On today’s show we are looking at our human ability to forecast non linear effects and in particular how this relates to economic forecasts. We are accustomed to looking at the world in very linear ways. When we see a car approaching most people are pretty good at estimating whether they have enough time to cross the road as long as the car is travelling at constant speed. But if the car is accelerating, virtually all people have a very hard time assessing whether it is safe to cross the road.

That’s the difference between a linear and a non linear system. Non linear systems have some form of acceleration.

We see these types of systems all over the place. Over the short term, if the acceleration is small, people have a tendency to make linear approximations which are accurate enough over the short term.

The US government makes regular updates to the financial health of the social security system. It’s no secret that the math which funds the social security system is breaking down. When social security was first conceived there were 16 people in the workforce for every one person collecting benefits. Demographics have changed and today there are less than 3 people contributing for every person collecting. Another non-linear effect.

We know that for the economy to grow, the population needs to grow. Shrinking working population means shrinking economy. This is a non-linear effect.

The industrial revolution replaced a lot of manual labour with machinery. It didn’t eliminate manual labor for all tasks. For those repetitive tasks that can be easily programmed, machines have replaced humans.

The theory was that machines could replace manual labor, but not thinking. Humans would continue to be the brains behind the work performed. But we do know that some knowledge work has already been replaced by AI and that proportion is only going to increase. So what happens to the falling demand for employees that have been replaced by AI? What will become of our society? Can we truly forecast the economy that is being impacted by so many non-linear factors?

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