
Tech • AI • Robotics • Game
A 1960 demographic model that jokingly pointed to Friday, 13 November 2026 as humanity’s “doomsday” remains a striking case study in how fast-growing systems can appear headed for infinity before real-world behavior changes.
In 1960, three researchers at the University of Illinois, including Heinz von Foerster, published a paper in Science arguing that if historical population growth trends continued, humanity would hit a mathematical singularity around 2026. The precise date, Friday, 13 November 2026, was partly a joke, tied to von Foerster’s birthday. Yet the underlying formula fit roughly 2,000 years of population growth surprisingly well.
The logic was simple: the time needed for the global population to double had been shrinking, so extending the trend implied a doubling time eventually falling to zero. In mathematical terms, that sends the curve to infinity at a finite date. The paper even joked that descendants would not die of famine but be “crushed,” underscoring both the absurdity and the power of extrapolation.
World population growth did not continue accelerating forever. The annual growth rate peaked at about 2.3% in the 1960s and has since fallen by more than half. Even so, total population kept rising because slowing growth is not the same as decline; demographic momentum means a system can keep expanding long after its growth rate begins to fall.
The most important lesson is that a curve is not destiny. The von Foerster model remained close to reality for years, then drifted away as fertility, health, development and social behavior changed. That break illustrates a central problem with long-range forecasting: when the underlying system evolves, the old equation can lose its grip.
Similar reasoning keeps returning in new forms. Economist David Roodman applied related growth logic to humanity’s long-run economic output and found a possible blow-up around 2047, reading it less as prophecy than as a sign of potential instability. Futurist Ray Kurzweil popularized another date, 2045, linking a coming “singularity” to artificial intelligence rather than population.
One interpretation of these recurring curves is that innovation cycles are shortening. Major transitions appear to come faster over time, from long prehistoric eras to agriculture, then about 12,000 years to the industrial age, and only about two centuries from industry to electronic computing. On a much shorter horizon, societies also adopt new technologies increasingly quickly.
A related scientific idea focuses on dissipative structures, ordered systems maintained by constant energy flows. On a per-kilogram basis, more complex systems tend to process more energy: galaxies less than stars, stars less than planets, planets less than plants, plants less than animals, and animals less than human society. The human brain is a striking example, making up about 2% of body mass while using roughly 20% of its energy.
This has inspired speculation that advanced intelligence may not expand outward but condense inward, into denser and smaller substrates. In astrobiology and futurist thought, this challenges the classic Kardashev scale, which ranks civilizations by total energy capture. Thinkers such as John Barrow and John Smart instead emphasized mastery of smaller scales, from genes and molecules down to particles and perhaps spacetime itself.
Under that logic, radical enhancement would not necessarily mean longer life in the ordinary sense. It could mean denser experience, faster cognition and much shorter external duration. Economist Robin Hanson, in The Age of Em, explored worlds where emulated minds run about 1,000 times faster than humans, making one human day feel like nearly three years to them.
Mathematical singularities do not guarantee physical ones. The old paradox of Zeno shows that infinitely many shrinking steps can still sum to a finite distance or time. But physics also raises the possibility that space cannot be divided without limit, with the Planck length often treated as a candidate lower bound where current theories break down. That is one reason many “infinite” forecasts are better read as signs that a model is reaching its limits.
The date 13 November 2026 is not a literal doomsday but a reminder that exponential trends can look inevitable until reality bends them. The deeper lesson is that the future may still accelerate dramatically, but any forecast that extends a curve too far risks mistaking a temporary pattern for a law of history.
Ask a question