When the World Curves

A note on linearity bias — or what I like to call false linearity.

Christian Keil (@pronounced_kyle) tweet: My 3-month-old son is now TWICE as big as when he was born. He's on track to weigh 7.5 trillion pounds by age 10. Two side-by-side photos: a dad holding his newborn, then holding the visibly bigger baby three months later.
The original tweet — @pronounced_kyle, Mar 16, 2024.

That joke has always been funny to me — and somehow that tweet by @pronounced_kyle always sends me back to the same idea: linearity bias, or what I like to call false linearity. I wanted to talk a little about that today.

Let’s start by drawing the exact example from the joke: how a person’s weight changes with age. Put years on the x-axis and weight on the y-axis. Draw a dotted line for what happens if the baby’s weight keeps increasing at the same rate forever — say, doubling every three months. Then a green line for the actual average change in a child’s weight from birth to age 10.

For that we can use real child-growth data — something like the WHO Child Growth Standards or the CDC growth charts is more than enough. Since the dotted line shoots upward so absurdly fast, we can just stop it partway and label it with something ridiculous like 7.5 trillion, to make the joke visually obvious.

Child weight: reality vs. false linearity

Typical child weight (WHO growth pattern) If weight doubled every 3 months
0204060801001200246810Age (years)Weight (kg)… ~7.5 trillionby age 10

The dotted line runs off the top of the chart before the second birthday. I just cut it and wrote the number. Real growth (green) barely looks like it is moving next to it.

Why the shortcut feels natural

In some sense, that graph is what linear thinking is: assuming a trend keeps moving the same way, in constant proportion to something else. And there’s nothing inherently wrong with it — it costs very little mental energy, and in everyday life we really do deal with plenty of systems that are close enough to linear. If 10 km takes an hour, 20 km takes two. If 1 kg of plov feeds 4 people, 2 kg feeds 8. These are simple cases where linear thinking works well enough.

The mistake is not using a line. The mistake is forgetting that the line is only a simplification.

But that kind of intuitive reasoning can’t explain everything in the world of cause and effect — just as a baby’s weight clearly doesn’t keep increasing at that rate forever. The baby example is easy to grasp because it’s familiar: we see the growth, but we also know from experience that growth changes shape over time.

Hero visual drawn from WHO child growth-chart medians; the doubling line is an illustrative extrapolation.

Where the line bends

Once you notice it, you start seeing false linearity everywhere. A lot of important relationships in life are not straight lines. They flatten, peak, bend, or change direction entirely.

Money and happiness

Many of us — especially those who don’t have much money — naturally think: the more I earn, the happier I’ll feel. Money does matter. But research suggests that past a certain point, extra income doesn’t lift happiness in the same dramatic way it did earlier. The curve bends; the relationship is no longer a straight line.

Based on Kahneman & Deaton (2010), and the later debate around Killingsworth’s work.

2.02.53.03.54.04.55.05.56.00255075100125150175200Annual income (USD, thousands)Reported well-beingroughly where gainsstart to flatten

Study hours and exam results

It’s easy to imagine a straight line: more hours studied, better results. But past some point, exhaustion, poor concentration, and diminishing returns kick in. The relationship can flatten — or bend into something closer to an inverted-U, depending on what exactly is measured.

More is better, until it isn’t.

657075808590024681012Study hours per dayExpected exam performanceuseful range

Savings and compound interest

Here the line fails the other way: reality curves up faster than we expect. Interest earns interest, so the balance gradually bends away from the steady climb we imagine.

Wonderful in a savings account, and kinda brutal on a credit card.

04080120160010203040YearsBalance (USD, thousands)interest earns interestwhat we picture

Technology adoption

New technologies often look like failures at first. Then they spread rapidly, before slowing down as the market becomes saturated. Slow, then sudden, then saturated — an S, not a line.

The trap is judging the slow beginning as if it were the whole story.

0204060801000246810Time (years)Adoption (%)slow, then sudden,then saturatedsteady guess

A few other places this shows up

  • exercise and recovery
  • product features and usability
  • advertising spending and new customers
  • medication dosage and effect

Linear thinking is a way of simplifying the world, and often a useful one. Linearity bias is our tendency to keep using that simplification after the conditions have changed. And false linearity is what appears when we stop treating the line as a model and start treating it as reality — ignoring the limits, thresholds, feedback loops, and diminishing returns that eventually make the world bend.

Sources. Child weight — WHO Child Growth Standards. Income and well-being — Killingsworth, Kahneman & Mellers, PNAS 2023. Study hours — IJETT 2024. Charts are illustrative, drawn to reflect the general shapes of the relationships discussed.