynamics combines history + mathematics + statistics + complexity science + big data.
- Social instability tends to rise when inequality, elite competition, popular hardship and state weakness reinforce one another.
- The goal is not exact prophecy, but something closer to a “weather forecast” for political and social instability.
- The deepest question raised by the article is whether understanding historical cycles can help societies change their trajectory rather than simply repeat them.
ARTICLE / ARTICLE [PDF]