Why Evolution Gave Us Short Lifespans
Most people assume our biology is perfectly optimized by millions of years of evolution. But what if instead, evolution barely tried to optimize for longevity? That's the provocative argument from Jacob Kimmel, president and co-founder of New Limit. His work on epigenetic reprogramming suggests aging might be one of the easiest biological problems to solve — precisely because evolution never spent much time trying to solve it.
The Missing Signal
During most of human evolution, the baseline hazard rate was extremely high. This means the odds of dying on any given day were steep — from diseases, predators, infections, accidents. Even absent aging, most people wouldn't survive long enough for natural selection to favor longer lifespans.
If you're unlikely to reach old age anyway, there's no strong evolutionary pressure to extend your lifespan. The gradient signal for longevity is weak. Evolution selects for reproduction and offspring survival, not for living long after you've reproduced.
Kimmel points out that this same logic may explain why our fluid intelligence peaks around age 25-30 — that's when human populations were largest during evolution. We weren't selected to stay smart into old age because few people reached old age.
Negative Selection Against Longevity
But there's more. Even if positive selection for longevity was absent, there might be negative selection working against it.
Think of aging as a kind of regularization term in an evolutionary algorithm. A population full of older individuals actually slows down the genome's propagation. If you extend lifespan without eliminating aging, those older individuals consume more resources than they contribute. It's better to have two younger individuals reproduce than one older person keep living.
This creates a fitness penalty for longevity — another reason evolution didn't push hard on extending lifespan.
The Optimization Problem
The third factor involves evolutionary constraints. Evolution works like training a neural network: it can theoretically optimize anything, but finding the right path requires specific conditions.
Mutation rates limit how many changes you can make per generation. Too many mutations causes cancer. Population size limits how many variants can be screened simultaneously. For most of human history, infectious disease was the dominant selective pressure — shaping our genome around protection rather than longevity.
These constraints mean evolution simply didn't have enough computational "budget" to fully optimize for long, healthy lives.
Evolution never spent much time optimizing for longevity, which means there's low-hanging fruit for intervention.
Counterpoints
Critics might argue that this framework underestimates the complexity of aging itself — that we've already made significant progress in treating age-related diseases through other approaches. Others might point out that evolutionary arguments, while intellectually compelling, don't necessarily translate into easy biological interventions.
Bottom Line
Kellogg's core argument is compelling: evolution spent relatively little time optimizing for longevity because the conditions during most of human history simply didn't require it. This creates an opportunity — if aging wasn't strongly selected, it might be easier to intervene than if evolution had optimized against it. The biggest vulnerability is practical: understanding why we age doesn't automatically mean we know how to stop aging. But the evolutionary logic suggests we're not fighting millions of years of optimization — we're fighting a much smaller biological constraint.